Configurable digital twins of chemical products

Abstract

This disclosure relates to apparatus for generating digital twin templates associated with a product or product class, as well as respective computer implementations and computer program elements; apparatus and systems for generating digital twins of the physical entities of a product, as well as respective computer implementations and computer program elements; methods for providing a product associated with such a digital twin, as well as respective apparatus and computer program elements; the use of a digital twin; a product associated with such a digital twin; computer implementations and apparatus for generating such a digital twin; and respective computer program elements.

Description

Technical Field

[0001] Technical Field The present disclosure relates to an apparatus for generating digital twin templates associated with a product or product class, and respective computer-implemented methods and computer program elements, an apparatus and system for generating a digital twin of a physical entity of a product, and respective computer-implemented methods and computer program elements, a method for providing a product associated with such a digital twin, and respective apparatuses and respective computer program elements, the use of a digital twin, a product associated with such a digital twin, such a digital twin, a computer-implemented method and apparatus for generating a digital access element associated with such a digital twin, and respective computer program elements.

Background Art

[0002] Background Art The production and supply chains of materials and products such as chemical materials and chemical products are strictly regulated to protect human safety and the environment. Therefore, manufacturers or importers of such materials and products need to document and provide information about this material and product in order to meet different regulatory requirements depending on the material, product, or location of production, consumption, or sale. Currently, such information is provided in various data formats, and the exchange and sharing of such data have become cumbersome. Therefore, it is required to standardize and customize the exchange and sharing of product data.

Summary of the Invention

Means for Solving the Problems

[0003] Summary of the Invention In one embodiment, the Disclosure relates to an apparatus for generating a digital twin template associated with a product or product class, wherein the digital twin template defines one or more aspect models, each aspect model describing a specific set of characteristics of the product or product class, and the apparatus comprises one or more computing nodes and one or more computer-readable media having computer-executable instructions, wherein when the computer-executable instructions are executed by one or more computing nodes, The step of receiving a request to generate a digital twin template, wherein the request includes product-related data, A step of providing a digital twin master template associated with one or more product classes, wherein the digital twin master template defines multiple aspect models, • A step of providing product data based on the data included in the received request, A step of optionally providing one or more additional aspect models, wherein the one or more additional aspect models are different from the multiple aspect models defined in the digital twin master template. The steps include: generating a digital twin template that, based on the provided product data, defines at least one aspect model defined in the digital twin master template, and optionally, at least one of the further aspect models provided; and The present invention relates to a device comprising a computer-readable medium configured to perform the following actions.

[0004] In a further embodiment, the Disclosure relates to a computer implementation for generating a digital twin template associated with a product or product class, wherein the digital twin template defines one or more aspect models, each aspect model describing a particular set of characteristics of the product or product class, and the Method The step of receiving a request to generate a digital twin template, wherein the request includes product-related data, A step of providing a digital twin master template associated with one or more product classes, wherein the digital twin master template defines multiple aspect models, • A step of providing product data based on the data included in the received request, A step of optionally providing one or more additional aspect models, wherein the one or more additional aspect models are different from the multiple aspect models defined in the digital twin master template. The steps include: generating a digital twin template that defines at least one aspect model defined from the digital twin master template, and optionally at least one of the further aspect models provided, based on the provided product data; and This relates to computer implementation methods, including

[0005] In a further aspect, the Disclosure relates to an apparatus for generating a digital twin of a physical entity of a product, wherein the apparatus comprises one or more computing nodes and one or more computer-readable media having computer-executable instructions, and when the computer-executable instructions are executed by one or more computing nodes, The step of receiving a request to generate a digital twin, wherein the request includes data related to the product, A step of collecting data associated with a chemical product from one or more data sources based on received data related to the product, wherein the data associated with the product includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data related to the production and / or use of the product, The steps include: providing the collected data and a decentralized digital twin identifier optionally associated with the data owner; The step of providing a digital twin template to be applied to collected product data based on data contained in a received request, wherein the digital twin template is generated by an apparatus for generating digital twin templates disclosed herein or in accordance with a computer implementation method for generating digital twin templates disclosed herein. The process involves generating a digital twin dataset by applying each aspect model defined in the provided digital twin template to the collected data, and The steps include: generating a digital twin that includes the provided decentralized identifier and the generated digital twin dataset; The present invention relates to a device comprising a computer-readable medium configured to perform the following actions.

[0006] In a further embodiment, the Disclosure relates to a computer-aided method for generating a digital twin of a physical entity of a product, wherein the method is The step of receiving a request to generate a digital twin, wherein the request includes data related to the product, A step of collecting data associated with a product from one or more data sources based on received data related to the product, wherein the data associated with the product includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data related to the production and / or use of the product, The steps include: providing the collected data and a decentralized digital twin identifier optionally associated with the data owner; The step of providing a digital twin template to be applied to collected product data based on data contained in a received request, wherein the digital twin template is generated by an apparatus for generating digital twin templates disclosed herein or in accordance with a computer implementation method for generating digital twin templates disclosed herein. The process involves generating a digital twin dataset by applying each aspect model defined in the provided digital twin template to the collected data, and The steps include: generating a digital twin that includes the provided decentralized identifier and the generated digital twin dataset; This relates to computer implementation methods, including

[0007] In a further embodiment, the Disclosure relates to a system for generating a digital twin of the physical entity of a product, wherein the system A data source layer configured to provide data associated with a product from one or more data sources, wherein the data associated with the product includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product. A service layer configured to optionally collect data provided by one or more data sources, optionally transform the collected data, and provide the collected or transformed data. A consumer layer that consumes data provided by one or more data sources or provided by a service layer and is configured to generate a digital twin in accordance with a computer implementation method for generating a digital twin disclosed herein, A connector layer comprising at least one decentralized data serving network node, optionally configured to provide access to the generated digital twin and / or at least one digital twin dataset contained in the digital twin by at least one decentralized data consuming network node associated with a decentralized network participant. Regarding a system that includes the following features.

[0008] In a further aspect, the Disclosure relates to a system for providing a product associated with a digital twin, wherein the digital twin includes a decentralized digital twin identifier and at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product, and the system • Production configured to produce a product from one or more input materials, A requester configured to generate requests for generating a digital twin, wherein the request includes product-related data, • An apparatus for generating a digital twin as disclosed herein, or a system for generating a digital twin as disclosed herein, for generating a digital twin of the physical entity of the product disclosed herein. • An assigner configured to assign the physical identifier associated with a manufactured product to a decentralized identifier included in the digital twin. Regarding a system that includes the following features.

[0009] In a further aspect, the Disclosure relates to a method for providing a product associated with a digital twin, wherein the digital twin includes a decentralized digital twin identifier and at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product, and the Method • Production involves producing a product from one or more input materials, • Generating a digital twin using an apparatus or system for generating a digital twin disclosed herein, or in accordance with a computer implementation method for generating a digital twin disclosed herein, • Assigning the physical identifier associated with the manufactured product to the decentralized digital twin identifier included in the generated digital twin. This includes methods.

[0010] In a further embodiment, the Disclosure relates to a computerized method for providing a product associated with a digital twin, wherein the product is produced by production from one or more input materials, and the method • Receiving a request to generate a digital twin, wherein the request includes data related to the product. • Collecting product-related data from one or more data sources based on received data relating to chemical products, wherein the product-related data includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data related to the production and / or use of the product. Based on the physical identifier associated with the product, a decentralized digital twin identifier is provided that is associated with the collected data and, optionally, with the data associated with the data owner, and the provided decentralized digital twin identifier is assigned to the physical identifier. • To provide a digital twin template to be applied to collected product data based on data contained in a received request, wherein the digital twin template is generated by an apparatus for generating digital twin templates disclosed herein, or in accordance with a computer implementation for generating digital twin templates disclosed herein. · For each aspect model defined in the provided digital twin template, generating a digital twin data set by applying each aspect model to the collected data, and · Generating a digital twin including the provided decentralized identifier and the generated digital twin data set relates to a computer-implemented method including.

[0011] In a further aspect, the disclosure is a computer-implemented method for providing access to a digital twin of a physical entity of a product, wherein access to the digital twin by one or more decentralized data consumption network nodes associated with decentralized participants of a decentralized network is controlled by a decentralized data providing network node associated with the digital twin, and the digital twin is generated according to a computer-implemented method for generating a digital twin disclosed herein or by an apparatus or system for generating a digital twin disclosed herein, and the method comprises · Receiving, at a decentralized data providing network node associated with the digital twin, a request to access the digital twin or a portion thereof by at least one decentralized data consumption network node, the request including a decentralized identifier associated with the digital twin, · Optionally, authenticating and / or authorizing, by the decentralized data providing network node, the request to access the digital twin or a portion thereof, · Providing, by the decentralized data providing network node, access to the digital twin or a portion thereof to the decentralized data consumption network node based on the decentralized digital twin identifier and optionally on authenticating and / or authorizing, relates to a computer-implemented method including.

[0012] In a further aspect, the Disclosure relates to a digital twin generated in accordance with a computer implementation method for generating a digital twin disclosed herein, or by an apparatus or system for generating a digital twin disclosed herein.

[0013] In a further aspect, this disclosure relates to the use of the digital twins disclosed herein for processing products associated with the digital twin.

[0014] In a further aspect, this disclosure relates to products associated with the digital twin disclosed herein.

[0015] In a further embodiment, the Disclosure relates to a computer implementation for generating digital access elements associated with a digital twin of a product, wherein the method is To generate a digital twin associated with a chemical product in accordance with the computer implementation method for generating a digital twin disclosed herein, or by an apparatus or system for generating a digital twin disclosed herein, • Receiving requests to provide decentralized access element identifiers associated with the digital twin of a product, • Provide decentralized access element identifiers upon request, and generate a digital access element that includes the provided decentralized access element identifiers and access data associated with the digital twin. Optionally, to provide generated digital access elements for accessing the digital twin or a portion thereof by a decentralized data consumption network node, under the control of a decentralized data provision network node associated with the data owner of the digital twin or a portion thereof. This relates to computer implementation methods, including

[0016] In a further aspect, the Disclosure relates to an apparatus for or for generating access elements associated with a digital twin of a product, wherein the apparatus comprises one or more computing nodes and one or more computer-readable media having computer-executable instructions, wherein the apparatus, when executed by one or more computing nodes, configures to perform a computer implementation method for generating the digital access elements disclosed herein.

[0017] In a further embodiment, the Disclosure relates to a computer element, such as a computer-readable storage medium containing instructions, a computer program, or a computer program product, wherein, when the instructions are executed by a computing node or computing system, the instructions instruct the computing node or computing system to perform steps of the method disclosed herein.

[0018] In a further aspect, the Disclosure relates to a computer element, such as a computer-readable storage medium containing instructions, a computer program, or a computer program product, wherein the instructions, when executed by an apparatus or system disclosed herein, instruct such apparatus or system to perform steps configured to be performed by such apparatus or system.

[0019] In a further embodiment, the Disclosure relates to a digital twin template generated by the apparatus disclosed herein or by a computer implementation method for generating a digital twin template disclosed herein.

[0020] In a further aspect, this disclosure relates to the use of the digital twin templates disclosed herein for generating a digital twin of the physical entity of a product.

[0021] All disclosures, embodiments, and examples described herein relate to the methods, systems, apparatus, digital twin templates, digital twins, products, and computer elements described above and below. Advantageously, any benefits derived from any one embodiment or example are equally applicable to all other embodiments and examples.

[0022] Embodiment The methods, systems, apparatus, digital twin templates, digital twins, products, uses, and computer elements disclosed herein provide an efficient and robust way to generate customized digital twin templates using a modular approach by selecting one or more aspect models from a digital twin master template that defines multiple aspect models existing for a product or product class in a hierarchical order. A customized digital twin template for a given product or product class can be generated by matching at least a portion of the product data associated with the product or product class with data points defined by the aspect models included in the digital twin master template. This customized digital twin template includes at least some of the aspect models of the digital twin master template that define data points matching at least a portion of the product data. Thus, the digital twin master template may represent a set of aspect models that can be used to generate customized digital twin templates by selecting one or more aspect models based on the product data associated with a given product or product class. The generation of digital twin templates may further include the selection of additional aspect models not included in the digital twin master template, allowing for consideration of product specificities not adopted by the aspect models included in the digital twin master template. This modular approach allows for the selection of appropriate aspect models of products that meet regulatory requirements for the products being manufactured (e.g., aspect models necessary to describe properties such as chemical and / or physical properties) from a digital twin master template and optionally from further available aspect models. Thus, the digital twins of products generated from such customized digital twin templates have a highly defined data structure, simplifying data exchange and sharing, while simultaneously ensuring that they include all relevant data necessary to meet regulatory requirements.This modular approach significantly reduces the complexity associated with generating a single aspect model for each product or product class, enabling the efficient generation of digital twin templates for various different products or product classes. Furthermore, the modular approach avoids the problems associated with maintaining a single large-scale aspect model and the use of inappropriate semantic descriptions for specific products or product classes within such a single large-scale aspect model, thus avoiding empty attributes resulting from missing product data in the digital twin.

[0023] By associating digital twins generated from digital twin templates with decentralized identifiers, simplified and customizable data sharing or exchange becomes possible within the product ecosystem, including the chemical industry, chemical supply chain stakeholders, end-product manufacturers, and optionally end-product recycling chain stakeholders. In this way, while data ownership remains with the raw material suppliers supplying the chemical industry, chemical suppliers supplying upstream stakeholders, end-product manufacturers, and recycling chain stakeholders, respectively, more reliable and efficient further processing of raw materials supplied by the chemical industry, chemical products supplied by upstream stakeholders in the chemical supply chain, and / or end-product recycling by stakeholders in the product recycling chain can be achieved. By further including one or more authorization mechanisms, data sharing or exchange can be made more flexible, with multiple data consumption network nodes from different stakeholders in the chemical supply chain accessing the data contained in the digital twin.

[0024] The objective of the present invention is to provide a simplified, standardized, and customizable sharing or exchange of product data associated with various different products within a product ecosystem, including the chemical industry, chemical supply chain stakeholders, end-product manufacturers, and optionally, end-product recycling chain stakeholders.

[0025] These objectives, and other objectives that will become apparent from the following description, are addressed by the subject matter of the independent claims. Dependent claims refer to preferred embodiments of the invention.

[0026] The following outlines several embodiments of this disclosure as examples. It should be understood that this disclosure is not limited to the above embodiments and / or examples.

[0027] In one embodiment, a digital twin of a product may be a digital representation of the physical entities of a product, having a defined semantic description of those physical entities. Thus, a digital twin of a product's physical entities is a digital version of those physical entities. Once created, a digital twin can be used to represent the physical entities of a product in a digital representation of a real-world system. A digital twin may be uniquely linked to a physical product, at least via a decentralized digital twin identifier. A digital twin may be created to be identical to the form and behavior of the corresponding product. In addition, a digital twin may reflect the characteristics of a product throughout its lifespan. For example, a sensor may capture real-time (or near real-time) data, such as transport or usage data, from a physical product and relay it to a remote digital twin. The sensor may include hard sensors and / or soft sensors. The digital twin may then be updated to maintain its correspondence with the physical entities of the product. Thus, a digital twin may represent the current state of the physical entities of a product at any given time. A digital twin may contain one or more digital twin datasets. At least one digital twin dataset may include at least one measured physical and / or chemical property of a product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product. Each digital twin dataset may include defined product data. Each digital twin dataset may be associated with a decentralized digital twin identifier. Each digital twin dataset may be further associated with a digital twin dataset identifier. This makes it possible to uniquely identify each digital twin dataset included in the digital twin by using the digital twin dataset identifier associated with the digital twin dataset. A digital twin may include a decentralized digital twin identifier, digital twin datasets, and digital twin dataset identifiers associated with the digital twin datasets. A digital twin may further include a product identifier.

[0028] In one embodiment, an aspect model (also referred to as a data model) may include a semantic description of each digital twin dataset associated with the digital twin. The semantic description may include the structure and / or characteristics of at least some of the digital twin datasets. The characteristics of the digital twin datasets may include data types. The characteristics of the digital twin datasets may include possible or acceptable values ​​and / or value ranges. The characteristics of the digital twin datasets may be physical units of parameters described by the values ​​contained in the digital twin datasets. The characteristics of the digital twin datasets may include one or more attributes. The aspect model may define (i) data structures of at least some of the digital twin, such as digital twin datasets, obtained from applying the aspect model to product data associated with physical entities of a product or product class, and (ii) one or more data points contained in such parts of the digital twin. The data points may define the physical and / or chemical properties of the product or product class. The data points may define data associated with the production of the product. The data points may define data associated with the use of the product and / or the disposal or recycling of the product. Therefore, an aspect model can function as a blueprint for a given digital twin dataset obtained by applying such an aspect model to product data. Thus, an aspect model can correspond to a machine-readable semantic description of a digital twin or a part thereof. A data structure can correspond to a blueprint or template for organizing data such as product data, and data points can define the actual content of the data. A data structure can define acceptable data types such as numbers, strings, and Booleans, and / or relationships such as linear order in arrays and parent-child relationships in trees. An aspect model may further specify processing rules associated with one or more data points and / or the digital twin dataset. Processing rules may include conversion rules for converting product data from one format to another and / or calculation rules for performing calculations on product data.In one embodiment, a digital twin master template may refer to a superset of aspect models defined for one or more product classes. For example, a superset of aspect models may be associated with the product class "Chemical Products" and may include multiple aspect models defined for Chemical Products. A superset of aspect models may include multiple aspect models. The aspect models included in the superset may be different from each other. Multiple aspect models may include at least two different aspect models. A digital twin master template may include a tree structure that includes a root entity or root node connected to multiple aspect models. A digital twin master template may include a hierarchical tree structure having a set of connected nodes represented by aspect models. Each aspect model in the tree may be connected to one or more child nodes (e.g., sub-aspect models) and strictly one parent node, excluding a root node that does not have a parent node or aspect model. The root entity may correspond to the product class to which the digital twin master template is associated. For example, a digital twin master template associated with the product class "Chemical Materials" may define Chemical Materials as the root entity.

[0029] In one embodiment, a digital twin template may refer to a subset of aspect models for several aspect models defined in a digital twin master template. Thus, a digital twin template may include a selection of aspect models defined in the digital twin master template. The digital twin template may further include at least one additional aspect model not defined in the digital twin master template. This allows the digital twin template to be customized to include all the aspect models necessary to adequately describe the physical product in the digital world. A digital twin template may be used to generate a digital twin or a portion thereof associated with the physical entity of a product. The digital twin or a portion thereof may be generated by applying the digital twin template to product data associated with the physical entity of the product.

[0030] In one embodiment, a product class may represent a general term applicable to multiple specific products. For example, the product class "polymer" may apply to all chemical compounds that represent polymers. In another example, the product class "automotive seat" may apply to all products that represent automotive seats.

[0031] In one embodiment, a computing node may comprise at least one hardware processor and memory. The computing node may contain program code. The program code may be referred to as an executable component, executable instruction, computer executable instruction, or instruction. The structure of an executable component may exist in computer-readable media such that, when interpreted by one or more processors of the computing node, it causes the computing node to perform the functions described herein. The processor of each computing node may direct the operation of each computing node in response to executing computer executable instructions that constitute the executable component.

[0032] In one embodiment, the product is a chemical product. A chemical product may be a chemical product obtained from at least one chemical reaction. A chemical product may include natural chemical products. Natural chemical products may include any chemical product produced naturally without human interaction or intervention, i.e., any untreated chemical substance found in nature, such as chemicals from plants, microorganisms, animals, the earth, and the sea, or any chemical substance found in nature and extracted using a process that does not alter its chemical composition. Natural chemical products may include biological preparations such as enzymes and naturally occurring inorganic or organic chemical products. Natural chemical products may be separated and purified before use, or may be used in an unseparated and / or unpurified form. A chemical product may be a synthetic chemical product. Synthetic chemical products may include chemical products produced by human interaction or intervention. Synthetic chemical products may be produced using the same chemical reactions that occur in nature, or using different chemical reactions. A chemical product may be any inorganic or organic chemical product obtained by the reaction of inorganic and / or organic chemical reactants. Inorganic and organic chemical reactants may be natural chemical products or synthetic chemical products. A chemical reaction can include any chemical reaction generally known in the art in which reactants are converted into one or more different chemical products. A chemical reaction can include the use of catalysts, enzymes, bacteria, etc., to achieve the chemical reaction between reactants. A chemical product can include raw materials. A chemical product can include chemical materials produced by reacting at least two raw materials and / or intermediate products.

[0033] Chemical products may be produced by chemical production from one or more materials. Materials may include raw materials, intermediate chemicals, or chemical products received from suppliers. Chemical production may be a chemical production network comprising multiple interconnected processing steps. A chemical production network may be an integrated chemical production network having interconnected production chains. A chemical production network may include multiple different production chains sharing at least one intermediate. A chemical production network may include multiple stages of a chemical value chain. A chemical production network may include multiple production chains producing chemical products as outputs from one or more input materials as inputs. A chemical production network may include multiple tiers of a chemical value chain. A chemical production network may include an arrangement of physically interconnected production sites. Production sites may be in the same location or in different locations. In the latter case, production sites may be interconnected by dedicated transport systems such as pipelines, supply chain vehicles such as trucks, supply chain ships, or other means of freight transport. Chemical production may be controlled by an operating system. An operating system may be configured to perform the methods disclosed herein. An operating system may include the apparatus and systems disclosed herein.

[0034] In one embodiment, the product is a component, a component assembly, a final product, a used product, or recycled material. A component may be produced using one or more chemical products. Recycled material may include any material obtained by performing at least one recycling step in the recycling chain related to the product. A used product may include a product that can no longer be used as intended and has been designated as waste.

[0035] In one embodiment, product-related data includes a product identifier, product class, or a combination thereof. The product identifier may include a batch number, product name, product ID, part number, lot number, or a combination thereof. The lot number may be assigned to the product at the time of production.

[0036] In one embodiment, the set of characteristics described by each aspect model defined in the digital twin template and / or digital twin master template may include the chemical and / or physical characteristics of a product or product class. Chemical characteristics may be characteristics of a product that become apparent during or after a chemical reaction. Therefore, chemical characteristics may be any quality that can only be established by altering the chemical identity of a product. Examples of chemical characteristics include heat of combustion, enthalpy of formation, toxicity, chemical stability in a given environment, flammability, oxidation state, corrosiveness, combustibility, acidity and basicity, chemical product composition, recyclable content used to produce or manufacture a chemical product, biobase content used to produce or manufacture a chemical product, renewable material content used to produce or manufacture a chemical product, and pH value. Physical characteristics may be any measurable characteristics that can therefore be obtained using sensors. Therefore, the values ​​of physical characteristics describe the state of a product. Examples of physical properties include absorption, brittleness, boiling point, capacitance, color, concentration, density, ductility, distribution, effectiveness, elasticity, charge, conductivity, electrical impedance, potential, flow rate, fluidity, hardness, heat capacity, inductance, intrinsic impedance, brightness, luminescence, gloss, mass, melting point, opacity, transmittance, dielectric constant, plasticity, pressure, radiance, resistivity, reflectivity, refractive index, solubility, specific heat, strength, stiffness, temperature, tension, thermal conductivity, thermal resistance, viscosity, volume, and wave impedance.

[0037] In one embodiment, the digital twin master template is provided from a database. The database may be a central database. The database may be part of a decentralized network. The decentralized network may be a decentralized peer-to-peer communication network. The decentralized network may include participant network nodes associated with participants in a product ecosystem and may be configured to perform data transactions. Decentralized participant nodes may include network nodes in the decentralized network. Network nodes associated with participants in a product ecosystem may be associated with raw material chemical suppliers, intermediate chemical manufacturers, intermediate component manufacturers, component manufacturers, component assembly manufacturers, final product manufacturers, or participants in the recycling chain related to the final product. Data transactions may be based on a transaction protocol that includes an authentication mechanism and / or authorization mechanism. Based on the authentication and / or authorization mechanism, peer-to-peer communication may be established between decentralized network nodes associated with participants in a product ecosystem. One or more authentication mechanisms may be associated with or linked to decentralized digital twin identifiers and / or decentralized access element identifiers. One or more authentication mechanisms may be associated with or linked to decentralized participant identifiers associated with participants in a decentralized network.

[0038] Digital twin master templates stored in a database can be accessed by decentralized data consumption network nodes. Decentralized data consumption network nodes can be part of a decentralized system. Decentralized data consumption network nodes can be associated with stakeholders in the product ecosystem that generate digital twin templates. Decentralized data consumption network nodes can contain computer executable instructions for accessing and / or processing data within a decentralized network. Stored digital twin master templates can be provided by decentralized data provision network nodes associated with the database. Decentralized data provision network nodes can be part of a decentralized network. Decentralized data provision network nodes can contain computer executable instructions for providing to and / or processing data within a decentralized network. Decentralized configurations enable more efficient use of computing resources.

[0039] In one embodiment, a digital twin master template includes one or more digital representations that include and / or refer to multiple aspect models. A digital representation may include endpoints for data exchange or sharing (resource endpoints) or service interaction (service endpoints) that are uniquely identified via a communication protocol. A digital representation can be considered a locator indicating the location or dedicated data storage where each aspect model is stored. Using digital representations reduces the amount of data included in the digital twin master template, and therefore reduces the amount of data associated with providing the digital twin master template. Furthermore, the use of digital representations allows for greater flexibility in modifying the aspect models included in the digital twin master template, as only each aspect model needs to be modified without needing to modify the digital twin master template itself. Therefore, using digital representations within a digital twin master template minimizes the amount of data included in the template, enabling more efficient data transfer and maintenance of the digital twin master template.

[0040] In one embodiment, a digital twin master template defines relationships between one or more aspect models from among a plurality of aspect models defined in the master template. Relationships may define required and optional aspect models. Relationships may define a tree structure of the plurality of aspect models defined in the digital twin master template. The tree structure may include one or more levels that result in a hierarchical order of the aspect models defined in the digital twin master template. Relationships between aspect models at higher tree levels and aspect models at subsequent lower tree levels may be described as parent-child relationships. For example, an aspect model at a higher tree level may be represented as a parent aspect model, while an aspect model associated with the parent aspect model at a subsequent lower tree level may be represented as a child aspect model. Relationships may be defined by relational expressions that specify the parent aspect model associated with a child aspect model, and / or the child aspect models associated with each parent aspect model. Relational expressions may specify the type of relationship between each parent aspect model and the child aspect models associated with each parent aspect model. For example, a relational expression associated with a root entity (or root node) may specify the child aspect models associated with the root entity, and the relational type between the root entity and each child aspect model. The relational type may specify whether each child aspect model can be a required or optional aspect model. Required aspect models can be defined by a 1:1 or 1:at least one relational type. Optional aspect models can be defined by a 1:0 or more relational types. The relational type may specify the number of child aspect models associated with a parent aspect model. For example, a 1:1 relational type may be used to define that exactly one child aspect model is associated with a parent aspect model. In another example, a 1:many relational type may be used to define that two or more child aspect models can be associated with each parent aspect model.Relational expressions can be associated with their respective parent aspect models. Relational expressions can be associated with their respective child aspect models.

[0041] In one embodiment, a plurality of aspect models include at least one required aspect model and at least one optional non-required aspect model. The required aspect model may include an aspect model that needs to be selected from a plurality of aspect models included in the digital twin master template when generating the digital twin template. By defining an aspect model as a required aspect model within the digital twin master template, it is ensured that data required by legal and / or regulatory frameworks is included in the digital twin generated from each digital twin template, thus avoiding the provision of additional data along with the digital twin. This enables the standardization of product data exchange and sharing within the product ecosystem. The non-required aspect model may include an aspect model that can be selected from a plurality of aspect models included in the digital twin master template when generating the digital twin template. By defining an aspect model as a non-required aspect model, it becomes possible to generate digital twin templates in a flexible, modular manner. This is because aspect models that are not suitable for a particular product or product class for which a digital twin template should be generated do not need to be selected and are therefore not included in the digital twin template. This avoids the existence of empty data fields resulting from the use of aspect models that define data types and attributes that are not available or applicable to a particular product or product class. Required and optional aspect models can be defined through relational expressions and associated relational types, as described above.

[0042] At least one required aspect model may include an aspect model defining digital twin data, an aspect model defining digital twin template data, an aspect model defining product safety data, an aspect model defining product producer data, an aspect model defining product identification data, an aspect model defining product composition data, an aspect model defining product parameter data, an aspect model defining product handling data, an aspect model defining product disposal data, or a combination thereof.

[0043] Non-essential aspect models may include aspect models defining product packaging data, aspect models defining certificates for analytical data associated with a product, aspect models defining emissions data associated with a product, aspect models defining production data associated with a product, aspect models defining technical data associated with a product, aspect models defining certificate data associated with a product, aspect models defining data about suppliers of materials used to produce a product, aspect models defining data about the supply of a product to consumers, aspect models defining data about product registration, or a combination thereof.

[0044] In one embodiment, product data includes data or classes of data to be included in the digital twin associated with the product. Classes of data may include data related to product use, data related to product production, product composition data, product characteristic data, data associated with the product's ecological profile, regulatory data associated with the product, certificates associated with the product, or a combination thereof. Product data may further include one or more product identifiers and / or product names. At least one product identifier may correspond to a product identifier included in a received request.

[0045] Data related to product use may include, for example, data related to further processing of the product by using the product in further chemical reactions and / or as a reactant in the manufacturing process. Data related to product use may include data related to product handling and / or disposal. Data related to product use may include data related to recycling processes associated with the product. Data related to product production may include any data related to the production of the product at any stage in the product value chain. The above data may include production data from the production of the product. Production data may include monitoring and / or control data associated with the production of the product. Production data may include measurement data related to product quality at any stage in the product value chain.

[0046] Product characteristic data may include the measured and / or determined chemical and / or physical characteristics of the product described above. At least one measured physical and / or chemical characteristic may be acquired by a sensor configured to measure physical and / or chemical characteristics. The sensor may be included in a measuring device. The sensor may correspond to a measuring device. For example, the physical and / or chemical characteristics may include characteristics provided by a sensor in a mobile device such as a camera, or by a measuring device configured to measure at least one physical and / or chemical characteristic.

[0047] Data associated with a product's ecological profile may include, or correspond to, product emission data, product recyclable content data, product bio-based content data, product renewable material content data, or a combination thereof. Emission data may include any data related to the environmental footprint. The environmental footprint may refer to an entity and its associated environmental footprint. The environmental footprint may be entity-specific. For example, the environmental footprint may relate to a product, a company, a process such as a manufacturing process, raw materials or basic substances, chemical products or materials, components, component assemblies, finished products, combinations thereof, or additional entity-specific relationships. Emission data may include data related to the product's carbon footprint, i.e., product carbon footprint (PCF). Emission data may include, for example, data related to greenhouse gas emissions released during the production of a product. Emission data may include data related to greenhouse gas emissions. Greenhouse gas emissions may include emissions such as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbon (HFC), perfluorocarbon (PFC), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3), combinations thereof, and additional emissions. Emission data may include data related to greenhouse gas emissions from the activities of the entity or company itself (production, power supply to plants, and waste incineration). Scope 2 may include emissions from externally supplied energy production. Scope 3 may include all other emissions along the value chain. Specifically, this may include greenhouse gas emissions from raw materials obtained from suppliers. The product carbon footprint (PCF) may sum up greenhouse gas emissions and removals from a series of interconnected process steps associated with a particular product. Cradle-to-gate plant-climate emissions (PCFs) can be the sum of greenhouse gas emissions based on selected process steps, for example, from resource extraction to the factory gate where the product leaves the company. Such PCFs may be called partial PCFs.To achieve such aggregation, each company providing any product may provide Scope 1 and Scope 2 contributions to the PCF for each product. Recycled content data, bio-based content data, and renewable material content data may include any data relating to the recycled content, bio-based content, or renewable material content used to produce or manufacture the physical entity of the product.

[0048] Regulatory data associated with a product may include, or correspond to, product declaration data, product safety data, certificates of analytical data associated with the product, or a combination thereof.

[0049] In one embodiment, product data is provided from one or more databases based on data included in an received request. For example, data may be requested from a database, or retrieved from a database based on a product identifier included in an received request. The database may be associated with a production that produces a product from one or more materials that enter production. The database may be a distributed data source. A distributed data source may be a collection of data stored at different locations on a computer network. Each location may exhibit some degree of autonomy, not only providing services for the execution of local applications but also participating in the execution of global applications. For example, a distributed data source may be a distributed database. A distributed database can be created by dividing the data of an existing database and distributing it to different locations, or by merging multiple existing databases together. Each data source may contain only fragments of product data. This results in the fragmentation of the data. Two common types of data fragmentation are horizontal fragmentation, where (possibly overlapping) subsets of data tuples are stored at different locations, and vertical fragmentation, where (possibly overlapping) subtuples of data tuples are stored at different locations. More generally, product data can be fragmented into a set of relationships (relational database tables distributed across multiple locations).

[0050] In one embodiment, at least one further aspect model is provided from a database. The database may be a central database. The database may be part of a decentralized network, as described above. The further aspect models stored in the database may be accessed by decentralized data consumption network nodes, as described above. Decentralized data consumption network nodes may be associated with stakeholders in the product ecosystem that generate digital twin templates. The stored further aspect models may be provided by decentralized data provision network nodes associated with the database, as described above.

[0051] In one embodiment, at least one further aspect model is provided based on the provided product data. For example, the provided product data may be used to determine a further aspect model that matches the above product data or a portion thereof. The determined further aspect model may then be provided. By using further aspect models not defined in the digital twin master template, it becomes possible to generate a digital twin template for a product in a flexible manner so that the digital twin of the product generated using the above digital twin template includes all the necessary data. Thus, available aspect models (e.g., aspect models defined in the digital twin master template and further aspect models) can be combined in a modular manner to design a digital twin template for a particular product or product class, thereby generating a digital twin for such product or product class that includes at least all the data necessary to meet the regulatory requirements associated with such product or product class. The modular approach further allows for consideration of requirements imposed by consumers and further downstream stakeholders in the product value chain, as well as / or stakeholders in the recycling chain associated with the product. This ensures that the digital twin template includes all the aspect models necessary to meet not only regulatory requirements but also any further requirements imposed by stakeholders in the product ecosystem.

[0052] In one embodiment, generating a digital twin template includes selecting at least one aspect model from a plurality of aspect models defined in a provided digital twin master template based on provided product data, and optionally selecting at least one of further provided aspect models. Selecting at least one aspect model from a plurality of aspect models defined in a digital twin master template may include mapping the provided product data to the aspect models defined in the digital twin master template. The mapping may include matching the provided product data with aspect model data associated with the aspect models defined in the digital twin master template. The mapping may include matching the provided product data with data point chemical and / or physical properties defined by the aspect models included in the digital twin master template. If the provided product data can be mapped to one or more aspect models defined in the digital twin, the above aspect models may be selected. Selecting at least one aspect model from further provided aspect models may include mapping the provided product data to further aspect models, as described above.

[0053] In one embodiment, the digital twin template includes at least one aspect model defined in the digital twin master template and optionally at least one of the further aspect models provided, and / or includes one or more digital representations defined in the digital twin master template and optionally one or more digital representations pointing to at least one of the further aspect models provided. Thus, the digital twin template may include a subset of the aspect models defined in the digital twin master template. The digital twin template may include additional aspect models not defined in the digital twin master template. This makes it possible to generate a digital twin template that includes all the aspect models necessary to meet regulatory requirements and further requirements imposed by stakeholders in the product ecosystem.

[0054] In one embodiment, a generated digital twin template may be provided. Providing the generated digital twin template may include providing the digital twin template to a database. The digital twin template may be correlated with data associated with products and / or product data in the database. For example, the digital twin template may be correlated with one or more identifiers associated with products or product classes in the database. Providing the digital twin template may include providing the template via a communication interface for display. This makes it possible to control the aspect models defined in the template to ensure that all necessary aspect models are properly defined. This avoids data loss in the digital twin generated from the digital twin template and therefore ensures that the digital twin generated from the digital twin template contains all necessary data.

[0055] In one embodiment, the apparatus for generating a digital twin template further performs the step of updating a digital twin master template with one or more additional aspect models defined in the generated digital twin template. Updating may include defining one or more additional aspect models in the digital twin master template. The updated digital twin master template may be provided to a database, such as a database that stores digital twin master templates as described above. By updating the digital twin master template with additional aspect models, it becomes possible to generate digital twin templates and increase the number of aspect models available for sharing the generated aspect models for a particular product or product class with other stakeholders in the product ecosystem. This allows for more efficient generation of digital twin templates due to the increased number of available aspect models that can be used in a modular approach when generating digital twin templates.

[0056] In one embodiment, one or more of the selected further aspect models defined in the generated digital twin template may be provided for updating the digital twin master template. The further aspect models may be provided to a third party, such as a party operating a database that stores the digital twin master templates, and the third party may update each digital twin master template using at least a portion of the provided aspect models.

[0057] Digital twin templates generated by the apparatus or methods disclosed herein can be used to generate further digital twin templates for different products or product classes. Thus, the generated digital twin templates can function as digital twin master templates for further products or product classes. This allows for the reuse of existing digital twin templates that define a reduced number of aspect models for the digital twin master template, thereby reducing the number of aspect models that must be mapped to product data when generating further digital twin templates.

[0058] Digital twin templates generated by the apparatus or methods disclosed herein may be used to generate digital twins of the physical entities of a product. For example, a digital twin template associated with a product or product class generated by the apparatus or methods disclosed herein may be used to generate digital twins of products belonging to such product or product class.

[0059] A digital twin may include a decentralized digital twin identifier and one or more digital twin datasets. The decentralized digital twin identifier may include any unique identifier uniquely associated with the digital twin and / or digital twin datasets, and optionally, the data owner. The decentralized digital twin identifier may link the physical entities of a product to the digital twin. The decentralized digital twin identifier may include one or more universally unique identifiers (UUIDs) or digital identifiers (DIDs). One or more DIDs and / or UUIDs may be associated with the digital twin and / or digital twin datasets. One or more DIDs and / or UUIDs may be further associated with a product. The decentralized digital twin identifier may be generated by the data owner or on behalf of the data owner of the digital twin data. The decentralized digital twin identifier may include authentication information. Access to the digital twin generated from the data, or to parts of the digital twin such as digital twin datasets contained within the digital twin, can be controlled by the data owner, via a decentralized digital twin identifier and its unique association with the digital twin (and thus the product) and optionally with the data owner. This is in contrast to a centralized authorization scheme, in which the identifier is provided by such centralized authorization and access to the data is controlled by such centralized authorization. In this context, decentralized refers to the use of decentralized identifiers in embodiments controlled by the data owner. A decentralized digital twin identifier may include, or be associated with, one or more identifiers used in a decentralized network that enable data exchange over the decentralized network. For example, a decentralized digital twin identifier may include, or be associated with, a digital twin dataset identifier of a digital twin dataset, such as a UUID of a digital twin dataset. Any combination of UUIDs and DIDs is possible. For example, a decentralized digital twin identifier may be a DID, while a digital twin data identifier may be a UUID.In another example, decentralized digital twin identifiers and digital twin data identifiers may be UUIDs. Data exchange may include the discovery of the decentralized identifier and, optionally, the identifier associated with the decentralized identifier of the participant nodes of the decentralized network, the authentication of the participant nodes of the decentralized network, and / or authorization of data transfer via peer-to-peer communication between the participant nodes of the decentralized network. Decentralized digital twin identifiers may be associated with any participant in a product ecosystem, including chemical raw material suppliers, intermediate chemical product manufacturers, intermediate component manufacturers, component manufacturers, component assembly manufacturers, final product manufacturers, or recycling chain participants. Decentralized digital twin identifiers may be associated with machines, systems, or devices used in the manufacture of raw materials, basic materials, chemical products, intermediate products, components, component assemblies, or final products, or in the execution of at least one recycling step in a recycling chain related to a product, or with a collection of such machines, devices, and / or systems.

[0060] A decentralized digital twin identifier can be linked to other decentralized product identifiers according to the physical relationship between a product entity and other physical entities, such as what is produced using or from the product. Thus, a decentralized participant node in a decentralized network may be able to interpret the relationship of a physical chemical product entity to a decentralized digital twin identifier that corresponds to the physical relationship of the physical chemical entity to other physical entities. By linking a decentralized digital twin identifier to other decentralized product identifiers, it becomes possible to determine a decentralized participant node that stores collected data associated with the use of the product or determined physical and / or chemical properties. The collected data and / or determined chemical and / or physical properties may be provided by the decentralized participant node and stored in the digital twin. For example, a new dataset may be generated by applying an aspect model associated with the use of the product, and this new dataset may be used to update the digital twin.

[0061] A decentralized digital twin identifier can be associated with the physical entity of a product. A decentralized digital twin identifier can be associated with the physical entity of the product from which the digital twin is generated. A decentralized digital twin identifier can be associated with the physical entity of the product to which the generated product dataset is associated.

[0062] A decentralized digital twin identifier may be, or may be assigned to, a physical identifier associated with a product. The association of a physical identifier with a product may be provided by a physical association with a physical product or physical entity. For example, a physical identifier may be associated with the physical entity of a product. A physical identifier may have a one-to-one correspondence with a virtual or physical identity through a physical association with a physical entity. A physical identifier may be physically attached to a product via an identifier element. A physical identifier or physical identifier element may refer to any virtual or physical configuration that associates a decentralized identifier with a product. A physical identifier may be any identifier of a manufactured product, such as a batch number or part number. A physical identifier element may include, but is not limited to, passive or active elements, such as a QR code® or an RFID tag. A physical identifier element may be a physical identifier physically associated with a product. An identifier element may include a marker embedded in a material, a barcode, a QR code, a tag such as an RFID tag, or a similar physical configuration that enables the digital identification of a product.

[0063] A data owner may include entities that generate data associated with a product, and / or a data owner is the data owner of the data associated with the product and / or the digital twin dataset. A data generation node may be connected to an entity that owns the physical entity of the product from which or for which data is generated. Data, in particular data associated with a product, may be generated by a third-party entity acting on behalf of the entity that owns the physical entity of the product from which or for which data is generated. A data owner may be a product producer. Therefore, a data owner may directly or indirectly own the data associated with a product. Data associated with a product may be stored in the data owner's database or a database associated with the data owner. Data associated with a product may be stored in a database of the data owner or under the data owner's control. Data associated with a product may be stored in a database accessible to the data owner. A data owner may control access to data associated with a product, for example, through a decentralized data delivery network node associated with the data owner. Data associated with a product may be associated with the data owner. A data owner may be the owner of the data associated with the product or the product data owner. In this sense, the data owner should be broadly interpreted as an entity that can access data associated with a product and controls access to the digital twin or a portion thereof generated using the aforementioned data associated with the product by decentralized data consumption network nodes of a decentralized network.

[0064] A digital twin dataset may correspond to the data structure obtained when applying each aspect model to the collected data associated with the physical entity of a product. A digital twin dataset may include values ​​and / or value ranges defined in the aspect model used to generate the digital twin dataset. A digital twin dataset may be a dataset suitable for representing at least a portion of the collected data. A digital twin dataset may represent at least a portion of the collected data. A digital twin dataset may include a subset of the collected data. A digital twin dataset may refer to a selection of data points within the collected data. Thus, each digital twin dataset includes the data structure and data defined by the aspect model used to generate it. This ensures that each digital twin dataset has a defined structure and includes defined data, thus simplifying data exchange and the processing of exchanged data regarding products. Each aspect model may be defined in the generated digital twin template. Therefore, digital twin datasets included in a digital twin can be generated by applying the aspect model defined in each digital twin template to the collected data. A digital twin dataset may include a digital twin dataset identifier. A digital twin dataset may include a product identifier. This makes it possible to associate digital twin datasets with specific products. Digital twin datasets can be assigned to decentralized digital twin identifiers. Digital twin datasets can be linked to decentralized digital twin identifiers. By using a combination of decentralized digital twin identifiers and digital twin dataset identifiers, it becomes possible to retrieve each digital twin dataset (e.g., a portion of the generated digital twin), thus avoiding the retrieval of the entire digital twin when access to only a specific digital twin dataset of the digital twin is requested.Furthermore, this allows for more granular control over access to the digital twin, as access can be controlled at the dataset level.

[0065] A digital twin may include at least one measured physical and / or chemical property of a product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product. A digital twin may include at least two different measured and / or determined physical and / or chemical properties that exist in different digital twin datasets. Data points in different datasets may overlap. Data associated with the production of a product may be collected before, during, and / or after the production of the product. The collected product data may be used to determine at least one physical and / or chemical property of the produced product. For example, product emission data may be determined based on product data collected during the production of the product. Data associated with the production of a product may include production data from the production of the product. Data associated with the production of a product may include monitoring and / or control data associated with the production of the product. Data associated with the use of a product may be collected via at least one identifier associated with the product. The data may be collected before, during, or after the use of the product. The collected data may include at least one measured physical and / or chemical property of the used product. The measured physical and / or chemical properties may include the chemical and / or physical properties described above. Data may be collected using appropriate sensors configured to measure chemical and / or physical properties. Sensor data may be correlated with identifiers associated with the product. Chemical and / or physical properties determined from sensor data may be correlated with identifiers associated with the product. Identifiers may include product identifiers. Identifiers may include decentralized digital twin identifiers.

[0066] A digital twin can be generated by a decentralized network node of a decentralized network. A decentralized node can communicate with a decentralized data-providing network node that provides access to the digital twin. A decentralized node can be associated with a decentralized data-providing network node that provides access to the digital twin. A digital twin can be generated by the data owner of the data associated with a product. The data owner of the data associated with a product may be the production that produces the product. The data owner of the data associated with a product may be the legal entity that operates the production that produces the product. The data owner of the data associated with a product may be the natural person that operates the production that produces the product. A digital twin can be generated on behalf of the data owner of the data associated with a product. For example, a digital twin can be generated by a third party based on services provided to the data owner by the third party.

[0067] A digital twin can be generated by providing a digital twin template and applying the aspect model defined in the digital twin template to the collected data associated with the product. A digital twin template can be provided by determining the appropriate digital twin template based on the data associated with the product from which the digital twin should be generated. For example, the product class associated with the product from which the digital twin should be generated can be used to determine the respective digital twin template. The data associated with the product can be collected from one or more data sources based on the data relevant to the product. These one or more data sources may be the distributed data sources described above. The data associated with the product may include one or more product identifiers associated with the product. These one or more product identifiers may include a batch number, product name, product ID, part number, lot number, or a combination thereof. The product identifiers enable the unique identification of the physical entity of each product, and therefore link all data associated with the above identifiers to the physical entity of the product. The data associated with chemical products includes chemical product data. Product-related data may include data relating to product use, data relating to product production, one or more product identifiers, product name, product composition, measured and / or determined chemical and / or physical properties of the product, product emission data, product recyclable content data, product bio-based content data, product renewable material content data, product declaration data, product safety data, certificates of analytical data associated with the product, certificates associated with the product, or a combination thereof.

[0068] The generated digital twin can be stored in data storage. This data storage may be a database associated with the data owner. The data storage can function as an intermediate layer between data collection and digital twin consumption by, for example, decentralized data consumption network nodes. This separation of data collection and consumption between the generated digital twin or associated digital twin dataset can result in high and stable availability of the digital twin dataset within a decentralized network.

[0069] The generated digital twin or a portion thereof (e.g., the digital twin dataset contained within the digital twin) may be provided to a decentralized data-providing network node for access by a decentralized data-consuming network node. A decentralized data-consuming network node may be controlled or owned by, or associated with, a consumer of a product. The consumer may be any entity that processes the product. The consumer may be any entity that operates the production comprised of a chemical product. A decentralized data-consuming network node may be controlled or owned by, or associated with, any upstream stakeholders in the product ecosystem, including product consumers, end-product manufacturers, and stakeholders in the recycling chain associated with the product. Access to the digital twin or a portion thereof may be controlled by a decentralized data-providing network node. A decentralized data-providing network node may be associated with the data owner of the digital twin dataset. A decentralized data-providing network node may be associated with the data owner of the digital twin. Therefore, access to the digital twin or a portion thereof may be under the control of the data owner associated with the decentralized data-providing network node. This allows the data owner to maintain complete control over the digital twin, while at the same time enabling the sharing of the digital twin or a portion thereof under controlled conditions, for example, by using appropriate authentication and authorization mechanisms or schemes.

[0070] A digital twin generated using a digital twin template produced by an apparatus or method disclosed herein may be associated with a digital access element. The digital access element may include a decentralized access element identifier and access data associated with the digital twin. The digital access element may be used to access the associated digital twin or a portion thereof.

[0071] A digital access element may represent a DID document associated with a decentralized identifier, such as a DID. A DID document may be generated at the time of DID generation. Alternatively, a DID document may be generated after DID generation, for example, when a digital twin is generated. A DID document may include the DID, further identifiers associated with the DID, such as a digital twin dataset identifier, and access data. Access data may refer to any data used to access a digital twin or a portion thereof, such as a digital twin dataset contained within the digital twin.

[0072] A decentralized access element identifier may include one or more universally unique identifiers (UUIDs) or digital identifiers (DIDs). One or more DIDs and / or UUIDs may be associated with the digital twin described above.

[0073] Access data may include a digital representation that points to at least one of the digital twin datasets associated with the digital twin. Access data may further include a digital twin dataset identifier associated with the digital twin datasets contained in the digital twin. A digital twin dataset identifier may be one or more universally unique identifiers (UUIDs) or one or more decentralized identifiers (DIDs). A digital twin dataset identifier may be requested from an ID generator before providing the generated digital twin to a decentralized data delivery network node. A digital twin dataset identifier may be obtained from the digital twin. A digital twin dataset identifier may be obtained from a digital access element, such as a DID document generated at the time of digital twin generation, as described below. The digital representation may be indirectly associated with a database that stores the digital twin datasets and is associated with or accessible by the data owner associated with the digital twin datasets. This may enhance security. A digital representation that points to at least one digital twin dataset may include an endpoint for data exchange or sharing (resource endpoint) or an endpoint for service interaction (service endpoint), which is uniquely identified via a communication protocol as described above. Therefore, a digital representation pointing to at least one digital twin dataset can be uniquely associated with a decentralized identifier. A digital representation pointing to at least one digital twin dataset can be considered a locator indicating the location or dedicated data storage where each digital twin dataset is stored. Access data may include authorization schemes and / or cryptographic information. For example, access data may include public keys, such as the public key required to decrypt a digital twin dataset. Access data may include authentication schemes associated with decentralized identifiers. Access data can be uniquely associated with decentralized digital twin identifiers. Access data can be provided to decentralized data consumption network nodes.Access data may be provided by a decentralized network database, a database associated with a decentralized data consumption network node, a decentralized data provision network node associated with the data owner, or a combination thereof. Using access data within a digital access element allows data owners to maintain control over the digital twin because appropriate authorization and authentication are required to access the data contained in the digital twin. This makes it possible to openly share the contents of a digital access element, for example, on a public web platform, without having to disclose the digital twin or any part thereof associated with the digital access element via a decentralized digital twin. Therefore, transparency regarding existing digital access elements can be provided while ensuring the necessary level of confidentiality of the data contained in the digital twin associated with the digital access element.

[0074] A brief explanation of some of the figures in the drawing. The present disclosure will be further described below with reference to the attached drawings. The same reference numerals in the drawings and in this disclosure are intended to refer to the same or similar elements, components, and / or parts. [Brief explanation of the drawing]

[0075] [Figure 1A] This example shows production controlled by an operating system, including a digital twin management system. [Figure 1B] This example shows production controlled by an operating system to deliver products associated with a digital twin. [Figure 1C] This presents another example of production controlled by an operating system to deliver products associated with a digital twin. [Figure 2] This example shows a production system that provides products associated with one or more digital twins. [Figure 3A]An example of a digital twin master template associated with a class of chemical products, according to exemplary embodiments of this disclosure, is shown. [Figure 3B] An example of a sub-aspect model included in the compositional aspect model of Figure 3A, according to an exemplary embodiment of the present disclosure, is shown. [Figure 3C] A first example of a sub-aspect model included in the compliance aspect model of Figure 3A, according to an exemplary embodiment of the present disclosure, is shown. [Figure 3D] Further examples of sub-aspect models included in the compliance aspect model of Figure 3A, according to exemplary embodiments of this disclosure, are shown. [Figure 3E] Further examples of sub-aspect models included in the compliance aspect model of Figure 3A, according to exemplary embodiments of this disclosure, are shown. [Figure 4A] An example of a digital twin template associated with a product, generated by selecting an aspect model included in a digital twin master template according to an exemplary embodiment of the present disclosure, is shown. [Figure 4B] An example of a digital twin template associated with a product generated by selecting aspect models included in a digital twin master template and further aspect models included in a model database, according to an exemplary embodiment of the present disclosure, is shown. [Figure 5] This disclosure illustrates an apparatus for generating a digital twin template associated with a product, according to an exemplary embodiment of this disclosure. [Figure 6A] A flowchart of a computer-aided method for generating a digital twin associated with a product or product class, according to exemplary embodiments of this disclosure, is shown. [Figure 6B] A flowchart of a computer-aided method for generating a digital twin associated with a product or product class, according to exemplary embodiments of this disclosure, is shown. [Figure 7A]This disclosure illustrates an apparatus for generating a digital twin of a product's physical entity using a digital twin template, according to an exemplary embodiment of this disclosure. [Figure 7B] An exemplary embodiment of this disclosure illustrates a hierarchical system for generating a digital twin of a product's physical entity using a digital twin template. [Figure 8] This document presents exemplary systems and related methods for generating digital twins associated with products produced by chemical manufacturing and for providing access to the generated digital twins. [Figure 9] This example demonstrates how to generate a digital twin of a product's physical entities using a digital twin template that defines three models. [Figure 10] A flowchart of a computer-aided method for generating a digital twin of a physical entity of a product, according to exemplary embodiments of this disclosure, is shown. [Figure 11] This is a flowchart of a computer implementation method for generating digital access elements associated with a digital twin of a product, according to exemplary embodiments of the present disclosure. [Figure 12] This document presents an example of a system for providing digital access elements associated with products produced and supplied by a production process that includes an exemplary method for generating a digital twin. [Figure 13] This shows an example of digital access elements, including DID owner data, DID document data, and a decentralized identity infrastructure. [Figure 14A] This shows the first example of a link between a digital twin, its associated digital twin dataset, and a digital access element via a decentralized digital twin identifier. [Figure 14B] This presents a second example of a link between a digital twin, its associated digital twin dataset, and a digital access element via a decentralized digital twin identifier. [Figure 15]This diagram illustrates how decentralized data consumption network nodes associated with data users can be used to provide access to a digital twin or a portion thereof associated with a product, via decentralized data delivery network nodes associated with data owners. [Modes for carrying out the invention]

[0076] Detailed explanation The following embodiments are merely examples of, and should not be considered as limiting, to the methods, systems, or application devices disclosed herein.

[0077] Figure 1A shows an example of a production 104 that produces one or more products from one or more input materials 102, in relation to an operating system 108 including a digital twin management system. The operating system 108 may be used to operate production 104, for example, by managing different production chains that exist within production 104. Different materials 102 (hereinafter also referred to as input materials 102) may be provided as physical inputs from material providers or suppliers in order to produce one or more shipped products 106. Physical inputs to production 104 may include chemical substances such as raw materials, intermediate materials, chemical products, parts, assemblies, or combinations thereof. Raw materials may be raw materials or recycled raw materials. Input materials 102 may be supplied to production 104 at any entry point. Input materials 102 may be supplied to production 104 at the start of production 104. Input materials may be considered inputs to production 104.

[0078] Production 104 may be chemical production. Chemical production may be a chemical production network that includes multiple interconnected processing steps. A chemical production network may be an integrated chemical production network having interconnected production chains. A chemical production network may include multiple different production chains that share at least one intermediate product. A chemical production network may include multiple stages of a chemical value chain. A chemical production network may include multiple production chains that produce a chemical product as output from one or more input materials as inputs. A chemical production network may include multiple tiers of a chemical value chain. A chemical production network may include an arrangement of physically interconnected production sites. Production sites may be in the same location or in different locations. In the latter case, production sites may be interconnected by dedicated transport systems such as pipelines, supply chain vehicles such as trucks, supply chain ships, or other means of freight transport.

[0079] Production 104 may include multiple production processes. The production processes included in Production 104 may be defined by the system boundary of Production 104. The system boundary may be defined by locations or controls across the production processes. The system boundary may be defined by the locations of Production 104. The system boundary may be defined by production processes jointly controlled by one or more entities. The system boundary may be defined by a value chain with time-delayed production processes to the final product, and these processes may be independently controlled by multiple entities.

[0080] Production 104 can convert input materials 102 into at least one output product 106 coming out of production 104. The conversion can be carried out by assembling the input materials 102, such as components or parts. The conversion may be a chemical reaction or any other processing step, such as a physical treatment. The conversion may be carried out via intermediate chemical products. Since the yield of a chemical reaction may be less than 100%, the chemical reaction may result in a mixture of different chemical products. Thus, a chemical reaction of one or more starting materials, such as input materials 202, may result in a mixture of different chemical products. Thus, a chemical reaction may be characterized by a one-to-many or many-to-many relationship between the starting materials and the resulting reaction products. This is in contrast to discrete manufacturing, where a many-to-one relationship exists between parts / components and assemblies, for example, the result of a discrete manufacturing process is a specific and predictable assembly. Since the yield of a chemical reaction is not 100%, the amount of the desired chemical product 106 (e.g., a chemical product supplied to an upstream participant in the chemical ecosystem) is less than the theoretical amount of the above chemical product calculated from the amount of the starting materials. Such mixtures typically require the separation of different chemical products contained within the mixture. This makes it possible to avoid the adverse effects of impurities and unreacted input materials 102 on further processing of the chemical product 106. Separation may include distillation, washing, extraction, crystallization, and recrystallization. The resulting mixture may contain unreacted starting materials, such as unreacted input materials 102. The unreacted starting materials may be reintroduced into the chemical reaction to reduce the amount of starting materials required. The resulting mixture may contain the desired chemical product 106 supplied to upstream participants in the chemical ecosystem, such as chemical product consumers or chemical product processors. The resulting mixture may contain intermediate chemical products used as input materials in further chemical reactions carried out within the chemical production. This makes it possible to reduce the amount of waste associated with the disposal of the intermediate chemical products and / or the amount of energy associated with transporting these intermediate products to other chemical productions. The resulting mixture may contain waste chemical products, such as chemical products that can no longer be used and need to be disposed of, for example, by incineration.Waste chemical products can be produced from undesirable chemical side reactions.

[0081] Production 104 may be equipped with a plurality of sensors 110a, 110b. Sensors 110a, 110b may measure at least one chemical and / or physical property of the shipped product 106 produced by production 104. Sensors 110a, 110b may measure at least one chemical and / or physical property of the input material 102 supplied to production 104. Sensors 110a, 110b may include sensor 110b configured to determine the quantity of input material 102 and / or shipped product 106. Examples of such sensors include measuring instruments or flow meters. Sensors 110a, 110b may include sensor 110a configured to measure at least one chemical and / or physical property of input material 102. Measuring the chemical and / or physical properties of input material 102 makes it possible to control the production process based on the measurement data. Sensors 110a and 110b may include sensor 110a configured to determine the chemical and / or physical properties of the produced shipment product 106. Sensor 110a configured to measure chemical properties may measure data associated with or corresponding to combustion heat, formation enthalpy, toxicity, chemical stability in a given environment, flammability, oxidation state, corrosiveness, flammability, acidity and basicity, and pH value. Sensor 110a configured to measure physical properties may measure data associated with or corresponding to absorption, brittleness, boiling point, capacitance, color, concentration, density, ductility, distribution, effectiveness, elasticity, charge, conductivity, electrical impedance, potential, flow rate, fluidity, hardness, heat capacity, inductance, intrinsic impedance, brightness, luminescence, gloss, mass, melting point, opacity, transmittance, dielectric constant, plasticity, pressure, radiance, resistivity, reflectance, refractive index, solubility, specific heat, strength, stiffness, temperature, tension, thermal conductivity, thermal resistance, viscosity, volume, and wave impedance. The data measured by sensors 110a and 110b may be stored in one or more databases, for example, a database included in the data source layer 704 in Figure 7A. These databases may be distributed databases. The stored data may be associated with input material identifiers and / or product identifiers.

[0082] The chemical production operating system 108 may monitor and / or control production 104 based on operating parameters associated with different processes performed by production 104. One process step to be monitored and / or controlled may be the supply of input materials 102 or the shipment of the produced product 106. Another process step to be monitored and / or controlled may be the separation of chemical products contained in a mixture resulting from chemical reactions performed within production 104, which is a chemical production. Another process step to be monitored and / or controlled may be the determination of the chemical and / or physical properties of the produced product 106 from collected data associated with the production of the chemical product, such as data measured by sensors 110a, 110b before, during, and / or after the production of the product 106. Another process step to be monitored and / or controlled may be the generation of a digital twin template, as described in relation to, for example, Figures 4A to 6A. Yet another process step to be monitored and / or controlled may be the generation of a digital twin, as described in relation to, for example, Figures 7A to 10. Further monitored and / or controlled process steps may include access to the generated digital twin by decentralized data consumption network nodes, as described, for example, in relation to Figure 8. Further monitored and / or controlled process steps may include the provision of products associated with the digital twin, as described, for example, in relation to Figures 8 and 15. Further monitored and / or controlled process steps may include the generation of digital access elements associated with the digital twin of the produced chemical product, as described, for example, in relation to Figures 11 and 12.

[0083] The operating system 108 may be configured to determine the physical and / or chemical properties of a chemical product from collected data associated with the production of that chemical product. The operating system 108 may be configured to generate a digital twin template, for example, as described in relation to Figures 4A to 6A. The operating system 108 may be configured to update a digital twin master template, for example, as described in Figure 6B. The operating system 108 may be configured to generate a digital twin of a chemical product, for example, as described in relation to Figures 7A to 10. The operating system 108 may be configured to generate digital access elements, for example, as described in relation to Figures 11 and 12. The operating system 108 may be configured to control access to the generated digital twin by decentralized data consumption network nodes, for example, as described in relation to Figures 8 and 15.

[0084] Figure 1B shows another example of production 104 controlled by the operating system 108 to provide products associated with a digital twin. Products may be further associated with digital access elements. Production 104 may be a chemical production that produces a chemical product 106 from at least one input material 102, as described in relation to Figure 1A.

[0085] The process steps described in relation to Figure 1A may be performed in interaction with a requester, an ID assigner, a device 112 for generating a digital twin template, and a device for generating a digital twin via the operating system 108 of production 104. The operating system 108 may further interact with a device for generating digital access elements (not shown). In this embodiment, the operating system 108 may be communicably connected to production 104 and may include a requester, an ID assigner, a device for generating a digital twin template, and a device 112 for generating a digital twin.

[0086] The apparatus for generating the DT template may be the apparatus 500 described in relation to Figure 5. The apparatus for generating the digital twin may be the apparatus described in relation to Figure 7A, or the system described in relation to Figure 7B.

[0087] A requester may be configured to generate a request for generating a digital twin template. The request may include product-related data such as a product identifier and / or product class. The product identifier may include a batch number, lot number, and / or product ID. The request may be received by a digital twin template generator 504 (see, for example, Figure 5), which may generate a digital twin template in response to the request using, for example, the method described in relation to Figure 6A. The digital twin generator 504 may be further configured to update a digital twin master template, as described in relation to Figure 6B.

[0088] The requester may be configured to generate requests for generating a digital twin template. The requests may include data related to the chemical product, such as batch number, lot number, and / or chemical product ID, and data related to at least one aspect model associated with the chemical product, as described above. The requests may be received by the data collection unit 712 (see Figure 7A), which may, upon request, initiate the generation of a digital twin, as described in relation to Figures 7A and 10. The requests may also be received by the digital twin generator 716 (see Figure 7A), which may, upon request, initiate the generation of a digital twin, as described in relation to Figures 7A and 10. The requester may be further configured to generate requests for generating digital access elements. The requests may include, as described above, owner identifiers and / or product identifiers and / or access data.

[0089] A requester may be configured to generate a request for the generation of a digital access element. The request may be received by a device for generating the digital access element (see, for example, Figure 12). The device for generating the digital access element may be configured to generate the digital access element using the method described in relation to Figure 11. An example of such a digital access element generated by the device is shown in Figure 13.

[0090] The ID assigner may be configured to assign decentralized digital twin identifiers and / or decentralized access element identifiers associated with the digital twin, as well as related information, to the physical identifiers of the produced products, as illustrated in relation to Figure 2. For example, the ID assigner may generate physical identifiers embedded with decentralized digital twin identifiers and / or digital access element identifiers, and provide these physical identifiers to a labeling device.

[0091] The ID assigner, requester, device for generating digital twin templates, device for generating digital twins, and / or device for generating digital access elements may be configured as a decentralized service or application executed over a decentralized network. The decentralized network may be a decentralized peer-to-peer communication network. The decentralized network may include participant network nodes associated with participants in the product ecosystem and may be configured to perform data transactions, for example, as described in relation to Figure 15.

[0092] Figure 1C shows yet another example of production 104 controlled by operating system 108 to provide products associated with a digital twin. Products may be further associated with digital access elements. Production 104 could be a chemical production producing a chemical product 106 from at least one input material 102, as described in relation to Figure 1A.

[0093] The process steps described in relation to Figure 1C may be performed in interaction with a requester, an ID assigner, an apparatus for generating a DT template, and an apparatus for generating a digital twin of a chemical product via the operating system 108 of production 104. The operating system 108 may further interact with an apparatus for generating a digital access element (not shown). In this embodiment, the operating system 108 may be communicatively connected to production 104 and may include a requester and an ID assigner 114. The operating system 108 may be communicatively connected to the apparatus 116 for generating a DT template. The operating system 108 may be communicatively connected to the apparatus 118 for generating a digital twin.

[0094] The apparatus 116 for generating the DT template may correspond to the apparatus 500 described in relation to Figure 5. The apparatus 118 for generating the digital twin may correspond to the apparatus described in relation to Figure 7A, or the system described in relation to Figure 7B.

[0095] The requester may be configured to generate a request to generate a digital twin template, as described in relation to Figure 1B. The requester may be configured to generate a request to generate a digital twin, as described in relation to Figure 1C. The requester may be configured to generate a request to generate a digital access element, for example, as described in relation to Figure 1C.

[0096] The ID assigner may be configured to assign decentralized digital twin identifiers and / or decentralized access element identifiers and related information to the physical identifiers of the produced products, as described in relation to Figures 1C and 2. The requester, ID assigner, apparatus for generating DT templates, apparatus for generating digital twins of chemical products, and / or apparatus for generating digital access elements may be configured as decentralized services or applications that run over a decentralized network, as described in relation to Figure 1B.

[0097] Figures 1B and 1C show only two exemplary embodiments, and any combination of the system components shown in Figures 1B and 1C is possible. For example, the requester may be configured as part of the operating system 108, while the ID assigner may not be configured as part of the operating system 108.

[0098] Figure 2 shows an example of a production system that provides products associated with a digital twin. Specifically, Figure 2 shows an example for generating a digital twin of a precursor material (e.g., an intermediate chemical product) and for generating a digital twin of a chemical product at least partially produced from the precursor material. Chemical products such as the shipped product 106 may be produced by chemical production, such as production 104 including an operating system 108, as described in relation to Figures 1A to 1C, for example.

[0099] The production of a chemical product may involve a two-stage process, namely, 1) the production of an intermediate chemical product from one or more input materials, and 2) the production of a chemical product from at least part of the intermediate chemical product. Input materials, such as input material 102, may be used as physical inputs to produce the intermediate chemical product. Input materials may be provided by a raw material provider. Input materials may include raw materials or recycled materials. Input materials may be provided for the production of the intermediate chemical product as input material 102. The production of the intermediate chemical product may be a chemical production as described with respect to Figures 1A to 1C. The input materials may have a physical identifier. The physical identifier may be a decentralized input material identifier, or may be associated therewith. The decentralized input material identifier may be associated with a digital twin of the input material. The operating system for the production of the intermediate chemical product, such as the operating system 108 as described with respect to Figures 1A to 1C, may include, or may communicate with, an ID reader configured to read the physical identifier and determine the decentralized input material identifier associated with the physical identifier. A decentralized input material identifier may be associated with a digital twin or a portion thereof of each input material. The digital twin of an input material may be generated using a digital twin template, as described later in relation to Figures 7A–10. The digital twin template may be generated as described in relation to Figures 4A–6A. The digital twin may include measured physical and / or chemical properties, as well as physical and / or chemical properties determined from collected data associated with the production and / or use of the input material. Physical and / or chemical properties may be measured using sensors, as described in relation to Figures 1A–1C. Physical and / or chemical properties may be determined from collected data, as described in relation to Figures 1A–1C. The digital twin may further include the input material name, input material producer, input material declaration data, input material safety data, emission data, recyclable content data, bio-based content data, certificates of analytical data associated with the input material, certificates associated with the input material, or a combination thereof.

[0100] The operating system may be configured to access a digital twin or a portion thereof of the input materials provided to the intermediate chemical production, based on a determined decentralized input material identifier, from a decentralized data provision network node associated with the input material provider (see, for example, Figure 15). Such data may be used to operate the chemical production that produces the intermediate chemical. For example, if the input material is recycled material, a production process to purify the recycled material may be performed. For example, if the input material is raw material, the purification process may be omitted. Intermediate chemicals may be formed by chemically reacting and / or physically processing the input materials. Chemical reactions may include polymerization, precipitation, and other commonly known chemical reactions. Physical processing may include mixing, grinding, extrusion, etc. Intermediate chemical production may include sensors such as sensors 110a, 110b that measure the physical and / or chemical properties of the intermediate chemical produced by the intermediate chemical production, as described with respect to Figures 1A to 1C. The operating system may be configured to determine the physical and / or chemical properties from collected data associated with the production of intermediate chemical products, as described, for example, with respect to Figures 1A to 1C.

[0101] The operating system may be configured to generate digital twins of the produced intermediate chemical products, as will be described later with reference to Figures 4A to 10. Each digital twin may include a decentralized intermediate chemical product identifier and at least one chemical and / or physical property of each intermediate chemical product measured by sensors 110a, 110b, and / or at least one physical and / or chemical property of each intermediate chemical product determined from the collected data. The digital twin may further include a decentralized input material identifier for the input materials used to produce each intermediate chemical product. This makes it possible to track the input materials used to produce each intermediate chemical product. The digital twin may further include the data described above in relation to the digital twin of the input materials. The intermediate chemical product digital access element may be generated, for example, as described with reference to Figures 11 and 12. The produced intermediate chemical products may be packaged, and the packaging may include a physical identifier such as a QR code, an embossed code, or an optical holographic code such as a zero-order diffraction microstructure. Physical identifiers can be assigned to each decentralized intermediate chemical product identifier in the digital twin and / or to each decentralized passport identifier of the intermediate chemical product digital access element. The assignment of physical identifier elements and decentralized intermediate chemical product identifiers can be performed through a locally operating ID assigner in a decentralized and / or distributed system. For example, a packaging line may include a labeling device that detects the packaging of the produced intermediate chemical product. Based on such recognition, a requester may generate a request to generate a digital twin, and each decentralized intermediate chemical product identifier included in the generated digital twin can be assigned to its respective physical identifier by, for example, an ID assigner (see also Figure 8 below). Assignment may include encoding each decentralized intermediate chemical product identifier into a physical identifier and providing the physical identifier, such as a code, to a labeling device configured to attach the physical identifier to each intermediate chemical product, such as the packaging of each intermediate chemical product.The ID assigner may be part of the labeling device or it may be a separate device.

[0102] In the second step, the intermediate chemical product produced in step 1) may be provided as input material 102 to a chemical production to produce a chemical product 106. The chemical production may be production 104 as described in relation to Figures 1A to 1C. The chemical production may be a chemical production that produces an intermediate chemical product. The chemical production may be different from a chemical production that produces an intermediate chemical product. In addition to the intermediate chemical product produced in step 1), further input materials may be provided to the chemical production and used to produce a chemical product 106. The intermediate chemical product may include recycled intermediate chemical products and / or intermediate chemical products produced by an intermediate chemical production different from the intermediate chemical production described with respect to step 1). Such intermediate chemical products may be associated with a physical identifier. The physical identifier may be associated with a decentralized intermediate chemical product identifier, and a digital twin or part thereof of each intermediate chemical product may be accessible through the decentralized intermediate chemical product identifier. An ID reader may be used to read the physical identifier associated with each decentralized intermediate chemical product identifier as described above. A digital twin, or a portion thereof, can be obtained via a decentralized data consumption network node using a decentralized intermediate chemical product identifier, as described above.

[0103] Production data from the production of intermediate chemical products may be used by an operating system, such as the operating system 108 described in relation to Figures 1A to 1C, for the chemical production that produces the chemical product 106, as described above. The chemical production may include sensors, such as sensors 110a, 110b, that measure the physical and / or chemical properties of the chemical product produced by the chemical production, as described in relation to Figures 1A to 1C. The operating system may be configured to determine the physical and / or chemical properties from the collected data associated with the production of the chemical product, for example, as described in relation to Figures 1A to 1C.

[0104] The operating system may be configured to generate a digital twin of a produced or packaged chemical product, as described above. The digital twin may include a decentralized chemical product identifier and at least one measured and / or determined physical and / or chemical property, as outlined above. The digital twin may also include a decentralized intermediate chemical product identifier. This makes it possible to track the intermediate chemicals used to produce the chemical product, and also to indirectly track the input materials used to produce the intermediate chemicals. The digital twin may include further data such as producer name, producer brand, producer identifier, chemical product name, chemical product brand, and chemical product identifier, as outlined above.

[0105] Digital access elements associated with chemical products can be generated, for example, as described in relation to Figures 11 and 12. Decentralized chemical product identifiers and / or digital access elements can be associated with chemical products via physical identifiers, as described above. Digital access elements may include decentralized access element identifiers and access data. Access data may include digital representations pointing to a digital twin or a portion thereof. Decentralized access element identifiers may correspond to or be associated with decentralized chemical product identifiers.

[0106] Figure 3A shows an example of a digital twin master template associated with a chemical product according to an exemplary embodiment of the present disclosure. While Figure 3A shows an example of a digital twin master template for a chemical product, it should not be construed as limiting, but rather serves only as an example. For example, a digital twin master template may be associated with products produced from such a chemical product, such as components or parts.

[0107] A digital twin master template may define multiple aspect models. An aspect model may define (i) data structures of at least part of the digital twin, such as a digital twin dataset, resulting from the application of the aspect model to product data associated with the physical entities of a product or product class, and (iii) one or more data points contained in such part of the digital twin. A data point may define the physical and / or chemical properties of a product or product class. A data point may define data associated with the production of a product. A data point may define data associated with the use of a product and / or the disposal or recycling of a product. Multiple aspect models defined in a digital twin master template may include aspect models usable for any product or product class. For example, aspect models that may be usable for any product or product class include an aspect model for template data (template metadata 306), an aspect model for DT data generated from the master template (DT metadata 308), and an aspect model for product producers (producer DM 310). The aspect model template metadata 306 may include the following attributes: identifier, version, creation data and time, issuer, and comments on the template.Aspect model DT metadata 308 may include the following attributes: identifier, version, last modified date, data carrier ID number (e.g., ID of an auto-identifiable data ingestion medium that can be read by a device), data carrier type (e.g., data carrier according to ISO / EC15459:2015), expiration date, layout (e.g., the layout and location of the data carrier as it is presented, corresponding to the product type (e.g., a product type such as a batch to which the digital twin corresponds)), read accessibility data for actors (e.g., stakeholders in a decentralized network who can access the data in the digital twin, and the data that stakeholders can access), update accessibility data for actors (e.g., stakeholders in a decentralized network who can update the data in the digital twin), accessibility data manners (e.g., manners that make the digital twin accessible to other stakeholders in a decentralized network), and the author and unique ID of the digital twin creator (e.g., the business partner number of the digital twin issuer). Aspect model producer DM310 may be linked to a child aspect model (not shown) that defines the producer's postal address and may include the following attributes: name, unique ID, supplier code, registered trademark name, registered trademark, postal address, email address, telephone number, web address, and EORI number.

[0108] The multiple aspect models defined in the digital twin master template may include aspect models specific to a product or product class. For example, aspect models for product identification (Identification DM312), product parameters (Parameters DM314), product safety data (Safety Data DM316), product composition (Composition DM318), sustainability profile including emission data (Sustainability DM320), product waste management (Waste Management DM322), product history (Product History DM324), product delivery (Delivery DM326), product packaging (Packaging DM328), and compliance data (Compliance DM330) may be specific to a chemical product or a particular class of chemical products. The aspect model parameter DM314 may include the following attributes: net weight, physical state, color, odor, pH, melting point, freezing point, softening point, boiling point or initial boiling point and boiling point range, flash point, flammability, lower explosive limit, upper explosive limit, autoignition temperature, vapor pressure, decomposition temperature, kinematic viscosity, solubility, n-octanol / water partition coefficient, relative density or density, relative vapor density, particle properties, flow time, other information (e.g., conductivity, burning rate), post-use parameters (e.g., hardness, gloss, scratch resistance, opacity, metamerism), and dynamic parameters (e.g., product parameters obtained by sensors such as temperature). The aspect model parameter DM314 may define one or more sub-aspect models (not shown). An example of such a sub-aspect model is a test aspect model. A test aspect model may define data on the test methods used to determine the parameters defined in parameter DM314. Such data may include data on the test methods used to determine each parameter. Data regarding test methods may include the name of the test method, units of parameters, a brief description of the test performed, test conditions, comments on the test method, test method results, execution summary of the test results, test method ID number, GLP compliance of the test method, or a combination thereof.

[0109] Compliance DM330 may define one or more sub-aspect models, such as those shown later in Figures 3C and 3E. In addition to the sub-aspect models shown in Figures 3C and 3E, further sub-aspect models relating to the certificate of analytical data may be defined. Such sub-aspect models may define a link to the certificate of analytical data or a structured certificate of analytical data, or may be associated with an open-source data structure for digital CoA. An aspect model defining a structured certificate of analytical data may include the following attributes: issuer, version, language, notes (e.g., sample description), customer (e.g., the party ordering the CoA), batch number, production data, shelf life and analysis list (e.g., list of tests performed on the sample), list of standards / certificates to which the laboratory performing the test conforms, remarks, or a combination thereof. An aspect model defining structured CoA data may define a test method aspect model. A test method aspect model may define a test method used to determine product parameters included in a CoA, and may include the following attributes: test method (e.g., name of test method), ID of test method, units of obtained values, brief description of test method, conclusion of test method, summary of test execution, GLP compliance, or a combination thereof. An aspect model defining structured CoA data may define an aspect model that defines upper and / or lower thresholds. An aspect model associated with an open-source data structure for digital CoA may use an open-source JSON data structure. The open-source JSON data structure may be available from www.materialidentity.org. An aspect model defining an open-source data structure may include the following attributes: format, format version (format version identifier), URL to format the definition file, and payload (JSON string in the open-source data structure).

[0110] A digital twin master template may include multiple aspect models and / or one or more digital representations that refer to multiple aspect models. A digital representation may include endpoints for data exchange or sharing (resource endpoints) or endpoints for service interaction (service endpoints) that are uniquely identified via a communication protocol. A digital representation can be considered a locator indicating the location where each aspect model is stored or dedicated data storage. Using digital representations within a digital twin master template minimizes the amount of data included in the template, enabling more efficient data transfer and maintenance of the digital twin master template.

[0111] A digital twin master template can define relationships between one or more aspect models from among the multiple aspect models defined in the master template. These relationships can define a tree structure of the multiple aspect models defined in the digital twin master template, for example, as shown in Figures 3B to 3E. The tree structure may include one or more levels that result in a hierarchical order of the aspect models defined in the digital twin master template. The relationship between an aspect model at a higher tree level and an aspect model at a subsequent lower tree level can be described as a parent-child relationship. For example, an aspect model at a higher tree level can be described as a parent aspect model, while an aspect model associated with that parent aspect model at a subsequent lower tree level can be described as a child aspect model. For example, aspect model 304 can be represented as a parent aspect model (or root aspect model / root node), and aspect models 306 to 330 can be represented as child aspect models of the parent aspect model 304.

[0112] Relationships can be defined by relational expressions that specify the parent aspect models associated with the child aspect models, and / or the child aspect models associated with each parent aspect model. Relational expressions can be associated with each parent aspect model. Relational expressions can be associated with each child aspect model. Relational expressions can specify the relationship type between each parent aspect model and the child aspect models associated with each parent aspect model. For example, a relational expression associated with root entity 304 (or root node) can specify the child aspect models 306-330 associated with the root entity, and the relationship type between the root entity and each child aspect model. The relationship type can specify whether each child aspect model can be a required or optional aspect model. Required aspect models can be defined by a 1:1 or 1:many relationship type. In the embodiment of the master template shown in Figure 3A, aspect models 306-318 and model DB418 322 are defined by a 1:1 relationship type with respect to the root aspect model 304 and therefore represent mandatory aspect models. Non-mandatory aspect models may be defined by a relationship type of 1:0 or more. In the embodiment of the master template shown in Figure 3A, aspect models 320, 324, 328, and 330 are defined by a 1:0 or 1:1 relationship type with respect to the root aspect model 304 and therefore represent non-mandatory aspect models.

[0113] The relationship type can specify the number of child aspect models associated with a parent aspect model. For example, a 1:1 relationship type might define that a root aspect model 304 has only one child aspect model, such as aspect model 306. In another example, a 1:many relationship type (see, for example, Figure 3B) can be used to define that two or more child aspect models can be associated with their respective parent aspect models.

[0114] By using the relationships between aspect models defined in the master template, and consequently the hierarchical structure of the aspect models, it becomes possible to generate digital twin templates in a flexible, modular manner. This is because aspect models that are not suitable for the specific product or product class for which the digital twin template should be generated do not need to be selected and are therefore not included in the digital twin template. This avoids the existence of empty data fields resulting from the use of aspect models that define data types and attributes that are not available or applicable to a particular product or product class.

[0115] Figure 3B shows an example of a sub-aspect model included in the composition aspect model 318 of Figure 3A, according to an exemplary embodiment of the present disclosure. The sub-aspect models of the composition aspect model 318 may be called child aspect models, and a child aspect model may define one or more sub-aspect models.

[0116] In this embodiment, the composition aspect model 318 may be a child aspect model of the root aspect model 304 and may have a 1:1 relationship with the root aspect model 304. Examples of attributes of the composition aspect model 318 are listed in Figure 3B. Each attribute may be associated with a defined data type, as shown in Figure 3B. The composition aspect model 318 may define sub-aspect models. In this embodiment, the composition aspect model 318 defines a composition component aspect model (composition component DM332). The composition component aspect model may have a 1:0 or 1:many relationship with the parent component aspect model 318. Therefore, the composition component aspect model 332 may represent an optional aspect model. Examples of attributes of the composition component aspect model 332 are listed in Figure 3B. Each attribute may be associated with a defined data type, as shown in Figure 3B.

[0117] This makes it possible to consider the various number of components present in different chemical compositions. Next, the compositional component aspect model 332 can be linked to the identification aspect model 312. The identification aspect model 312 may include the following attributes: a specific code model number, a unique ID, a trademark name, a trademark name code, an index number, a list number assigned by ECHA, an authorization number, a REACH number, a unique formulation identifier (UIF) number, a CAS number, an EC number, another name of the product in use (e.g., information about the nanoform), a TARIC code, a product code, an international trade identification number (e.g., one provided in ISO / IEC 15459-6), a classification code, an EC name (e.g., the name of the component in EC inventory), an IUPAC name, and a molecular formula. Next, the compositional component aspect model 332 can be linked to a nanoparticle property aspect model (not shown). Such an aspect model may define the properties of nanoparticles. The properties include chemical name, particle size distribution D10, D50, D90, degree of crystallinity, nanoparticle shape, nanoparticle aspect ratio, nanoparticle surface treatment, description of surface treatment process, nanoparticle specific surface area, nanoparticle zeta potential, nanoparticle bulk density, nanoparticle photocatalytic activity, nanoparticle radical formation potential, nanoparticle catalytic activity, nanoparticle porosity, nanoparticle dispersibility, nanoparticle magnetic properties, whether the nanoparticles meet WHO fiber standards, nanoparticle solubility, nanoparticle flammability and / or explosiveness data, or combinations thereof. The aspect model defining the properties can be linked to the test aspect model, as described in relation to Figure 3A.

[0118] Figure 3C shows a first example of a sub-aspect model included in the compliance aspect model 330 of Figure 3A, according to an exemplary embodiment of the present disclosure. Sub-aspect models of compliance aspect model 330 may be referred to as child aspect models.

[0119] In this embodiment, the compliance aspect model 330 may be a child aspect model of the root aspect model 304 and may have a 1:0 or 1:1 relationship with respect to the root aspect model 304. Therefore, the compliance aspect model 330 may be considered an optional aspect model. The compliance aspect model 330 may define sub-aspect models. In this embodiment, three different sub-aspect models 334, 336, and 338 are shown for technical information associated with the product. Defining different aspect models for technical information about the product makes it possible to select the appropriate aspect model when generating the digital twin template, thus ensuring that the available data for the manufactured product 106 can be appropriately mapped to each aspect model. This makes it possible to standardize the exchange of product data via the digital twin, as selecting the appropriate aspect model ensures that data for technical information related to the product is provided in a standardized manner. Therefore, this modular approach provides a flexible way to generate digital twin templates that define appropriate aspect models (e.g., aspect models that match the available data associated with the produced product 106), thus enabling the generation of digital twins of the produced product 106, including standardized datasets, and facilitating the standardized exchange of product data within the product ecosystem.

[0120] The technical information link aspect model 334 may have a 1:0 or 1:many relationship with the parent compliance aspect model 330. Therefore, the technical information link aspect model 334 may represent a non-essential aspect model. Examples of attributes of the technical information link aspect model 334 are listed in Figure 3C. Each attribute may be associated with a defined data type, as shown in Figure 3C. This aspect model 334 makes it possible to reference technical information associated with a product via URLs, such as publicly available URLs. By utilizing this aspect model, integration costs are reduced because the majority of the technical information is already published in PDF format and available via the internet.

[0121] The technical information binary aspect model 336 may have a 1:0 or 1:many relationship with the parent compliance aspect model 330. Therefore, the technical information binary aspect model 336 may represent non-essential aspect models. Examples of attributes of the technical information binary aspect model 336 are listed in Figure 3C. Each attribute may be associated with a defined data type, as shown in Figure 3C. Base64 encoded technical information may provide the aspect model 336. Binary files, such as PDF files, can be encoded with Base64, a binary-to-text encoding commonly used for data transfer within systems that support only text characters. Data recipients can decode the text information back into a binary file, such as a PDF file, which can then be viewed through a viewer, such as a PDF viewer.

[0122] Figure 3D shows an example of a sub-aspect model included in the safety data aspect model 316 of Figure 3A, according to an exemplary embodiment of the present disclosure. Sub-aspect models of safety data aspect model 316 may be referred to as child aspect models.

[0123] In this embodiment, the safety data aspect model 316 may be a child aspect model of the root aspect model 304 and may have a 1:1 relationship with the root aspect model 304. Therefore, the safety data aspect model 316 may be considered an essential aspect model. The safety data aspect model 316 may define sub-aspect models. In this embodiment, the safety data aspect model 316 defines four different aspect models 340, 342, 344, and 346 for safety data associated with a product. The safety data may include at least one measured physical and / or chemical property as described above in relation to Figures 1A to 1C. By defining different aspect models for safety data associated with a product, it becomes possible to select the appropriate aspect model when generating the digital twin template, thus ensuring that the available safety data for the produced product 106 can be appropriately mapped to each aspect model. This makes it possible to standardize the exchange of product data via digital twins, and thus provides a flexible way to generate digital twin templates that define appropriate aspect models (for example, an aspect model that matches the available data regarding product 106, as described in relation to Figure 3C).

[0124] The safety information link aspect model 340 may have a 1:0 or 1:many relationship with the parent safety data aspect model 316. Therefore, the safety information link aspect model 340 may represent a non-essential aspect model. Examples of attributes of the safety information link aspect model 340 are listed in Figure 3D. Each attribute may be associated with a defined data type, as shown in Figure 3D. This aspect model 340 makes it possible to reference safety data associated with a product via a URL, such as a publicly available URL. By utilizing this aspect model, integration costs are reduced because most safety data is already published in PDF format and available via the internet.

[0125] The security information binary aspect model 342 may have a 1:0 or 1:many relationship with the parent security data aspect model 316. Therefore, the security information binary aspect model 342 may represent a non-essential aspect model. Examples of attributes of the security information binary aspect model 342 are enumerated in Figure 3D. Each attribute may be associated with a defined data type, as shown in Figure 3D. Base64 encoded security data may provide the aspect model 336. Binary files, such as PDF files, can be encoded with Base64, a binary-to-text encoding commonly used for data transfer within systems that only support text characters. The data recipient can decode the text information back into a binary file, such as a PDF file, which can then be viewed through a viewer, such as a PDF viewer.

[0126] Figure 3E shows a further example of a sub-aspect model included in the compliance aspect model 330 of Figure 3A, according to an exemplary embodiment of the present disclosure. The sub-aspect models of the compliance aspect model 330 may be referred to as child aspect models.

[0127] In this embodiment, compliance aspect model 330 may be a child aspect model of root aspect model 304 and may have a 1:0 or 1:1 relationship with root aspect model 304, as described in relation to Figure 3C. Compliance aspect model 330 may define subaspect models. In this embodiment, seven different subaspect models 348, 350, 352, 354, 356, 370, and 372 are shown. Thus, compliance aspect model 330 may include the subaspect models shown in Figure 3C and / or the subaspect models shown in Figure 3E. All subaspect models 348, 350, 352, 354, 356, 370, and 372 may have a 1:0 or 1:1 relationship with the parent compliance aspect model 330. Therefore, all child aspect models 348, 350, 352, 354, 356, 370, and Figure 372 shown in Figure 3E may represent non-essential aspect models.

[0128] Sub-aspect model 348 may define data associated with the declaration of nanomaterials contained within the manufactured product 106. The declaration of nanomaterials may include data indicating the classification of compounds within the product that are nanomaterials, according to existing regulations of the European Union, France, Belgium, Denmark, Sweden, Switzerland, and the United States, or according to existing definitions and vocabulary such as ISO TS 80004-1, European Commission Recommendation 2011 / 696 / EU.

[0129] The sub-aspect model supplier information 350 may include information about the suppliers of compounds present in product 106. Attributes included in the above aspect model 350 may include the product name of the supplied compound, the country of origin of the supplied compound, the supplier name, the supplier identifier, the manufacturer, the composition of the supplied compound, and the chemical registration data of the supplied compound. The supplier information aspect model 350 may be linked to further sub-models such as the composition component aspect model 358, the chemical registration aspect model 360, the signature area aspect model 362, and the customs aspect model (not shown, which may define the tariff number of the supplied product). The relationships may differ depending on the aspect model. For example, aspect model 358 may have a 1:0 or 1:many relationship with the parent aspect model 350 to reflect two or more compounds present in the product, while aspect models 360 and 362 and the customs aspect model (not shown) may have a 1:1 relationship with the parent aspect model 350.

[0130] The composition component aspect model 358 may include the following attributes, namely, CAS number, content, name, or encoded document as described in relation to Figure 3C. The signature area aspect model 362 may include the following attributes, namely, data indicating that the information is true and complete, comments, company name, function, name, date, telephone number, email address, and signature information.

[0131] Chemical registration aspect model 360 may be the parent aspect model of aspect models 364 and 366 associated with the registration of supplied materials 102 in various countries. The number of aspect models 364 and 366 may vary and depend on the number of countries where chemical compounds need to be registered. Countries where chemical compounds need to be registered include Australia, Canada, China, Japan, South Korea, New Zealand, the Philippines, Switzerland, Taiwan, and the United States. Registration information EUREACH aspect model 368 may contain data on the registration of all compounds compliant with REACH.

[0132] Transaction control DM352 may include the following attributes: product name, name of the supplied product, supplier ID (such as a unique participant ID used within a decentralized network), and supplier contact information. Transaction control DM352 may define one or more sub-aspect models. The relationship between transaction control DM352 and one or more sub-aspect models may be a one-to-one relationship. Sub-aspect models may include signature area aspect models such as signature area DM362, aspect models for international trade control that define whether a product contains compounds listed as chemical and / or biological weapons, and one or more aspect models for specific regions that specify regulations regarding the declaration of compounds.

[0133] ReachDM354 may include the following attributes: product name, product supplier name, product supplier ID (such as a unique stakeholder identifier used within a decentralized network), country code of product origin, or a combination thereof. Reach354 may define one or more sub-aspect models. The relationship between transaction management DM352 and one or more sub-aspect models may be a one-to-one relationship. Sub-aspect models may include signature area aspect models such as signature area DM362 and aspect models that define reach information for regions such as EMEA.

[0134] SPM Information DM370 may define information relating to synthetic polymer particulate matter (SPM). Synthetic polymer particulate matter may be synthetic polymer particulate matter as defined in accordance with Regulation (EC) No. 1907 / 2006 REACH Annex X VII. For example, synthetic polymer particulate matter (SPM) is a solid and (a) is contained in particles and constitutes at least 1 wt% of those particles, or constructs a continuous surface coating on the particles, and (b) at least 1 wt% of the particles referred to in point (a) satisfies either of the following conditions: (bi) all dimensions of the particles are 5 mm or less, or (b.ii) the length of the particles is 15 mm or less and the ratio of length to diameter of the particles is greater than 3, (c) is not a chemically modified substance, is not a polymer obtained as a result of a naturally occurring polymerization process, (d) is not a degradable polymer as demonstrated in Appendix [X], (e) is a polymer that does not have a solubility greater than 2 g / L as demonstrated in Appendix [Y], and (f) is a polymer that contains carbon atoms in its chemical structure. The synthetic polymer microparticle aspect model may include the following attributes: a product containing SPMs, and a list of SPMs. The product containing SPMs may be a Boolean type defining whether or not synthetic polymer microparticles are present at a concentration of 0.01% by weight or more. The synthetic polymer microparticle aspect model may define one or more sub-aspect models, such as SPM item DM374. The relationship between the synthetic polymer microparticle aspect model and one or more sub-aspect models may be a 1:0 or 1:many relationship. One or more sub-aspect models may define a list of SPMs present in a chemical material. The list of SPMs may include data on the identity of the SPMs, such as CAS numbers, data on the amount or concentration of SPMs in the chemical material, and / or data on the function and / or desired properties of the SPMs.

[0135] GxP DM372 can define the documentation required in a regulatory environment. A regulatory environment may specify guidelines for ensuring high product quality and may include defined documentation requirements. Some of the required documentation may be shared with further stakeholders in a decentralized stakeholder network. The required documentation may be shared during audits. Examples of such regulatory environments include Good Manufacturing Practices (GMP), Good Laboratory Practices (GLP), Good Clinical Practices (GCP), and ISO certifications such as ISO 17025. A regulatory environment aspect model may define a list of eligible electronic signatures. A regulatory environment aspect model may define one or more sub-aspect models. The relationship between a regulatory environment aspect model and one or more sub-aspect models may be 1:0 or 1:many. One or more sub-aspect models may include an aspect model specifying required documentation (such as the storage location of the site master file, data on risk management, data on the quality assurance system, and data on verification under Article 46b(2)(b) of Directive 2001 / 83 / EC), an aspect model specifying required reports (such as a Certificate of Analysis), and / or an aspect model specifying data on electronic signatures.

[0136] Compliance aspect model 330 may include further sub-aspect models not shown in Figures 3C and 3E. Such further aspect models include the UKREACH information aspect model and the KKDIK information aspect model.

[0137] The compliance aspect model 330 enables the compilation of data containing all the information required by the recipient of material 102 to meet regulatory requirements. For example, the compliance aspect model 330 enables the compilation of necessary data from suppliers in a standardized format, simplifying the data acquisition and exchange process between the supplier of material 102 and the producer of product 106 from the material. The supplier of material 102 may use the compliance aspect model 330 and appropriate sub-aspect models to generate a digital twin template that enables the generation of a digital twin of the material containing all the data required by the material consumer (e.g., the operator of production 104). The data acquired from the supplier in a standardized format may be used in generating a digital twin of product 106 produced from material 102.

[0138] Figure 4A shows an example of a digital twin template associated with a product generated by selecting an aspect model included in a digital twin master template according to an exemplary embodiment of the present disclosure. The product may be produced from at least one input material 102 by production such as production 104 described in relation to Figures 1A-1C. The product may be a chemical product.

[0139] A digital twin master template may define multiple aspect models 402, 404, 406, and 408. Digital twin master template 302 may be the digital twin master template 302 described in relation to Figures 3A to 3E. The multiple aspect models may include essential aspect models such as aspect models 402 and 404, and optional aspect models such as aspect models 406 and 408, as described in relation to Figures 3A to 3E. At least some of the aspect models included in digital twin master template 302 may define the chemical and / or physical properties of a product or product class.

[0140] The generation of a digital twin template 410 from a digital twin master template 302 may involve the selection of at least one aspect model from a set of defined aspect models in the master template 302. The digital twin template 410 may be generated using the apparatus disclosed in relation to Figure 5. The digital twin template 410 may be generated by the method described in relation to Figure 6A. In this embodiment, two essential aspect models 402, 404 and an optional aspect model 406 are selected to generate the digital twin template 410. The selection of aspect models defined in the digital twin master template 302 may be performed as described in relation to Figure 6A. The digital twin template 410 may define or include the selected aspect models. The digital twin template 410 may define or include digital representations that point to at least a portion of the selected aspect models. This avoids such updates to the digital twin template 410, thus allowing for more efficient updates of the generated digital twin template 410. Instead, the digital representation refers to the updated aspect model without the need to modify the digital twin template in that way, so it is sufficient to simply update each aspect model.

[0141] Figure 4B shows an example of a digital twin template associated with a product generated by selecting an aspect model included in a digital twin master template and further aspect models included in a model database, according to an exemplary embodiment of the present disclosure. The product may be produced from at least one input material 102 by production such as production 104 described in relation to Figures 1A to 1C. The product may be a chemical product.

[0142] The digital twin master template 302 may define multiple aspect models 402, 404, 406, and 408, as described in relation to Figure 4A. The model database 418 may include at least one further aspect model 412, 414, and 416. The at least one further aspect model may differ from the aspect models 402-408 defined in the digital twin master template 302. The at least one further aspect model may define a tree structure having one or more levels, as described in relation to Figures 3B-3E, for example. Thus, at least one further aspect model may define one or more child aspect models, and one or more child aspect models may define further child models, and so on. The further aspect models may be specific to the product from which the DT template 420 is to be generated. The model DB 418 may be part of a decentralized network, as described above.

[0143] The generation of the digital twin template 420 from the digital twin master template 302 may include the selection of at least one aspect model from a plurality of aspect models defined in the master template 302, as well as the selection of at least one further aspect model stored in the model DB 418. The digital twin template 420 may be generated using the apparatus disclosed in relation to Figure 5. The digital twin template 420 may be generated by the method described in relation to Figure 6A. In this embodiment, two essential aspect models 402, 404 and an optional aspect model 406 are selected from the digital twin master template DT master template of product 302, and two further aspect models 414, 416 are selected from the model DB 418 to generate the digital twin template 420. In this embodiment, two further aspect models are selected. However, it is also possible to select fewer or more further aspect models. The selection of aspect models defined in the digital twin master template 302 and the model DB 418 may be performed as described in relation to Figure 6A. The digital twin template 420 may define or include digital representations that refer to at least a portion of the selected aspect model, as described in relation to Figure 4A.

[0144] The selected additional aspect models 414, 416 may be used to update the digital twin master template 302 by correcting the digital twin master template 302 so that the additional aspect models 414, 416 are defined therein (not shown). The master template 302 may be updated as described in relation to Figure 6B. Updating the digital twin master template 302 makes it possible to provide other stakeholders in the ecosystem generating the digital twin with a wider selection of aspect models, reducing the effort required to generate product-specific aspect models, ensuring necessary standardization, and enabling the simplification and customized exchange of product data within the product ecosystem.

[0145] Figure 5 shows an apparatus 116 for generating a digital twin template associated with a product, according to an exemplary embodiment of the present disclosure. The product may be a chemical product. The apparatus 116 may be a decentralized participant node in a decentralized network. The apparatus 116 may be included in the operating system 108 of a production 104 that produces product 106 from one or more input materials 102 (see, for example, Figures 1A to 1C). Production 104 may be a chemical production, for example, as described in relation to Figures 1A and 2. The apparatus 116 may be communicatively coupled to the operating system 108 of the production 104 that produces product 106 (see Figure 1C). The apparatus 116 may be configured to generate a digital twin template associated with a product using, for example, the method described in relation to Figure 6A. The apparatus 116 may be configured to update a digital twin master template, for example, as described in relation to Figure 6B.

[0146] Device 116 may be connected to a decentralized network 514. The decentralized network may be a decentralized peer-to-peer communication network. The decentralized network may include participant network nodes associated with participants in the product ecosystem. Decentralized participant nodes may include network nodes in the decentralized network. Decentralized participant nodes may be connected to or included in device 116 for generating DT templates. The device for generating DT templates may include a decentralized data consumption network node (not shown, see, for example, Figure 15) configured to consume the master template 302 from the master template DB 512. The decentralized network 514 may include infrastructure nodes. Infrastructure nodes may not be associated with participants in the product ecosystem. Infrastructure nodes may include network nodes in the decentralized network 514. Infrastructure nodes may include the master template DB 512. Infrastructure nodes may include the model DB 418.

[0147] A decentralized network 514 may be configured to perform data transactions. Data transactions may be based on a transaction protocol that includes an authentication mechanism and / or an authorization mechanism. Based on the authentication and / or authorization mechanism, peer-to-peer communication may be established between decentralized network nodes associated with stakeholders in the product ecosystem. One or more authentication mechanisms may be associated with or linked to decentralized digital twin identifiers and / or decentralized access element identifiers. One or more authentication mechanisms may be associated with or linked to decentralized stakeholder identifiers associated with stakeholders in the product ecosystem.

[0148] The master template DB512 may store at least one digital twin master template 302. An example of a digital twin master template stored in the master template DB512 is shown in Figures 3A to 3F. The digital twin master template 302 stored in the master template DB512 may define multiple aspect models, as described in relation to Figures 3A to 3F. The master template DB512 may be connected to a decentralized data serving network node (not shown) configured to control access to the master template 302. The master template DB512 may be configured to provide the master template 302.

[0149] Model DB418 may store at least one further aspect model, as described in relation to Figure 4B. Model DB418 may be connected to a decentralized data serving network node (not shown) configured to control access to Model DB418. Model DB418 may be configured to provide at least one further aspect model.

[0150] The device 116 for generating DT templates may include a digital twin template generator 504. The digital twin template generator 504 may be configured to receive requests to generate digital twin templates. Requests may be received from a user via an I / O device 510. The I / O device 510 may be connected to the digital twin template generator 504 via a communication interface such as a network. The I / O device 510 may be configured to display a user interface that allows the user to select a master template 302 and / or one or more further aspect models. The user interface may display available master templates 302 stored in the master template DB 512 and / or available further aspect models stored in the model DB 418. Data regarding the available master templates 302 and / or further aspect models may be collected via a decentralized data consumption network node associated with the digital twin template generator 504 and provided to the I / O device 510 for display on a screen.

[0151] The request may include data related to the product. Product-related data may include product identifiers and / or product classes, as described in relation to Figure 6A. The digital twin template generator 504 may be configured to collect digital twin master templates associated with one or more product classes. The master template 302 may be collected from the master template DB 512. The master template 302 may be collected based on the data contained in the received request. Collecting the master template 302 may include retrieving or receiving the master template 302 from the master template DB 512.

[0152] The digital twin template generator 504 may be configured to collect product data based on the data contained in the received request. Collection may include acquiring or receiving product data. Product data may be stored in the product data DB 502. Product data may include data or classes of data contained in the digital twin associated with the product. Classes of data may include data related to product use, data related to product production, product composition data, product characteristic data, data associated with the ecological profile of the product, regulatory data associated with the product, certificates associated with the product, or a combination thereof. Product data may further include one or more product identifiers and / or product names. At least one product identifier may correspond to a product identifier contained in the received request. The product data DB 502 may be associated with a production, such as production 104 described in relation to Figures 1A-2, which produces product 106 from one or more materials 102 that enter production. The product data DB 502 may be a distributed data source as described above.

[0153] The digital twin template generator 504 may be configured to collect one or more further aspect models. Collecting may include obtaining and / or receiving at least one further aspect model. Further aspect models may be collected from model DB 418. Further aspect models may be collected based on data contained in the received request. Further aspect models may be collected based on collected product data.

[0154] The digital twin template generator 504 may be configured to generate a digital twin template based on collected product data. The digital twin template may define at least one aspect model defined in the digital twin master template. The digital twin template may further define at least one additional aspect model stored in the model DB 418. Generating a digital twin template may include, for example, selecting at least one aspect model defined in the master template 302, as described in relation to Figures 4A and 6A. Generating a digital twin template may include, for example, selecting at least one aspect model defined in the master template 302 and at least one additional aspect model, as described in relation to Figures 4A and 6A. Selecting at least one aspect model may include matching the collected product data with the chemical and / or physical properties defined by each aspect model (e.g., the aspect model included in the digital twin master template 302 and optionally additional aspect models). The generated digital twin template may be provided to the template DB 506. Template DB506 can store generated digital twin templates. Stored digital twin templates can be associated with product identifiers or product class identifiers. This makes it possible to collect digital twin templates, for example, when generating a digital twin of a product. Digital twin templates can be generated for specific products. Digital twin templates can be generated for product classes.

[0155] Figures 6A and 6B show an example of a computer-aided method for generating a digital twin associated with a product or product class, according to exemplary embodiments of the present disclosure. The product may be a chemical product. The product may be produced by production 104 from at least one input material 102 (see Figures 1A to 2). Production 104 may be a chemical production (see Figure 2). The method may be carried out using apparatus 116, for example, as described in relation to Figure 5. A digital twin template may be generated by the operating system 108 of production 104. The operating system 108 may include apparatus 116 for generating a DT template, for example, as described in relation to Figure 5. A request to generate a digital twin may be manually triggered by a user via a user interface, for example using an I / O device 510 (see Figure 5). The digital twin template may define one or more aspect models included in the digital twin master template used to generate the digital twin template (see Figure 4A). The digital twin template may further define one or more further aspect models, such as further aspect models provided from model DB 418 (see Figure 4B).

[0156] In block 608, a request may be received to generate a digital twin template. The request may include data related to the product. This data may include a product identifier, product class, or a combination thereof. The product identifier may include a batch number, product name, product ID, part number, lot number, or a combination thereof. The lot number may be assigned to the product during production.

[0157] In block 610, a digital twin master template may be provided. The digital twin master template may define multiple aspect models. At least some of the aspect models may describe the chemical and / or physical properties of a product or product class, as shown, for example, in Figure 3A. Multiple aspect models may be defined by the digital twin master template by including such aspect models in the digital twin master template (see, for example, Figure 3A). Multiple aspect models may be defined by the digital twin master template by including one or more digital representations that point to such aspect models in the digital twin master template. Examples of digital master templates and aspect models defined by such digital twin master templates provided in block 604 are described in relation to Figures 3A to 3E. The digital twin master template may be provided from data storage 604 which includes at least one digital twin master template. Data storage 604 may be a central database. Data storage 604 may be part of a decentralized network, such as a decentralized network 514. The digital twin master template stored in data storage 604 can be accessed by decentralized data consumption network nodes, such as decentralized data consumption network node 808. Decentralized data consumption network nodes may be part of a decentralized network 514. Decentralized data consumption network nodes may be associated with stakeholders in the product ecosystem that generate the digital twin template. The stored digital twin master template can be provided by decentralized data provision network nodes associated with data storage 604. Decentralized data provision network nodes may be part of a decentralized network 514. A decentralized configuration enables more efficient use of computing resources.

[0158] In block 612, product data may be provided based on data related to the product included in the received request. Product data may include data or classes of data that should be included in the digital twin associated with the product. Classes of data may include, as described above, data related to product use, data related to product production, product composition data, product characteristic data, data related to the product's ecological profile, regulatory data associated with the product, certificates associated with the product, or a combination thereof. Product data may further include one or more product identifiers and / or product names. At least one product identifier may correspond to a product identifier included in the received request. Product data may be provided from data storage 602 that stores the above product data. Product data may be provided based on product identifiers included in the received request. Data storage 602 may be connected to the data source layer 704, as described in relation to Figure 7A. Data storage 602 may correspond to DT storage 720 that stores collected data associated with the product, as described in relation to Figure 7A.

[0159] In decision block 614, it may be determined whether or not further aspect models should be provided. The decision may be based on the provided product data. For example, the provided product data may be used to determine further aspect models that match the above product data or a part thereof. The matching further aspect models may be determined by matching the product data with data points defined by the further aspect models, such as chemical and / or physical properties defined by such aspect models. If it is determined in block 614 that further aspect models should be provided, the method may proceed to block 620. Otherwise, the method may proceed to block 616.

[0160] In block 616, a digital twin template may be generated by selecting at least one aspect model from a plurality of aspect models defined in a provided digital twin master template, based on the provided product data. Selecting at least one aspect model from a plurality of aspect models defined in a digital twin master template may include mapping the provided product data to the aspect models defined in the digital twin master template. Mapping may include matching the provided product data with aspect model data associated with the aspect models defined in the digital twin master template. Mapping may include matching the provided product data with data point chemical and / or physical properties defined by the aspect models included in the digital twin master template. If the provided product data can be mapped to one or more aspect models defined in the digital twin, the above aspect models may be selected. In addition, the aspect models may be selected from a plurality of aspect models defined in a digital twin master template based on the relationships between one or more aspect models of the plurality of aspect models. For example, the relationships may define the essential aspect models that can be selected based on such relationships.

[0161] In block 618, at least one additional aspect model may be provided. At least one additional aspect model may be provided from a storage environment 606, such as model DB418, as described in relation to Figures 4B and 5, which contain the additional aspect model. The storage environment 606 may be a central database. The storage environment 606 may be part of a decentralized network, such as decentralized network 514. The additional aspect model stored in the storage environment 606 may be accessed by decentralized data consumption network nodes, as described above. Decentralized data consumption network nodes may be associated with stakeholders in the product ecosystem that generate the digital twin template. The stored additional aspect model may be provided by decentralized data provision network nodes associated with the database, as described above. By using additional aspect models not defined in the digital twin master template, it becomes possible to generate digital twin templates for products in a flexible manner so that the digital twin of the product generated using the above digital twin template includes all the necessary data. Therefore, available aspect models (e.g., aspect models defined in the digital twin master template and further aspect models) can be combined in a modular manner to design a digital twin template for a specific product or product class, thereby generating a digital twin for such product or product class that includes all the data necessary to satisfy at least the regulatory requirements associated with such product or product class. The modular approach further enables consideration of requirements imposed by downstream stakeholders in the product value chain, such as consumers and further downstream stakeholders of the product, as well as / or stakeholders in the recycling chain associated with the product. This ensures that the digital twin template includes all the aspect models necessary to satisfy not only regulatory requirements but also further requirements imposed by stakeholders in the product ecosystem.

[0162] In block 622, a digital twin template may be generated by selecting at least one aspect model from a plurality of aspect models defined in the provided digital twin master template, and by selecting at least one further aspect model. Selecting at least one aspect model from a plurality of aspect models defined in the digital twin master template may include mapping the provided product data to the further aspect model, as described above (see block 616). Selecting at least one further aspect model from the provided further aspect models may include mapping the provided product data to the further aspect model, as described in relation to block 616.

[0163] A digital twin template generated in block 616 or block 622 may include at least one of the aspect models defined in the digital twin master template (see also Figure 4A). A digital twin template generated in block 620 may include at least one of the aspect models defined in the digital twin master template and at least one additional aspect model (see also Figure 4B). A digital twin master template generated in block 616 or block 622 may include one or more digital representations that point to the aspect models defined in the digital twin master template. A digital twin template generated in block 622 may include one or more digital representations that point to additional aspect models selected in block 622. Therefore, a digital twin template may include a subset of the aspect models defined in the digital twin master template. A digital twin template may include additional aspect models not defined in the digital twin master template. This makes it possible to generate a digital twin template that includes all the aspect models necessary to meet regulatory requirements and requirements imposed by stakeholders in the product ecosystem.

[0164] In block 618, a digital twin template generated in block 616 may be provided. Providing the generated digital twin template may include providing the digital twin template to a database such as the template DB 506 described in relation to Figure 5. The digital twin template may be correlated with data associated with products and / or product data in the database. For example, the digital twin template may be correlated with one or more identifiers associated with products or product classes in the database. Providing the digital twin template may include providing the template via a communication interface for display. This makes it possible to control the aspect models defined in the template to ensure that all necessary aspect models are properly defined. This avoids data loss in the digital twin generated from the digital twin template and therefore ensures that the digital twin generated from the digital twin template contains all necessary data.

[0165] In block 624, the digital twin template generated in block 622 may be provided as described in relation to block 618.

[0166] The method shown in Figure 6A enables the generation of customized digital twin templates using a modular approach by selecting one or more aspect models from a digital twin master template that defines multiple aspect models existing for a product or product class in a hierarchical order. The generation of digital twin templates may further include the selection of additional aspect models not included in the digital twin master template, allowing for consideration of product specificities not covered by the aspect models included in the digital twin master template. This modular approach makes it possible to select appropriate aspect models (e.g., aspect models necessary to describe the characteristics of a product that meet regulatory requirements for the product being manufactured) from the digital twin master template and optionally additional available aspect models. Therefore, the digital twins of products generated from such customized digital twin templates have a highly defined data structure, simplifying data exchange and sharing, while simultaneously ensuring that they include all relevant data necessary to meet regulatory requirements. This modular approach significantly reduces the complexity associated with generating only one aspect model for each product or product class, enabling the efficient generation of digital twin templates for various different products or product classes. Furthermore, the modular approach avoids the problems associated with maintaining a single large-scale aspect model and the use of inappropriate semantic descriptions of specific products or product classes within such a single large-scale aspect model, thus avoiding empty attributes resulting from missing product data in the digital twin.

[0167] In decision block 626, it may be determined whether or not the digital twin master template should be updated. The decision may be based on whether or not at least one additional aspect model was used to generate the digital twin template (for example, whether blocks 620 and 622 were executed). If the generated digital twin master template should not be updated, the method may terminate or return to block 608. If the generated digital twin should be updated, the method may proceed to block 628.

[0168] In block 628, the provided digital twin master template may be updated using at least one additional aspect model provided in block 620. Updating may include defining one or more additional aspect models in the digital twin master template. Defining one or more additional aspect models may include including the additional aspect models in the digital twin master template. Defining one or more additional aspect models may include defining digital representations in the digital twin master template that refer to the additional aspect models.

[0169] In decision block 630, it may be determined whether an updated digital twin master template can be provided. If an updated digital twin master template should be provided, the method may proceed to block 632. Otherwise, the method may terminate or return to block 608.

[0170] In decision block 630, the updated digital twin master template may be provided to a database such as template DB 506 and / or master template DB 512, as described in relation to Figure 5. After block 630, the method may terminate or return to block 608.

[0171] Updating the digital twin master template with additional aspect models increases the number of aspect models available for generating digital twin templates and sharing the generated aspect models for a specific product or product class with other stakeholders in the product ecosystem. This allows for more efficient generation of digital twin templates, as it increases the number of available aspect models that can be used in a modular approach during the generation process.

[0172] Figure 7A shows an exemplary apparatus 702 for generating a digital twin of the physical entity of a product using a generated digital twin template. The digital twin template may be generated by apparatus 116 for generating a DT template, as described in relation to Figure 5. The digital twin template may be generated by the method described in relation to Figures 6A and 6B. The product may be a chemical product. Apparatus 702 may be a decentralized participant node in a decentralized network. Apparatus 702 may be included in the operating system 108 of production 104 that produces product 106 from one or more input materials 102 (see, for example, Figures 1A and 1B). Apparatus 702 may be communicatively coupled to the operating system 108 of production 104 that produces product 106 (see Figure 1C). Apparatus 702 may be configured to generate a digital twin of a chemical product using the method described, for example, in relation to Figure 10.

[0173] The apparatus 702 may be coupled to a data source layer 704 which includes one or more distributed data sources 706, 708, 710. The apparatus 702 may include a data source layer 704 (not shown). One or more distributed data sources may be distributed databases. A distributed data source may be a data lake which contains product-related data from multiple distributed data sources. In this example, the data source layer 704 includes three distributed data sources. However, the data source layer 704 may also include fewer or more distributed data sources. One or more distributed data sources may include product-related data, such as chemical products produced by chemical production 104 from one or more input materials 102, as described in relation to Figures 1A to 2. Product-related data may include at least one measured physical and / or chemical property of each product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of each product. At least one physical and / or chemical property may be measured using sensors such as sensors 110a, 110b, and the measured and / or physical property may be stored in a distributed data source. At least one physical and / or chemical property may be determined from data acquired from sensors such as sensors 110a, 110b before, during, and / or after production, and the determined chemical and / or physical property may be stored in a distributed data source. One or more distributed data sources may further include product name, product manufacturer, product declaration data, product safety data, emission data, recyclable content data, bio-based content data, certificates of analytical data associated with the product, certificates associated with the product, or a combination thereof.

[0174] Product-related data may be acquired before, during, and / or after production of product 106. Acquired data may be provided to data source layer 704 for storage. Data source layer 704 may be owned or controlled by the data owner of the data associated with product data. Data source layer 704 may be associated with the data owner of the data associated with product data. At least one of the distributed data sources may include a data instance related to product 106 configured so that the apparatus 702 generates a digital twin. At least one data instance may include at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product. Data source layer 704 may be connected to data acquisition unit 712 via a communication interface such as a network or API. Data source layer 704 may be directly connected to data acquisition unit 712, or it may be connected to a further layer existing between data source layer 704 and data acquisition unit 712 (not shown, see, for example, Figure 7B).

[0175] The data acquisition unit 712 may be configured to receive requests to generate a digital twin associated with product 106 produced by production 104. The requests may include data related to the product. This product-related data may include a product identifier associated with the produced product 106, such as a batch number, lot number, ID, or a combination thereof. Based on the received product-related data, the data acquisition unit 712 may be configured to collect product-related data from the data source layer 704. For example, a product identifier may be received along with a request such as a batch number, and the received product identifier may be used to collect data associated with the product identifier. In another example, a product identifier may be received from a user via an I / O device 510.

[0176] The data acquisition unit 712 may be configured to determine, upon receiving a request to generate a digital twin, whether a digital twin associated with the product is already contained in the DT storage 720. For example, the data acquisition unit 712 may use the product identifier contained in the received request to determine whether a digital twin associated with the product identifier is already contained in the DT storage 720. This avoids generating a digital twin for products for which a digital twin already exists in the DT storage 720 (e.g., a digital twin has already been generated previously).

[0177] The device 702 may further include a digital twin generator 716 configured to generate a digital twin that includes a decentralized digital twin identifier, such as a decentralized digital twin identifier provided by a decentralized ID generator 718, and one or more digital twin datasets, such as a digital twin dataset generated by an aspect agent 714. The decentralized identifier may include one or more DIDs and / or one or more UUIDs. One or more DIDs and / or UUIDs may be associated with a digital twin and / or a digital twin dataset included in the digital twin. One or more DIDs and / or UUIDs may be further associated with a product. The digital twin generator 716 may be configured to generate a digital twin in accordance with the methods described in relation to Figures 8 and 10. The digital twin generator 716 may be configured to request a decentralized digital twin identifier. The request may include at least one authentication mechanism, or may include selecting at least one of a plurality of authentication mechanisms. The request may include an owner identifier and / or a chemical product identifier and / or access data. The digital twin generator 716 may be configured to generate access data. The access data may include a digital representation that points to a digital twin dataset. The access data may further include a digital twin dataset identifier. The digital twin generator 716 may be configured to assign decentralized digital twin identifiers received from the decentralized ID generator 718 to at least a portion of the digital twin dataset generated by the aspect agent 714. For example, the digital twin generator 716 may assign product identifiers included in at least a portion of the digital twin dataset to the received decentralized digital twin identifiers, such that at least a portion of the product digital twin dataset is associated with a decentralized digital twin identifier.Assigning may involve relating a decentralized digital twin identifier to a digital twin dataset associated with a product and stored in the DT storage 720, for example, at least a portion of the digital twin datasets stored in the DT storage 720 by the aspect agent 714, as outlined below. The digital twin generator 716 may be configured to assign a decentralized digital twin identifier received from the decentralized ID generator 718 to a digital twin dataset identifier associated with at least a portion of the digital twin datasets generated by the aspect agent 714. The digital twin generator 716 may be configured to provide the generated digital twin or a portion thereof (for example, a digital twin dataset, also hereafter referred to as an asset or aspect of the digital twin) to the digital twin provider 722. The digital twin generator 716 may be configured to provide the decentralized digital twin identifier and access data associated with the digital twin to the digital twin provider 722. The digital twin generator 716 may be configured to provide the access rules associated with each digital twin or each digital twin dataset to the digital twin provider 722, as described below.

[0178] The device 702 may further include a decentralized ID generator 718 configured to generate and provide decentralized digital twin identifiers associated with data owners, such as data owners of data collected by the data collection unit 712 and optionally collected data. The decentralized ID generator 718 may be configured to generate digital twin dataset identifiers (separate from decentralized digital twin identifiers). The decentralized ID generator 718 may be communicatively coupled to the device 702, and for example, the device 702 may not include the decentralized ID generator 718 (not shown). The decentralized digital twin identifiers may further be associated with data owners of the collected data and / or digital twin datasets, such as entities operating production 104. The decentralized ID generator 718 may be a central or decentralized network node configured to generate decentralized identifiers, such as DID or UUIDv4, as described in relation to Figure 13. The decentralized ID generator 718 may be a computing node that functions as a management module, user agent, ID hub, and / or certificate issuer for the DID owner. The decentralized ID generator 718 may be configured to receive requests for a decentralized digital twin identifier associated with the data collection unit 712 and optionally the data collected by the data owner. The request may include at least one authentication mechanism, or may include selecting at least one of several authentication mechanisms. The request may include, as described above, an owner identifier and / or a product identifier and / or access data. The decentralized ID generator 718 may be configured to generate a decentralized digital twin identifier and data related to the authentication mechanism, and to provide the generated digital twin decentralized identifier and data related to the authentication mechanism to the digital twin generator 716.

[0179] The aspect agent 714 may be configured to retrieve or receive a generated digital twin template from the template DB 506 based on the data contained in the received request. The template DB 506 may store digital twin templates. The digital twin template may be generated by the device 116 for generating DT templates, as described in relation to Figure 5. The digital twin template may be generated, for example, according to the method described in relation to Figures 6A and 6B. The digital twin template may be provided based on the product identifier contained in the received request. The aspect agent 714 may be configured to receive or retrieve at least one aspect model from the model DB 418 connected to the aspect agent 714 via a communication interface, based on each digital twin template. The model DB 418 may be part of the decentralized network 514, as described in relation to Figure 5. Each aspect model may include at least some of the structure and / or characteristics of the digital twin dataset.

[0180] The aspect agent 714 may be configured to generate a digital twin dataset associated with a product by applying each acquired or received aspect model to the collected data received from the digital twin generator 716 (see, for example, Figure 9). For example, the aspect agent 714 may map the collected data to the structure and / or characteristics of each aspect model. The aspect agent 714 may be configured to store at least a portion of the generated digital twin dataset in the DT storage 720. This makes it possible to avoid unnecessary data transfer between the aspect agent 714 and the digital twin generator 716. Furthermore, this makes it possible to separate digital twin generation from digital twin access, thus improving the overall stability and availability of digital twin generation and delivery. At least a portion of the digital twin dataset may include a product identifier that enables the generated digital twin dataset to be linked to its respective product. For example, each generated digital twin dataset may include the same product identifier.

[0181] Each digital twin dataset associated with a decentralized digital twin identifier of a digital twin can be considered an asset or aspect of the digital twin. Each asset or aspect can be uniquely identified by a digital twin dataset identifier. Therefore, the combination of a decentralized digital twin identifier and a digital twin dataset identifier can make it possible to uniquely identify a digital twin dataset associated with a product. Furthermore, the above combination also makes it possible to specifically retrieve such a digital twin dataset, for example, via a decentralized data consumption network node, using the decentralized digital twin identifier, the digital twin dataset identifier, and access data as described in relation to Figure 15.

[0182] The device 702 may further include a DT storage 720 configured to store digital twin datasets generated by the aspect agent 714. The DT storage 720 may be configured to store data associated with products collected by the data acquisition unit 712. The digital twin datasets stored in the DT storage 720 can be correlated with decentralized digital twin identifiers provided by the decentralized ID generator 718 to enable the retrieval of the digital twin datasets based on the decentralized digital twin identifiers. The digital twin datasets can be further correlated with digital twin dataset identifiers and, in combination with the digital twin dataset identifiers, to enable the retrieval of specific digital twin datasets based on decentralized digital twin identifiers. This makes it possible to retrieve specific assets or aspects of a digital twin without having to provide all the data contained in the digital twin. Furthermore, this makes it possible to define access rights at the asset / aspect level, and thus enable higher-granularity control over access to the data contained in each asset / aspect of the digital twin.

[0183] The device 702 may further comprise a digital twin provider 722 configured to provide a digital twin or a portion thereof generated by the digital twin generator 716 for access by a decentralized data consumption network node associated with, for example, a consumer of a chemical product (see also Figure 15). The digital twin provider may be a decentralized data provision network node. The device 702 may be communicatively coupled to a digital twin provider 722 configured to provide the digital twin generated by the digital twin generator 716 for access (not shown, see, for example, Figure 7B). The digital twin provider 722 may be configured to receive a generated digital twin or a portion thereof (e.g., an asset or aspect of the digital twin) from the digital twin generator 716. The digital twin provider 722 may be configured to receive a decentralized digital twin identifier and access data associated with the digital twin from the digital twin generator 716. The digital twin provider 722 may store the received data in a database (not shown). This allows the digital twin provider 722 to retrieve a digital twin or a portion thereof from, for example, the DT storage 720, as described with respect to Figures 8 and 15, and provide the respective data to decentralized data consumption network nodes. For example, the database may store the decentralized digital twin identifier and access data associated with each digital twin. By storing the access data for each digital twin dataset in combination with the decentralized digital twin identifier, it becomes possible to avoid unnecessary data traffic. This is because, upon request (for example, a request from a decentralized data consumption network node), only the requested digital twin dataset contained in the digital twin needs to be retrieved, rather than the complete data contained in the digital twin. Based on the decentralized digital twin identifier and the access data stored in the database, the digital twin provider 722 may retrieve a digital twin or a portion thereof from the DT storage 720 and provide the retrieved data to decentralized data consumption network nodes.

[0184] The digital twin provider 722 may be configured to receive access rules associated with each digital twin or a portion thereof from the digital twin generator 716. The digital twin provider 722 may be configured to store the received access rules in its database. The access rules may include a list of decentralized participant identifiers associated with decentralized data consumption network nodes that are permitted to access the data contained in the digital twin or digital twin dataset. The access rules may include usage policies that define the processing, aggregation, or transfer of the data in the digital twin or digital twin dataset. The access rules may be associated with decentralized centralized digital twin identifiers of the digital twin and / or the digital twin dataset of the digital twin. The access rules may be further associated with digital twin dataset identifiers.

[0185] Usage policies can be constrained by the data being exchanged, and enforcement of attached usage policies can be continuously controlled, for example, by decentralized data consumption network nodes receiving the data, or by decentralized data processing network nodes processing the received data. Usage policies can be instantiated on the target system. Usage policies can be data-dependent (also called sticky policies). Sticky policies are one way of dealing with the distribution of usage restrictions. In this approach, machine-readable usage policies can be attached to the data during data exchange. Different implementations are also possible. For example, the data can be encrypted and only decrypted if compliance with usage restrictions is guaranteed.

[0186] Usage policies may include additional information provided, for example, by a policy information registry. This additional information may include information about contextual information such as previous data usage or the geographical location of the entity, pre-conditions or post-conditions that must be maintained before (e.g., integrity checks) and after (e.g., data items are deleted after use), and on-conditions that must be maintained during use (e.g., only during business hours). For example, a policy information registry may be used to resolve supplier IDs to postal addresses, and postal addresses to GPS coordinates.

[0187] Usage control may be implemented by encrypting the data within a decentralized network node connected to the storage infrastructure before transferring the data to the storage infrastructure. Data usage is only possible by decrypting the data using the decentralized network node. Therefore, all usage is controlled by the decentralized network node. In such cases, usage restrictions, such as data lifetime or time constraints, may be implemented by deleting the cryptographic key material. Additionally or alternatively, the storage infrastructure may include usage control enforcement components that monitor and / or control data usage.

[0188] Figure 7B shows an example of a hierarchical system for generating a digital twin of the physical entity of a product. The product may be a chemical product. The hierarchical system may be contained within an operating system 108 of a production 104 that produces a product 106 from one or more input materials 102 (see, for example, Figures 1A and 1B). At least a portion of the hierarchical system may be contained within the operating system 108, while another portion may be communicatively coupled to the operating system 108 (see, for example, Figure 1C).

[0189] The hierarchical system may include a data source layer 704, such as the data source layer 704 described in relation to Figure 7A. The data source layer 704 may include one or more distributed data sources 706, 708, 710. The distributed data sources may include data instances related to products 106 produced by production 104, as described in relation to Figures 2 and 7A.

[0190] The system may further comprise a service layer 724, which is generally optional. The service layer may be configured to collect product-related data from the data source layer 704. The service layer may be configured to collect data according to predefined selection criteria. The service layer may be configured to apply one or more semantic models to the collected data to generate a uniform data set. The service layer may be configured to deliver the uniform data set to a data streaming platform included in the service layer. The streaming platform may include a platform deployed across several hosts, clusters, data centers, and / or other sets of computing resources. The streaming platform may include one or more client processes that generate records of activity and publish those records to one or more event streams. For example, if a particular type of activity occurs in the data source layer 704, such as the provision of a new uniform data set, the production of a new batch of chemical products, or a new data set associated with the produced chemical products, one or more client processes may generate records of the activity and publish those records to one or more event streams. The data streaming platform can then propagate the record to one or more components that are subscribed to the same event stream. The data propagated to one or more components can be stored in a database located within the service or consumer layer. The data streaming platform thus enables activity occurring in multiple distributed data sources in the data source layer 704 to be captured and transmitted in an integrated and scalable manner.

[0191] The system may further comprise a consumer layer 726. The consumer layer 726 may comprise a device for generating a digital twin, such as the device 702 described in relation to Figure 7A. The consumer layer 726 may be configured to collect product-related data from the data source layer 704, for example, as described in relation to Figure 7A. The consumer layer 726 may be configured to consume data from the service layer 724, for example, from one or more databases of the service layer 724, including data stored by consumer components of the service layer 724's data streaming platform. The consumer layer 726 may be configured to generate a digital twin of a product from the data collected from the data source layer 704 or the data consumed from the service layer 724, as described in relation to Figures 7A, 9, and 10. The consumer layer 726 may be connected to an input / output device (not shown), for example, the I / O device 510 in Figure 7A. The I / O device 510 may be used to trigger the generation of a digital twin of a product, as described in relation to Figure 7A.

[0192] The system may further comprise a connector layer 728. The connector layer 728 may be configured to provide a digital twin or a portion thereof generated in the consumer layer 726 for access. The connector layer 728 may comprise a digital twin provider 722, such as a decentralized data delivery network node as described with respect to Figures 8 and 15, configured to provide access to the digital twin or a portion thereof. Access may be controlled by the data owner of the digital twin or a portion thereof via the digital twin provider 722, by access rules associated with the digital twin or a portion thereof, as described with respect to Figure 7A, for example. The digital twin provider 722 of the connector layer 728 may be configured to exchange data, such as the data contained in the digital twin, with a decentralized data consumption network node. The decentralized data consumption network node may be associated with a consumer or processor of the product (see, for example, Figure 15). The decentralized data delivery network node and the decentralized data consumption network node may perform an authentication step before data exchange. The digital twin provider 722 may apply access rules associated with the digital twin or a portion thereof requested by the decentralized data consumption network node before providing the data to the decentralized data consumption network node, as described, for example, in relation to Figure 7A. Based on the access rules, the digital twin provider 722 may deny access to the digital twin or a portion thereof. Based on the access rules, the digital twin provider 722 may grant access to the digital twin or a portion thereof. Based on the access rules, the digital twin provider 722 may modify access to the digital twin or a portion thereof. Access may be granted to all data contained in the digital twin (e.g., all data associated with the decentralized digital twin identifier) ​​or a portion thereof (e.g., a specific digital twin dataset contained in the digital twin).

[0193] A hierarchical system makes it possible to achieve the availability, integrity, and confidentiality of data contained in a digital twin or digital twin dataset. The connector layer ensures that only predefined decentralized network stakeholders can access and retrieve the data associated with the digital twin. For example, separating digital twin generation from the consumption of data contained within the digital twin enables high and stable availability of data within the digital twin within a decentralized network.

[0194] Figure 8 shows an exemplary system and associated method for generating a digital twin associated with a product produced by production and providing access to the generated digital twin. The product may be a chemical product. The digital twin may be generated using a digital twin template. The digital twin template may be generated by the apparatus 116 for generating DT templates, as described in relation to Figure 5. The digital twin template may be generated according to the method described in relation to Figures 6A and 6B. The apparatus for generating the digital twin may be the apparatus 702, as described in relation to Figure 7A. The apparatus for generating the digital twin may be included in the operating system 108 of production 104 (see, for example, Figures 1A and 1B). The apparatus for generating the digital twin of a product may be communicatively coupled to the operating system 108 of production 104 (see, for example, Figure 1C). The digital twin may be generated as described in relation to Figure 7B.

[0195] Production 104 may be a chemical production as described in relation to Figures 1A to 2. Production 104 may produce at least one product 106 from one or more input materials 102. Input materials may be supplied to production 104 as described, for example, in relation to Figures 1A to 1C. Input materials may enter the system boundary 802 of production 104 at an inlet point such as a production plant or material storage facility associated with production 104. The amount of input materials entering the system boundary 802 of production 104 may be measured, for example, using a sensor 110b as described in relation to Figures 1A to 1C. The chemical and / or physical properties of the input materials may be measured, for example, using a sensor 110a as described in relation to Figures 1A to 1C, after they have passed through the system boundary 802 of production 104. The measurement data may be used to determine at least one chemical and / or physical property of the input materials.

[0196] Input materials may be used in production 104 to produce one or more products 106 from input materials 102, as described in relation to Figures 1A to 1C, for example. The operating system 108 of production 104 may monitor and / or control chemical production based on the operating parameters of different processes. The operating system 108 may receive production demand data associated with the production plan of production 104. The production demand data may be generated from the target production capacity of one or more chemical products to be produced by production 104. The production demand data may be generated from a predefined production capacity or from a data-driven model that associates production capacity with market demand data or the amount consumed at the point of consumption. The production demand data may include the target capacity of the products to be produced by production 104. The operating system 108 may further receive a bill of materials associated with the products to be produced. The bill of materials may include input material data associated with the materials used to produce the product, process data associated with the production chain for producing the product, and / or product data associated with the product, such as product specification data or the quantity of product to be produced.

[0197] Based on the received production demand data and material list, material demand data may be determined. The material demand data may include data on the amount of material needed to produce a target production quantity of product 106. The material demand data may include material identifiers associated with the materials needed to produce product 106, and data on the quantity of each material. For each material identifier, the material demand data may include one or more material specifiers indicating the material specifications. For each material identifier, the material demand data may include data on material quantities indicating the amount of material supplied. The material demand data may specify the production chain of production 104. The material demand data may include bills of materials for one or more production chains of production 104. The material demand data may include one or more recipes specifying one or more materials for the production process of production 104. The determined material demand data may be provided for access by supplier systems associated with suppliers outside the physical system boundary of production 104. Material supply may be triggered by the supplier system accessing the material demand data.

[0198] The amount of product 106 resulting from processes performed within production 104, such as chemical reactions and / or physical processing and / or assembly processes, can be measured using sensors such as sensor 110a, as described in relation to Figures 1A to 1C. Since chemical reactions can yield two or more reaction products, for example, chemical reactions involve a many-to-many relationship between starting materials and resulting reaction products (see also Figures 1A to 1C), and by measuring the amount of chemical product resulting from each chemical reaction performed within the chemical production, it becomes possible to track the flow of materials within the chemical production. The measured data can be stored in one or more databases associated with the operating system 108. Furthermore, chemical reactions and / or physical processes can be monitored using sensors such as sensor 110b, and the generated monitoring data can be stored in one or more databases associated with the operating system 108. The measured amount and monitoring data of the produced products can be used to generate a digital twin of each production process performed within production 104. The measured amount and monitoring data of the produced products can be used to generate a digital twin of production 104. This digital twin allows for reliable tracking and consideration of the flow of input materials, intermediate chemicals, and chemical products, even when there is a many-to-many relationship between the starting materials and reaction products associated with a chemical reaction. The physical and / or chemical properties of the produced product can be measured by sensors such as sensor 110a and / or determined as described with respect to Figures 1A to 1C. The measured and / or determined chemical and / or physical properties of the produced product 106 can be stored in one or more databases associated with the operating system 108.

[0199] The produced chemical product 106 may be delivered at one or more exit points of production 104. Product 106 may leave the system boundary 802 of production 104. When product 106 is produced, or when product 106 leaves production 104, a digital twin may be generated. Apparatus 702 may be configured to generate a digital twin, as described with respect to Figures 7A and 10. A requester 804 may be configured to generate a request to generate a digital twin. The requester 804 may be included in a labeling device, as described, for example, with respect to Figure 2. The request may include data related to the product, such as a batch number. The request to generate a digital twin may be provided to a data acquisition unit 712 of apparatus 702. In response to the request, the data acquisition unit 712 may be configured to collect data related to the product, for example from a data source layer 704 (not shown, see, for example, Figures 7A and 7B), based on the data included in the received request (see Figures 7A and 7B). The data acquisition unit 712 may be configured to determine whether a digital twin associated with the manufactured product 106 is already contained in the DT storage 720 (see Figure 7A). A request to generate a digital twin may be provided to the digital twin generator 716 of the device 702 (not shown). In response to the request, the digital twin generator 716 may be configured to initiate the collection of data associated with the product by the data acquisition unit 712.

[0200] The data collection unit 712 may provide the collected data to the digital twin generator 716. The digital twin generator 716 may be configured to request the collected data and a decentralized digital twin identifier optionally associated with the data owner from the decentralized ID provider 806, as described, for example, in relation to Figure 7A. The digital twin generator 716 may be configured to obtain a digital twin dataset from the aspect agent 714. The digital twin generator 716 may be configured to generate a digital twin, as described, for example, in relation to Figures 7A and 10. The digital twin may include a decentralized digital twin identifier and a digital twin dataset generated by the aspect agent 714. The digital twin generator 716 may be configured to provide the generated digital twin to the digital twin provider 722.

[0201] The aspect agent 714 may be configured to retrieve or receive a digital twin template generated from the template DB 506 based on the data contained in the received request, as described in relation to Figure 7A. The template DB 506 may store digital twin templates. The digital twin template may be generated by the device 116 for generating DT templates, as described in relation to Figure 5. The digital twin template may be generated according to the method described in relation to Figure 6A or Figure 6B. The aspect agent 714 may be configured to receive or retrieve at least one aspect model from the model DB 418 connected to the aspect agent 714 via a communication interface, based on each digital twin template (not shown). The model DB 418 may be part of the decentralized network 514, as described in relation to Figure 5.

[0202] The aspect agent 714 may be configured to generate a digital twin dataset for each acquired or received aspect model (see, for example, Figure 9). The aspect agent 714 may be configured to store the generated digital twin dataset in the DT storage 720 (see Figure 7A). The aspect agent 714 may be configured to provide at least a portion of the generated digital twin dataset to the digital twin generator 716.

[0203] The decentralized ID generator 718 may be configured to generate decentralized digital twin identifiers associated with the collected data and, optionally, with data owners such as data owners of the data associated with the product. The decentralized ID generator 718 may be configured to generate decentralized identifiers including, or associated with, further identifiers such as dataset identifiers. For example, the decentralized ID generator 718 may be configured to generate digital twin identifiers such as DIDs or UUIDs. The decentralized ID generator 718 may be configured to generate digital twin data identifiers such as DIDs and / or UUIDs. The decentralized ID generator 718 may include a component configured to generate decentralized identifiers (DIDs). The decentralized ID generator 718 may include a component configured to generate universally unique identifiers (UUIDs). The decentralized identifiers generated by the decentralized ID generator 718 may be one or more DIDs and / or UUIDs. One or more DIDs and / or UUIDs may be associated with a digital twin and / or digital twin dataset. One or more DIDs and / or UUIDs may be further associated with a product. For example, a decentralized digital twin identifier may include a digital twin identifier associated with the digital twin, and one or more digital twin data identifiers associated with the digital twin data. The decentralized identifier may further include a product identifier associated with a chemical product. The decentralized ID generator 718 may be a central or decentralized node, or a computing node, as described in relation to Figure 7A. The decentralized digital twin identifier may be requested by the digital twin generator 716. The decentralized digital twin identifier may be requested by the decentralized ID provider 806 (not shown) after receiving a request from the digital twin generator 716. The decentralized ID generator 718 may be part of the device 702. The decentralized ID generator 718 may be communicatively coupled to the device 702 (not shown).The decentralized identifier generator 718 may be configured to provide the generated decentralized digital twin identifiers to the decentralized ID provider 806. The decentralized ID generator 718 and the decentralized ID provider 806 may be separate devices, as shown in Figure 8. The decentralized ID generator 718 and the decentralized ID provider 806 may be contained within a single device configured to generate decentralized identifiers and provide the generated decentralized identifiers, for example, as shown in Figure 7A.

[0204] The decentralized ID provider 806 may be configured to provide the received decentralized digital twin identifier to a requester 804 configured to associate the received decentralized digital twin identifier with a product. For this purpose, the requester 804 may include an ID assigner (see, for example, Figures 1B, 1C, and 2). The decentralized ID provider 806 may be configured to provide the received decentralized digital twin identifier to an ID assigner (not shown) configured to associate the received decentralized identifier with a product. Such association may include encoding the decentralized identifier into a code such as a barcode, QR code, embossed code, or optical holographic identifier, and providing a code generated for labeling the product. In this way, a physical identifier may be provided that associates the physical entity of the product with the decentralized digital twin identifier, and therefore the digital twin with the physical entity of the product.

[0205] The digital twin provider 722 may be configured to provide the digital twin or a portion thereof for access by the decentralized data consumption network node 808. The decentralized data consumption network node 808 may be part of the decentralized network 514. The digital twin or a portion thereof may be accessed by the decentralized data consumption network node 808 using at least a decentralized digital twin identifier. Access to the digital twin or a portion thereof may be controlled by the digital twin provider 722 (see, for example, Figure 15). The digital twin provider 722 may be associated with the data owner of the digital twin dataset. The digital twin provider 722 may be associated with the data owner of the digital twin. The digital twin provider 722 may be associated with the operator of production 104. The digital twin provider 722 may be a decentralized data provision network node.

[0206] Figure 9 shows an exemplary apparatus for generating a digital twin of a product's physical entity using a digital twin template that defines three different aspect models. The digital twin template used to generate the digital twin can more or less define an aspect model. The product may be a chemical product. This apparatus may correspond to the apparatus 702 described in relation to Figure 4A. This apparatus may be included in the operating system 108 of production 104 that produces product 106 from one or more input materials 102 (see, for example, Figures 1A and 1B). This apparatus may be communicatively coupled to the operating system 108 of production 104 that produces product 106 from one or more input materials 102 (see, for example, Figure 1C). This apparatus may be configured to generate a digital twin 912, as described, for example, in relation to Figures 7A and 10. The apparatus in Figure 9 may be connected to the data source layer 704, as described in relation to Figure 7A.

[0207] The apparatus may include a data acquisition unit 712 configured to collect data associated with the product generated from the data source layer 704 by the digital twin, as described, for example, in relation to Figures 7A and 10. The collected data may be provided to a digital twin generator 716. The collected data may be acquired by the digital twin generator 716.

[0208] The digital twin generator 716 may be configured to request a decentralized digital twin identifier from a decentralized ID generator 718, for example, as described in relation to Figures 7A to 10. The digital twin generator 716 may be configured to provide data collected by the data acquisition unit 712 to the aspect agent 714. The digital twin generator 716 may be configured to acquire or receive digital twin datasets generated by the aspect agent 714. The digital twin generator 716 may be configured to acquire or receive digital twin datasets from the DT storage 720. The digital twin generator 716 may be configured to generate a digital twin of a product from the received decentralized digital twin identifier and at least a portion of the received or acquired digital twin datasets, for example, as described in relation to Figures 7A and 10. For example, the digital twin generator 716 may generate a digital twin 912 by associating the received decentralized digital twin identifier with each of the generated digital twin datasets 906, 908, and 910, respectively. Therefore, the decentralized identifier enables the identification of all digital twin datasets contained in the product's digital twin 912. Each digital twin dataset can be uniquely identified by a digital twin dataset identifier combined with a decentralized digital twin identifier, as described in relation to Figure 7A. The digital twin generator 716 may be configured to generate access data, for example, as described in relation to Figure 7A. The digital twin generator 716 may be configured to generate a DID document containing access data such as a decentralized digital twin identifier (e.g., DID) received from the decentralized ID generator 718, as well as a chemical digital twin dataset identifier and their respective digital representations pointing to the digital twin datasets. The digital twin generator 716 may be configured to store the generated digital twin 912 in the DT storage 720, as described in relation to Figures 7A and 10.The digital twin generator 716 may be configured to provide the generated digital twin 912 to the digital twin provider 722, as described in relation to Figures 7A and 10 (not shown).

[0209] The aspect agent 714 may be configured to acquire or receive a digital twin template (DT template 902). The digital twin template may be generated by the apparatus 116 for generating a DT template, as described in relation to Figure 5. The digital twin template may be generated by the method described in relation to Figures 4A, 4B, 6A, and 6B. The digital twin template may define one or more aspect models. In this embodiment, the DT template 902 defines three different aspect models. In another embodiment (not shown), the DT template 902 may define more or less aspect models. The DT template 902 may include three aspect models. The DT template 902 may include digital representations pointing to each aspect model. The digital representations may be used by the aspect agent 714 to acquire or receive each aspect model from the model DB 418, for example, as described in relation to Figure 5. The aspect agent 714 may be configured to generate a digital twin dataset from the collected data received from the data acquisition unit 712 according to each aspect model included in the DT template 902. Each digital twin dataset 906, 908, and 910 may be associated with the respective aspect model used in its generation. The aspect agent 714 may be configured to store the generated digital twin datasets and related data such as digital twin dataset identifiers in the DT storage 720 (see Figure 7A). The aspect agent 714 may be configured to provide at least a portion of the generated digital twin datasets to the digital twin generator 716.

[0210] The decentralized ID generator 718 may be configured to generate and provide decentralized digital twin identifiers to the digital twin generator 716, as described in relation to Figures 7A and 10. The decentralized ID generator 718 may be a central node or a decentralized node, and upon receiving a request from the digital twin generator 716 (see, for example, Figure 7A), it may generate decentralized digital twin identifiers. The decentralized ID generator 718 may be configured to generate access data, such as digital twin dataset identifiers.

[0211] Figure 10 shows a flowchart of a computer implementation method for generating a digital twin of a physical entity of a chemical product according to an exemplary embodiment of the present disclosure. The product may be a chemical product. The digital twin may be generated for a product 106 produced by a production 104 from one or more input materials 102. Production 104 may be a chemical production, as described in relation to Figures 1A to 2. The digital twin may be generated by the operating system 108 of production 104. The operating system 108 may include, for example, a device 702 for generating the digital twin, as described in relation to Figures 7A to 8. A request to generate a digital twin may be manually triggered by a user via a user interface, for example using an I / O device 510 (see Figure 7A). A request to generate a digital twin may be automatically triggered when packaging of the produced product is detected, for example, as described in relation to Figures 2 and 8.

[0212] In block 1002, a request to generate a digital twin of a product may be received. The request may include data related to the product. The request may be generated manually or automatically, as described above. The data related to the product may include product identifiers such as batch number, lot number, product name, and / or product ID.

[0213] In decision block 1004, it can be determined whether a digital twin of the product already exists. Therefore, it can be determined whether a digital twin has already been generated and stored, for example, in the DT storage 720. This determination may be based on product-related data included in the received request, such as a product identifier. For example, a product identifier may be used to determine whether a digital twin associated with the above product identifier already exists, for example, whether it is already stored in the DT storage 720. If a digital twin of the product already exists, the method may proceed to decision block 1006. Otherwise, the method may proceed to block 1010 as described below.

[0214] In decision block 1006, it may be determined whether the existing digital twin should be updated. The determination may be based on the data contained in the received request. For example, the request may contain data indicating that the digital twin should be updated. If the existing digital twin should be updated, the method may proceed to block 1008. Otherwise, the method may terminate or proceed to block 1002.

[0215] In block 1008, the digital twin may be updated. Updating may include performing the actions described in blocks 1010, 1014, and 1016 below, for example, generating additional digital twin datasets. Updating may include modifying the data contained in the existing digital twin or existing digital twin dataset, or adding data to the existing digital twin or existing digital twin dataset.

[0216] In block 1010, data associated with a product may be collected from one or more distributed data sources based on data related to the product included in the request received in block 1002. The collected data may include at least one measured and / or determined physical and / or chemical property of the product. The data may be collected from one or more distributed data sources, for example, distributed data sources of data source layer 704, as described in relation to Figures 7A to 8. The data may be collected directly from one or more distributed data sources of data source layer 704, for example, as described in relation to Figure 4A. The data may be consumed with data from service layer 724, for example, as described in relation to Figure 7B.

[0217] In block 1012, the collected data and optionally a decentralized digital twin identifier associated with the data owner may be provided. The decentralized digital twin identifier may be provided in response to a request generated, for example, by a digital twin generator 716 (see Figures 7A and 8). The request may include a data owner identifier and / or a product identifier. The data owner may be the data owner of the collected data and / or data contained in a distributed data source. The data owner may be a product producer. The data owner may be any of the data owners described above. The decentralized digital twin identifier may be requested from a central or decentralized node, for example, as described in relation to Figure 7A. The decentralized identifier may be one or more DIDs and / or UUIDs, for example, as described in relation to Figure 7A. Block 1012 may also be executed after either block 1014 or block 1016.

[0218] In block 1014, a digital twin template to be applied to the collected data may be provided. The digital twin template may be generated by the apparatus described in relation to Figure 5. The digital twin template may be generated by the method described in relation to any one of Figures 4A, 4B, 6A, and 6B. The digital twin template may be provided based on the data contained in the request received in block 1002, for example, based on a product identifier. The digital twin template may be stored in a database such as template DB 506 and provided based on the data contained in the request received.

[0219] In block 1016, the aspect model defined in the provided digital twin template can be applied to the collected data. The aspect model can be defined in the digital twin template. The aspect model can be retrieved or received from a database such as model DB418 based on the digital representation contained in the digital twin template (see also Figure 9). By applying the aspect model defined in the digital twin template to the collected data, a digital twin dataset can be generated as a result. The digital twin dataset can be generated for each aspect model defined in the digital twin template, as described, for example, in relation to Figures 7A and 8.

[0220] In block 1018, a digital twin may be generated. The digital twin may include a decentralized digital twin identifier provided in block 1012 and a digital twin dataset generated in block 1016. The decentralized digital twin identifier may be linked to at least a portion of the digital twin dataset generated in block 1016 to generate a digital twin (see, for example, Figure 9). The generated digital twin may include a digital twin dataset identifier. The digital twin dataset identifier may be generated by a digital twin generator 716 (see, for example, Figures 7A and 8). The digital twin may further include a product identifier. The product identifier may be a product identifier included in an received request. The generated digital twin may be stored in DT storage 720 as described in relation to Figure 7A. Storing the digital twin in DT storage 720 may improve security regarding access to the digital twin, as appropriate authentication and authorization schemes may be implemented between DT storage 720 and a digital twin provider 722 that provides the digital twin or a portion thereof to authorized decentralized data consumption network nodes. The generated digital twin and / or the digital twin dataset contained therein may be provided to the digital twin provider 722, as described in relation to Figures 7A and 8.

[0221] In block 1020, the generated digital twin may be provided to decentralized data consumption network nodes under the control of the digital twin provider 722, and this block is generally optional. The digital twin may be provided to decentralized data consumption network nodes as described in relation to Figure 15.

[0222] In block 1022, a physical identifier may be assigned to a decentralized identifier included in the digital twin, although this block is generally optional. This block may be performed, for example, when a decentralized digital twin identifier included in the digital twin is used to generate a digital access element (see, for example, Figures 11 and 12). This makes it possible to link the decentralized digital twin identifier, and therefore the digital twin, to the physical entity of the product. Assigning a decentralized digital twin identifier to a physical identifier may include generating a physical identifier that embeds the decentralized digital twin identifier. The physical identifier may be generated by an ID assigner, as described, for example in relation to Figure 5, and may be attached to a chemical product, for example, using a labeling device.

[0223] Figure 11 shows a flowchart of a method for generating a digital access element associated with a digital twin of a product, according to an exemplary embodiment of the present disclosure. Since the digital twin is associated with the physical entity of the product, the digital access element is also associated with the physical entity of the product, at least indirectly. The product may be a chemical product. The digital access element may enable indirect access to the digital twin or a portion thereof, i.e., access to the digital twin via the digital access element. Access to the digital access element itself may remain unrestricted while still allowing controlled access to the digital twin or a portion thereof. The product 106 may be produced by production 104 from one or more input materials 102. Production 104 may be a chemical production as described in relation to Figures 1A to 2. Production may include, or be associated with, an operating system 108. The operating system 108 may include, for example, a device for generating a digital twin, as described in relation to Figures 7A to 8. The operating system 108 may include, for example, a device for generating a digital access element, as described in relation to Figure 12. The operating system 108 may be communicatively coupled to a device for generating a digital twin and / or generating a digital access element. The digital access element may correspond to a DID document associated with the DID used to generate the digital twin. Such a DID document may include the DID contained in the generated digital twin, a digital twin dataset identifier associated with the digital twin dataset contained in the digital twin, and access data. The access data may include a digital representation pointing to the digital twin dataset, as described with respect to Figure 7A. The digital access element may correspond to a DID document associated with a further decentralized identifier. The digital access element may correspond to a data structure including a decentralized digital twin identifier, a further identifier such as a digital twin dataset identifier, and access data, as shown, for example, in Figure 13.

[0224] In block 1102, a digital twin of the physical entity of the product may be generated. The digital twin may be generated by the method described in relation to Figure 10. Block 1102 may be performed using equipment for generating digital twins, as described in relation to Figures 7A to 8. The generated digital twin may be stored in a data storage medium such as DT storage 720.

[0225] In block 1104, a request may be received to provide a decentralized access element identifier associated with the digital twin. The decentralized identifier may be further associated with a data owner. The data owner may be the data owner of the digital twin dataset included in the digital twin, as described above. The data owner may be the product producer, as described above. The decentralized access element identifier may be a DID. The decentralized access element identifier may be a UUID. The request may be generated by a requester, for example, as described in relation to Figure 12. The request may include an owner identifier and / or a product identifier, as described above.

[0226] In decision block 1106, it may be determined whether further decentralized identifiers should be provided. The determination may be based on data such as decentralized digital twin identifiers included in the digital twin generated in block 1102. For example, if the decentralized digital twin identifier included in the digital twin is a DID, the method may proceed to block 1110. The use of decentralized digital twins makes it possible to avoid the generation of further decentralized identifiers, and thus enables more efficient generation of digital access elements. The determination may be based on the programming of the routine that implements the method. For example, the routine may be programmed to provide further decentralized identifiers. The use of further decentralized identifiers makes it possible to use different identifier schemes such as UUID and DID. This makes it possible to store access data necessary to access the digital twin or a part thereof decentralizedly using DID documents (see, for example, Figure 13). If further decentralized identifiers should be provided, the method proceeds to block 1108. Otherwise, the method proceeds to block 1110.

[0227] In block 1108, further decentralized identifiers may be provided. This may include generating further decentralized identifiers and providing the generated further decentralized identifiers, as described, for example, in relation to Figure 12. Further decentralized identifiers may be assigned to decentralized digital twin identifiers. This makes it possible to link the digital twin with digital access elements, and thus to access the digital twin or a portion thereof using the digital access elements. Further decentralized identifiers may be DIDs. Further decentralized identifiers may be assigned to decentralized digital twin identifiers. This may make it possible to link the digital twin with each digital access element.

[0228] In block 1110, the decentralized digital twin identifier included in the digital twin generated in block 1102 may be retrieved. The retrieved decentralized digital twin identifier may then be provided. For example, the decentralized digital twin identifier included in the generated digital twin may be retrieved from DT storage 720. Each digital twin may be identified using the product identifier included in the request received in block 1104. For example, the product identifier may be used to retrieve the decentralized digital twin identifier included in the digital twin associated with the above product identifier.

[0229] In block 1112, a digital access element associated with the manufactured product may be generated. The generated digital access element may include a decentralized digital twin identifier or a further decentralized identifier contained in the digital twin, and access data. If the decentralized digital twin identifier is a DID, the generated digital access element may correspond to a DID document associated with the DID. Access data may refer to any data for accessing the digital twin or a part thereof, as described above. For example, access data may include endpoints for data exchange or sharing (resource endpoints) or endpoints for service interaction (service endpoints) that are uniquely identified via a communication protocol. Endpoints may be represented by a digital twin provider 722 (see, for example, Figures 8 and 12). Access data may include multiple digital representations, each digital representation referring to a different digital twin dataset contained in the digital twin. Each decentralized identifier and access data may be associated with one another. For example, the decentralized identifier that serves as the basis for generating the digital access element may be associated with authentication information used as the access data that serves as the basis for generating the digital access element.

[0230] In block 1114, the physical identifier associated with the product may be assigned to a decentralized digital twin identifier / further decentralized identifier contained in the digital access element generated in block 1112, and this block is generally optional. This makes it possible to link the digital twin, which is associated with the digital access element and therefore indirectly associated with the decentralized digital twin identifier or further decentralized identifier, to the physical entity of the chemical product. The physical identifier may correspond to a code such as a barcode, QR code, embossed code, optical holographic code such as zero-order diffraction microstructure, or a tag such as an RFID tag. The physical identifier may be produced by a labeling machine, for example, as described in relation to Figure 12.

[0231] In block 1116, the generated digital access element may be provided for access to the digital twin or a portion thereof by a decentralized data consumption network node, and this block is generally optional. The decentralized data consumption network node may be part of a decentralized network. For example, the digital access element may be provided to a passport registry accessible by the decentralized data consumption network node (see, for example, Figure 12). The decentralized data consumption network node may use the data contained in the digital access element, such as the decentralized access element identifier and access data, to obtain the digital twin or a portion thereof associated with the decentralized access element identifier from a decentralized data provision network node, such as a digital twin provider 722, as described, for example, in relation to Figure 15. The digital twin provider 722 may authorize access to the digital twin based on the decentralized digital twin identifier associated with the digital access element. The digital twin provider 722 may authorize access to the digital twin based on the decentralized participant identifier associated with the decentralized data consumption network node requesting access to the digital twin or a portion thereof.

[0232] The generated digital access elements enable simplified, customizable data sharing or exchange of digital twin data associated with manufactured products among stakeholders in the product ecosystem.

[0233] Figure 12 shows an exemplary system and associated method for generating digital access elements associated with a digital twin of a product produced by a production, and for providing access to the generated digital twin. The product may be a chemical product. The apparatus for generating the digital access elements of the digital twin associated with the product may be included in the operating system 108 of production 104 (see, for example, Figures 1A and 1B). Production 104 may be a chemical production. The apparatus for generating the digital access elements of the digital twin associated with the product may be communicatively coupled to the operating system 108 of production 104 (see, for example, Figure 1C). The digital twin may be generated as described in relation to Figures 7A to 8.

[0234] Production 104 can produce at least one product 106 from one or more input materials 102. Input materials may be provided to production 104, for example, as described in relation to Figures 1B and 1C. Input materials may enter the system boundary of production 104 at an entry point such as a production plant or material storage facility associated with production 104. Input materials may be used in production 104 to produce one or more products 106 from the input materials, for example, as described in relation to Figures 1B to 2. The operating system 108 of production 104 may monitor and / or control production 104 based on the operating parameters of different processes, as described in relation to Figure 8.

[0235] The produced product 106 may be delivered at one or more exit points of production 104. Product 106 may leave the system boundary 802 of production 104. When product 106 is produced, or when product 106 leaves production 104, a digital access element may be generated. The digital access element may be generated by a device 1202 for generating digital access elements. The device 1202 for generating digital access elements may be configured to generate digital access elements. The device 1202 may be configured to receive requests to provide decentralized access element identifiers associated with a digital twin. The device 1202 may be configured to generate digital access elements in response to received requests. In this embodiment, the device 1202 may include a device for generating a digital twin, such as the device 702 described in relation to Figures 7A and 7B. In another embodiment (not shown), the device 1202 may be communicably coupled to a device for generating a digital twin, such as the device 702 described in relation to Figures 7A and 7B.

[0236] In this embodiment, the device 1202 may further include a decentralized ID generator 718. In another embodiment (not shown), the decentralized ID generator 718 may be part of the device 702, and for example, the device 1202 may not include a further decentralized ID generator 718. Instead, the decentralized ID generator 718 of the device 702 may be configured to provide decentralized access element identifiers (see, for example, Figure 7A).

[0237] In this embodiment, the device 1202 may further include a decentralized identity provider 806. In another embodiment (not shown), the decentralized identity provider 806 may be part of the device 702, and for example, the device 1202 may not include a further decentralized identity provider 806. Instead, the decentralized identity provider 806 of the device 702 may be configured to provide decentralized access element identifiers (see, for example, Figure 7A). Although the decentralized identity generator 718 and the decentralized identity provider 806 are shown as separate units in Figure 12, their functions may be combined within a single unit so that the device 1202 includes a decentralized identity providing unit configured to perform the functions of the decentralized identity generator 718 and the decentralized identity provider 806.

[0238] Requester 1204 may be configured to generate requests for decentralized access element identifiers. These requests may be triggered by a labeling system such as a QR code generator. The requests may include owner identifiers and / or product identifiers, as described above. Requests providing decentralized access element identifiers may be provided to a decentralized ID generator 718 configured to provide decentralized access element identifiers, as described, for example, in relation to Figure 11. The decentralized ID generator 718 may be configured to retrieve decentralized digital twin identifiers contained in a digital twin associated with a chemical product, as described, for example, in relation to Figure 11. For example, the decentralized ID generator 718 may have access to DT storage 720 and retrieve decentralized digital twin identifiers based on product identifiers contained in the received request. The decentralized ID generator 718 may be configured to generate further decentralized identifiers. The decentralized ID generator 718 may provide the generated additional decentralized identifiers or acquired decentralized digital twin identifiers to the decentralized ID provider 806.

[0239] The decentralized ID provider 806 may provide the requested 1204 with the acquired decentralized digital twin identifier or any further decentralized identifier generated. The decentralized ID provider 806 may associate the further decentralized identifier with the decentralized digital twin identifier. The requested 1204 may be configured to associate the received decentralized digital twin identifier / further decentralized identifier with a manufactured product. Thus, the requested 1204 may include an ID assigner configured to assign the decentralized digital twin identifier / further decentralized identifier to a physical identifier. Such association may include encoding the decentralized identifier into a code such as a barcode, QR code, embossed code, optical holographic code, or tag such as an RFID tag, and providing the code or tag for labeling the product. Thus, a physical identifier may be provided that associates the physical entity of a product with a decentralized digital twin identifier / further decentralized identifier received from a decentralized identity provider 806. Because the physical identifier is associated with the product and its virtual digital access elements and digital twin, the product may be provided in association with the digital access elements, thereby enabling access to the digital twin or a portion thereof associated with the product. Therefore, the product associated with the physical identifier may be provided physically, and at least one digital access element and a digital twin or a portion thereof associated with the physical identifier may be provided virtually.

[0240] The decentralized identity provider 806 may provide a decentralized digital twin identifier / further decentralized identifier to a digital access element generator 1206 configured to generate digital access elements based on the decentralized digital twin identifier / further decentralized identifier and access data received from the decentralized identity provider 806. The digital access element generator 1206 may generate digital access elements as described, for example, in relation to Figure 11. The generated digital access elements may include a decentralized access element decentralized identifier and access data. The decentralized access element identifier may correspond to or be associated with a decentralized digital twin identifier contained in the digital twin. This makes it possible to link the digital twin to the digital access element, and thus make it possible to use the digital access element as a means of communication to communicate digital assets, such as a digital twin or a portion thereof associated with the physical entity of the product, to the product consumer. The access data may include a digital representation that points to the digital twin or a portion thereof. The above expression may include the endpoint address of the decentralized data delivery network node associated with the digital twin (i.e., the digital twin provider 722 associated with each DT storage 720). By using the endpoint address of the decentralized data delivery network node, it is possible to avoid disclosing the internal endpoint address to the DT storage 720, thus improving security and preventing unintended access or leakage of the digital twin or any part thereof. The digital access element may include, or be associated with, one or more authentication mechanisms associated with the decentralized access element identifier and / or the access data. The authentication mechanism may be used, for example, as described with respect to Figure 15. The digital access element may be associated with one or more authentication mechanisms associated with the decentralized access element identifier and / or the access data. The authorization mechanism may be used, for example, as described with respect to Figure 15.

[0241] The generated digital access elements can be provided to the DT storage 720. This makes it possible to store the generated digital access elements, thus avoiding their regeneration.

[0242] The generated digital access elements may be provided to a digital twin provider 722 (not shown). The generated digital access elements may also be provided to an access element registry 1208. The access element registry 1208 may be part of a decentralized network 514. The access element registry 1208 may be configured to store digital access elements and may function as a central or decentralized repository for existing digital access elements. For example, the access element registry 1208 may store decentralized access element identifiers and associated access data. The access element registry 1208 may be publicly available and thus provide transparency about existing digital access elements and the associated digital twins of products. However, access to the digital twin or a portion thereof associated with the digital access elements may be controlled by the data owner of the digital access element, for example, by using decentralized data provision network nodes that implement appropriate authentication and authorization schemes. This retrains data owners in controlling data access and use, while providing transparency about available digital twins and associated digital twin datasets.

[0243] The decentralized data consumption network node 808 can access the access element registry 1208 and retrieve access data based on decentralized access element identifiers, as illustrated, for example, in relation to Figure 15. The decentralized data consumption network node 808 may be part of the decentralized network 514. The decentralized data consumption network node 808 may be associated with product consumers, as illustrated, for example, in relation to Figure 15. This enables controlled and secure transfer or access to digital twins and parts thereof.

[0244] The digital twin provider 722 may be configured to provide the digital twin or a portion thereof for access by the decentralized data consumption network node 808. The digital twin provider 722 may be configured to provide the digital twin or a portion thereof based on a decentralized digital twin identifier and access data optionally received from the decentralized data consumption network node 808, as described, for example, in relation to Figure 15. The digital twin provider 722 may control access to the digital twin or a portion thereof by the decentralized data consumption network node 808. The digital twin provider 722 may be a decentralized data provision network node associated with production 104. The digital twin provider 722 may be associated with, or under the control of, the data owner of the digital twin. Digital access elements may be used to control access to the digital twin or a portion thereof, as described, for example, in relation to Figure 15.

[0245] The described system and related methods enable the generation of digital access elements associated with a product's digital twin. These generated digital access elements facilitate simplified, customizable data sharing or exchange of digital twin data associated with the manufactured product among stakeholders in the product ecosystem.

[0246] Figure 13 shows an example of decentralized identifier-based owner data 1302, decentralized identifier-based digital access element data 1304, and a decentralized identity manager 1306.

[0247] A decentralized identifier may be a decentralized ID (DID). In this case, a decentralized identifier-based digital access element may be a DID document 1304 associated with the DID. In addition to the DID document 1304 acting as a digital access element, Figure 13 shows a DID owner data element 1302 that includes decentralized identifier-based owner data. Generally, decentralized identifier-based owner data may include a decentralized identifier associated with a subject such as a digital twin dataset and may include one or more authentication mechanisms. Decentralized identifier-based owner data 1302 may include owner data that is electronically owned and controlled by the DID owner. In this regard, electronically owned may mean data stored in an owner repository or wallet. Such data may be securely stored and / or managed on an organized server or client device. Decentralized identifier-based owner data 1302 may include the DID, private key, and public key. A DID owner may own and control the DID, the private key and public key pair associated with the DID, which represents the identity associated with the DID subject. A DID can be understood as an identifier and the authentication information associated with or uniquely linked to that identifier.

[0248] A DID subject may be a raw material, basic substance, chemical product, component, assembly, or final product. A DID subject may be a machine, system, or device used in the production of a raw material, basic substance, chemical product, intermediate product, component, assembly, or final product, or a collection of such machines, devices, and / or systems. A DID owner may be a supplier, such as a chemical manufacturer that produces a chemical, or a supply chain participant. A DID owner may be an upstream participant in a chemical manufacturer's supply chain, such as a supplier that provides raw chemicals or precursors for producing a chemical product. A DID owner may be a downstream participant in a chemical manufacturer's supply chain, such as a customer that consumes a chemical to produce an intermediate product, component, component assembly, or final product. A DID owner may be any participant in the supply chain, including raw chemical suppliers, intermediate chemical manufacturers, intermediate component manufacturers, component manufacturers, component assembly manufacturers, or final product manufacturers.

[0249] DID can be any identifier associated with the DID subject and / or DID owner. Preferably, the identifier is unique to the DID subject and / or DID owner. The identifier may be unique at least to the extent that the DID is expected to be unique in use. The identifier may be a locally or globally unique identifier of any participant in the supply chain, including raw materials, precursors, basic substances, chemical products, intermediate products, components, component assemblies, finished products, or sets thereof; machines, systems, or devices used in the production of raw materials, basic substances, chemical products, intermediate products, components, component assemblies, or finished products, or sets thereof; chemical manufacturers producing chemicals, upstream participants in the supply chain of chemical manufacturers, downstream participants in the supply chain of chemical manufacturers, or sets thereof; or raw material chemical product suppliers, intermediate chemical product manufacturers, intermediate parts manufacturers, component manufacturers, component assembly manufacturers, or finished product manufacturers, or sets thereof.

[0250] A DID can be any identifier associated with a DID subject and / or DID owner. Preferably, a DID is unique to the DID subject and / or DID owner. A DID may be unique to at least the extent to which it is expected to be unique when used. A DID may be a locally or globally unique identifier for any of the possible DID subjects described above. A DID may also be a Unified Resource Identifier (URI), such as a Unified Resource Location Specifier (URL). Furthermore, a DID may be an Internationalized Resource Identifier (IRI). A DID may be a Unified Resource Identifier (URI), such as a Unified Resource Location Specifier (URL). A DID may be an Internationalized Resource Identifier (IRI). For enhanced security, a DID may be a random string of numbers and letters. In one embodiment, a DID may be a sequence of 128 characters and numbers following the format did:method name:method-specific did, such as "did:example:ebfeb1f712ebc6f1c276e12ec21". DID can be a decentralized identity that is under the control of the DID owner, independent of a centralized third-party management system.

[0251] A digital access element as a DID document 1304 may be associated with a DID, i.e., a DID contained in decentralized identifier-based owner data 1302. Thus, a digital access element may include a reference to a DID associated with a DID subject described by the DID document 1304. The DID document 1304 may also include authentication information, such as a public key. The public key may be used by a third-party entity authorized by the DID owner / subject to access information and data owned by the DID owner / subject. The public key may also be used to verify that the DID owner actually owns or controls the DID. The DID document may include authentication and authorization information, for example, to authorize a third-party entity to read the DID document or a portion of the DID document, without, for example, granting the third party the right to prove ownership of the DID.

[0252] The digital access element 1304 may further include one or more representations that are digitally linked to the digital twin dataset, for example, by a service endpoint. A service endpoint may include a network address on which a service operates on behalf of the DID owner. In particular, a service endpoint may refer to a service, such as a decentralized data provision network node of the DID owner, that provides access to the digital twin or a portion thereof. Such a service may include a service that reads or analyzes product data contained in the digital twin or a portion thereof. Product data may include product declaration data, product safety data, certification of analytical data, emissions data, product carbon footprint data, product environmental footprint data, product specification data, product information, technology application data, production data, or a combination thereof.

[0253] The digital access element 1304 may include various other information, such as metadata specifying when the digital access element was created, when the last modification was made, and / or when it expires.

[0254] The DID and digital access element 1304 may be associated with a data registry node such as a decentralized data service system or decentralized data service system 1306, for example, a distributed ledger or blockchain or a decentralized file system. The distributed ledger or blockchain may be used to store a representation of the DID that points to the digital access element 1304. The representation of the DID may be stored in the distributed computing nodes of the distributed ledger or blockchain 1006. For example, a DID hash may be stored in multiple computing nodes of the distributed ledger and may point to the location of the digital access element 1304. In some embodiments, the digital access element 1304 may be stored on the distributed ledger 1306. Each computing node may store a copy of the distributed ledger 1306. In this way, each DID hash can be stored redundantly, thereby increasing data security. The distributed ledger 1306 may contain DIDs associated with multiple different digital access elements 1004.

[0255] In some embodiments, the digital access element 1304 may be stored in the distributed ledger 1306, i.e., in addition to or alternative to the associated DID representation stored in the distributed ledger 1306. In other embodiments, the digital access element 1004 may be stored in data storage associated with a distributed ledger, blockchain, or decentralized file system (not shown).

[0256] A distributed ledger or blockchain 1306 can be any decentralized distributed network containing various computing nodes that communicate with one another. For example, a distributed ledger 1306 may include a first distributed computing node, a second distributed computing node, a third distributed computing node, and any number of additional distributed computing nodes (not shown). A distributed ledger or blockchain 1306 may include known technology stacks such as Bitcoin (see, for example, the Bitcoin documentation published on November 11, 2022 at https: / / en.bitcoin.it / wiki / Protocol_documentation), Ethereum (see, for example, the Ethereum documentation published on August 15, 2022 at https: / / ethereum.org / en / developers / docs / ), Solana (see, for example, the Solana documentation published on November 11, 2022 at https: / / spl.solana.com / ), Polygon (see, for example, the Polygon documentation published on November 11, 2022 at https: / / wiki.polygon.technology / ), or other embodiments with a different degree of data transactions performed on a distributed ledger. The description of exemplary frameworks is for illustrative purposes only and should not be considered limiting.

[0257] Figure 14A shows a first example of the linkage between a dataset of a digital twin and a digital access element via a decentralized digital twin identifier. The digital twin 1402 can be generated as described in relation to FIGS. 7A and 8 using a digital twin template. The digital twin 1402 can be stored in the DT storage 720. The digital access element 1410 associated with the physical entity of the product can be generated as described in FIGS. 11 and 12. The datasets 1404, 1406 associated with the digital twin 1402 are respectively assigned to the decentralized digital twin identifier 1408. Thus, by using the decentralized digital twin identifier 1408, it becomes possible to identify all existing datasets included in the digital twin 1402. The decentralized digital twin identifier 1408 may include further identifiers such as dataset identifiers of the datasets 1404, 1406. Thereby, by using the decentralized digital twin identifier 1408 and the respective dataset identifiers, it becomes possible to uniquely identify the datasets included in the digital twin.

[0258] The digital access element 1410 may include a decentralized passport identifier 1412. The decentralized passport identifier 1412 may be a decentralized identifier linked to the decentralized digital twin identifier 1408 included in the digital twin. The decentralized passport identifier 1412 may correspond to the decentralized digital twin identifier 1408 included in the digital twin 1402. The latter avoids the generation of a new decentralized identifier and the linking of the newly generated decentralized identifier to the decentralized digital twin identifier included in the digital twin.

[0259] The digital access element may further include access data 1414. The access data 1414 may include a digital representation that directly or indirectly refers to a storage structure (e.g., data sets 1404, 1406) that stores a digital twin or a part thereof, such as DT storage 720 (not shown). The access data 1414 may include a digital representation that refers to a non-central data providing network node associated with the DT storage 720 (not shown).

[0260] The digital access element 1410 is linked to the digital twin 1402 via the decentralized passport identifier 1412, and thus also to the data sets included in the digital twin. Therefore, as described in connection with FIG. 15, it may be possible to obtain the digital twin or a part thereof (e.g., data sets 1404, 1406) using the decentralized passport identifier 1412 and the access data 1414 included in the digital access element 1410.

[0261] FIG. 14B shows a second example of the linkage between the digital twin 1402, the associated data sets 1404, 1406, and the digital access elements 1416, 1422 via the decentralized digital twin identifier 1408 and the decentralized passport identifiers 1420, 1426. The digital twin 1402 may be generated as described in connection with FIGS. 7A - 8 using a digital twin template. The digital access elements 1416, 1422 associated with the physical entity of the product may be generated as described in FIGS. 11 and 12. The data sets 1404, 1406 associated with the digital twin 1402 are assigned to the decentralized digital twin identifier 1408. Therefore, by using the decentralized digital twin identifier 1408, it becomes possible to identify all existing data sets included in the digital twin 1402.

[0262] In this example, a first digital access element 1416 may be generated for dataset 1 1404, and a second digital access element 1422 may be generated for dataset 2 1406. Digital access elements may be generated for each dataset, or for at least a portion of the datasets included in the digital twin. Each digital access element may be linked to its respective dataset via decentralized digital twin identifier 1408 and decentralized passport identifiers 1420, 1426. Each digital access element 1416, 1422 may contain access data 1414, 1424. The access data 1414, 1424 may include digital representations pointing to product datasets, as described in relation to Figure 14A.

[0263] Figures 14A and 14B show only two exemplary embodiments, and any number of digital access elements and any number of datasets in the digital twin are possible. For example, a first digital access element may be generated for a first number of datasets, and a second digital access element may be generated for a second number of datasets. The number of datasets may include one or more datasets.

[0264] Figure 15 shows a schematic diagram of using a digital access element to provide access by a decentralized data delivery network node to a digital twin or a portion thereof associated with a product. Access to the digital twin or a portion thereof may be requested by a decentralized data consumption network node. Product 106 may be produced by production 104, such as chemical production, as described in relation to Figures 1A to 2. The digital twin may include a decentralized digital twin identifier and at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data associated with the production and / or use of the product.

[0265] Digital access elements may be generated during or after the production of a product, as described, for example, in relation to Figures 11 and 12. Digital access elements may be associated with a digital twin or a portion thereof. Digital access elements may include a decentralized access element identifier and access data. The decentralized access element identifier may correspond to or be associated with the decentralized digital twin identifier of the digital twin. Access data may include a digital representation that points to the digital twin or a portion thereof. Access data may include a digital twin data identifier associated with the digital twin dataset contained in the digital twin (see, for example, Figure 13). An example of a digital access element is shown in Figure 13. Digital access elements may further include, or be associated with, authentication and / or authorization information linked to the decentralized access element identifier. Authentication and / or authorization information may be provided for authentication and / or authorization of the digital twin provider 722 and / or decentralized data consumption network node 808. Digital access elements may be provided to the access element registry 1208, as described, for example, in relation to Figure 12. The access element registry 1208 may store decentralized access element identifiers and associated access data.

[0266] Product 106 produced by production 104 may be provided to consumers in association with a digital access element. Consumers may process the product to produce further chemical products and / or separate products. Product 106 may be associated with a code such as a barcode or QR code that encodes a decentralized passport identifier. Consumers of product 106 may read the code through a code reader 1502. The code reader 1502 may be a smartphone running a code reading application such as a QR code reader app. Data obtained by the code reading application may be used to determine the decentralized access element identifier. Data obtained by the code reading application may be used to determine the decentralized digital twin identifier. Data obtained by the code reading application may be used to determine the product identifier. Data obtained by the code reading application may be used to determine the access data. The decentralized access element identifier, decentralized digital twin identifier, product identifier, and access data may be determined by the code reader 1502. For example, a decentralized passport identifier may be determined by the code reader 1502, or it may be a DID, and the code reader 1502 may be configured to retrieve an associated DID document containing the digital twin identifier and access data, for example, using a DID resolver (see also Figure 13). In another example, a product identifier may be determined by the code reader 1502 and used to retrieve a decentralized access element identifier and associated access data from a database, for example, an access element registry 1208. Thus, the code reader 1502 may be configured to retrieve a digital access element containing the decentralized access element identifier and access data from the access element registry 1208. The code reader 1502 may be configured to provide the decentralized access element identifier and / or decentralized digital twin identifier to a database 1506 associated with the consumer of the product.The code reader 1502 may be configured to provide the determined decentralized access element identifier, decentralized digital twin identifier, and access data to the decentralized data consumption network node 808.

[0267] The code reader 1502 may be configured to display the determined / acquired data on a user interface, as indicated by reference numeral 1504. The user interface may display the determined decentralized access element identifier (PP identifier), the determined decentralized digital twin identifier (DT identifier), and the determined access data (DT location). In this embodiment, the decentralized access element identifier and the decentralized digital twin identifier are different from each other. In another embodiment, the decentralized access element identifier is equal to the decentralized digital twin identifier. The user interface may further display the determined product identifier (CP identifier). The user interface may also allow the user to initiate the acquisition of the digital twin or a portion thereof based on the decentralized access element identifier and access data, as described below. This process may be initiated by a button labeled "Access DT". When the above button is pressed, the code reader 1502 may send a request to access the digital twin or a portion thereof to the decentralized data consumption network node 808.

[0268] A decentralized data consumption network node 808 associated with a consumer of a product may generate requests to access a digital twin or a portion thereof. The decentralized data consumption network node 808 may generate requests based on data received from the code reader 1502. For example, the decentralized data consumption network node 808 may generate requests based on a decentralized digital twin identifier received from the code reader 1502. The decentralized data consumption network node 808 may generate requests based on a decentralized access element identifier and / or a decentralized digital twin identifier provided to the database 1506. For example, the decentralized data consumption network node 808 may be configured to retrieve a decentralized digital twin identifier and access data from the access element registry 1208 based on a decentralized access element identifier stored in the database 1506. Requests generated by the decentralized data consumption network node 808 may include a decentralized digital twin identifier and a decentralized participant identifier associated with the participants in the decentralized network that operates the decentralized data consumption network node 808. The decentralized data consumption network node 808 may be configured to determine the digital twin provider 722 associated with the digital twin based on access data provided by the code reader 1502 or from the access element registry 1208.

[0269] The decentralized data consumption network node 808 may send a request to access the digital twin or a portion thereof to the determined digital twin provider 722, as indicated by arrow 1508. The digital twin provider 722 may be associated with a product producer. The digital twin provider 722 may be associated with a production 104, such as a chemical production, that produces product 106. The digital twin provider 722 may be associated with the data owner of the digital twin. In addition to the request, authentication and / or authorization information may be provided by the decentralized data consumption network node 808.

[0270] Requests can be authenticated. Requests can be verified by the digital twin provider 722, for example, by retrieving access rules from the digital twin provider 722's database based on the decentralized digital twin identifier contained in the received request. At least some of the retrieved access rules can be applied to the received request. This makes it possible to filter decentralized data consumption network nodes requesting access based on decentralized participant identifiers associated with the decentralized network participants operating the network nodes. If a request is invalid, for example, if the decentralized data consumption network node is not authorized to access the digital twin data, the peer-to-peer communication channel is terminated by the digital twin provider 722 and the digital twin is not provided.

[0271] If the request is valid, the digital twin provider 722 may initiate contract negotiations with the decentralized data consumption network node 808. The digital twin provider 722 may provide the decentralized data consumption network node 808 with an electronic contract. The electronic contract may include access rules associated with the decentralized digital twin identifier. This allows data consumers to determine the access and usage conditions associated with the desired data. The digital twin provider 722 and the decentralized data consumption network node 808 may be configured to negotiate and sign the electronic contract. The use of the electronic contract ensures that the decentralized data consumption network node 808 and any further systems handling the digital twin or part thereof comply with the access rules associated with the digital twin. Once the electronic contract is signed, the digital twin provider 722 may retrieve or request the digital twin stored in the DT storage 720 based on the decentralized digital twin identifier included in the received request, as indicated by arrows 1510 and 1512. The digital twin provider 722 may apply the determined access rules to the retrieved or received digital twin. Subsequently, the digital twin provider 722 may provide the digital twin or a portion thereof to the decentralized data consumption network node 808 in accordance with the applied access rules, as indicated by arrow 1514.

[0272] The digital twin provided by the digital twin provider 722 may be stored in the database 1506 associated with the decentralized data consumption network node 808, according to the access rules, as indicated by arrow 1516.

[0273] Through a decentralized digital twin identifier, a digital twin can be uniquely associated with a product. Over a decentralized network, the digital twin, or a portion thereof, can be transferred between product producers and consumers in a standardized and secure manner, allowing product producers to control access to the digital twin, or a portion thereof, by multiple decentralized data consumption network nodes residing within the decentralized network. Thus, the digital twin, or a portion thereof, can be shared directly among stakeholders in the product ecosystem without central mediation, thanks to its unique association with the product. This enhances the transparency of the digital twin within the product ecosystem.

[0274] By generating a digital twin of the physical entity of the manufactured product, and generating digital access elements associated with the digital twin, it becomes possible to share the product dataset contained in the digital twin under simplified and customizable conditions without compromising data security and data sovereignty.

[0275] This disclosure has been described in conjunction with preferred embodiments and examples. However, a person skilled in the art who practices the invention described in the claims will be able to understand and implement other variations by examining the drawings, this disclosure, and the claims.

[0276] Any of the steps presented herein can be performed in any order. The methods disclosed herein are not limited to any particular order of these steps. It is not required that the different steps be performed in a specific location or on a specific computing node of a distributed system; that is, each step may be performed on a different computing node using different equipment / data processing.

[0277] As used herein, “determine” also includes “initiate or cause to determine,” “generate” also includes “initiate and / or cause to generate,” and “provide” also includes “initiate or cause to determine, generate, select, transmit, and / or receive.” “Initiate or cause to perform an action” includes any processing signal that triggers a computing node or device to perform the respective action.

[0278] In the claims and herein, the word “including” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude plural. A single element or other unit may perform the function of several entities or items described in the claims. The mere fact that certain means are described in different dependent claims does not imply that a combination of these means cannot be used in a favorable embodiment.

Claims

1. An apparatus for generating a digital twin template associated with a product or product class, wherein the digital twin template defines one or more aspect models, each aspect model describing a specific set of characteristics of the product or product class, and the apparatus comprises one or more computing nodes and one or more computer-readable media having computer-executable instructions, wherein when the computer-executable instructions are executed by the one or more computing nodes, - A step of receiving a request to generate the digital twin template, wherein the request includes data related to the product, - A step of providing a digital twin master template associated with one or more product classes, wherein the digital twin master template defines multiple aspect models, - A step of providing product data based on the data included in the received request, - A step of optionally providing one or more additional aspect models, wherein the one or more additional aspect models are different from the plurality of aspect models defined in the digital twin master template, - A step of generating the digital twin template based on the provided product data, which defines at least one aspect model defined in the digital twin master template and optionally at least one of the further aspect models provided. An apparatus comprising a computer-readable medium configured to perform the above.

2. The apparatus according to claim 1, wherein the data relating to the product includes a product identifier, a product class, or a combination thereof.

3. The apparatus according to claim 1 or 2, wherein the digital twin master template includes the plurality of aspect models and / or one or more digital representations referring to the plurality of aspect models.

4. The apparatus according to any one of claims 1 to 3, wherein the digital twin master template defines the relationships between one or more aspect models from among the plurality of aspect models defined in the master template.

5. The apparatus according to any one of claims 1 to 4, wherein the plurality of aspect models include at least one essential aspect model and at least one optional non-essential aspect model.

6. The apparatus according to claim 5, wherein the at least one required aspect model includes an aspect model defining digital twin data, an aspect model defining digital twin template data, an aspect model defining product safety data, an aspect model defining a product producer, an aspect model defining the identification of the product, an aspect model defining at least a portion of the composition of the product, an aspect model defining product parameters, an aspect model defining the handling of the product, an aspect model defining the disposal of the product, or a combination thereof.

7. The apparatus according to claim 5 or 6, wherein the non-essential aspect models include an aspect model defining product packaging data, an aspect model defining a certificate of analytical data associated with the product, an aspect model defining emission data associated with the product, an aspect model defining production data associated with the product, an aspect model defining technical data associated with the product, an aspect model defining certificate data associated with the product, an aspect model defining data relating to suppliers of materials used to produce the product, an aspect model defining data relating to the supply of the product to consumers, an aspect model defining data relating to the registration of the product, or a combination thereof.

8. The apparatus according to any one of claims 1 to 7, wherein the step of generating the digital twin template includes selecting at least one aspect model from the plurality of aspect models defined in the provided digital twin master template based on the provided product data, and optionally selecting at least one of the further provided aspect models.

9. The apparatus according to any one of claims 1 to 8, wherein the digital twin template includes at least one of the aspect models defined in the digital twin master template and optionally at least one of the further provided aspect models, and / or includes one or more digital representations defined in the digital twin master template and optionally one or more digital representations referring to at least one of the further provided aspect models.

10. A computer implementation method for generating a digital twin template associated with a product or product class, wherein the digital twin template defines one or more aspect models, each aspect model describing a specific set of characteristics of the product or product class, and the method - A step of receiving a request to generate the digital twin template, wherein the request includes data related to the product, - A step of providing a digital twin master template associated with one or more product classes, wherein the digital twin master template defines multiple aspect models, - A step of providing product data based on the data included in the received request, - A step of optionally providing one or more additional aspect models, wherein the one or more additional aspect models are different from the plurality of aspect models defined in the digital twin master template, - A step of generating the digital twin template based on the provided product data, which defines at least one aspect model defined in the digital twin master template and optionally at least one of the further aspect models provided. A computer implementation method, including

11. A digital twin template generated by the apparatus described in any one of claims 1 to 9, or by the computer implementation method described in claim 10.

12. Use of the digital twin template according to claim 11 for generating a digital twin of the physical entity of a product.

13. An apparatus for generating a digital twin of a physical entity of a product, wherein the apparatus comprises one or more computing nodes and one or more computer-readable media having computer-executable instructions, and the computer-executable instructions are executed by the one or more computing nodes. - A step of receiving a request to generate the digital twin, wherein the request includes data related to the product, - A step of collecting data associated with the product from one or more data sources based on the received data relating to the product, wherein the data associated with the product includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data relating to the production and / or use of the product, - The steps of providing the collected data and a decentralized digital twin identifier optionally associated with the data owner, - A step of providing a digital twin template to be applied to the collected product data based on the data included in the received request, wherein the digital twin template is generated by the apparatus described in any one of claims 1 to 9 or in accordance with the computer implementation method described in claim 10. - A step of generating a digital twin dataset by applying each aspect model defined in the provided digital twin template to the collected data, - A step of generating the digital twin, which includes the provided decentralized identifier and the generated digital twin dataset. An apparatus comprising one or more computer-readable media configured to perform the above.

14. A computer-aided method for generating a digital twin of the physical entity of a product, wherein the method is - A step of receiving a request to generate the digital twin, wherein the request includes data related to the product, - A step of collecting data associated with the product from one or more data sources based on the received data relating to the product, wherein the data associated with the product includes at least one measured physical and / or chemical property of the product, and / or at least one physical and / or chemical property determined from collected data relating to the production and / or use of the product, - The steps of providing the collected data and a decentralized digital twin identifier optionally associated with the data owner, - A step of providing a digital twin template to be applied to the collected product data based on the data included in the received request, wherein the digital twin template is generated by the apparatus described in any one of claims 1 to 9 or in accordance with the computer implementation method described in claim 10. - A step of generating a digital twin dataset by applying each aspect model defined in the provided digital twin template to the collected data, - A step of generating the digital twin, which includes the provided decentralized identifier and the generated digital twin dataset. A computer implementation method, including

15. A computer element, such as a computer-readable storage medium containing instructions, a computer program, or a computer program product, wherein, when executed by a computing node or computing system, the instructions instruct the computing node or computing system to perform the steps of the method according to claim 10 and / or claim 14.

Images