System and method for managing data in digital twin

Abstract

A system is disclosed, comprising a processor configured to: run a digital twin of a real-world asset; receiving a data set from a data source via a first application programming interface (API), the data source communicatively coupled to a processor; updating the digital twin based on the received data set; receiving, via a second API, a query from a user device to obtain information from the digital twin, the user device communicatively coupled to the processor; processing the query to generate a response including the information; and sending the response to the user equipment.

Description

Technical Field

[0001] The present invention relates to managing large datasets. In particular, but not exclusively, the present invention relates to systems and methods for updating and querying datasets in at least one digital twin to generate responses. Background Art

[0002] With the advancement of technology, a shift from manual data management to computerized data management has been observed. This computerized management requires and creates a large amount of data which can vary greatly depending on the type of data management being performed. This data can exist as structured or unstructured data and can be in a variety of different formats. Since a large amount of data is available in multiple formats, managing this data to retrieve useful information is difficult.

[0003] Recently, various technologies have been used to manage such data and derive meaningful information. One such technology is digital twin technology, in which virtual representations (i.e., digital twins) are created that replicate real-world objects and processes. Digital twin technology is updated using real-time data and uses simulation, machine learning, and reasoning to perform decision-making processes. Digital twin technology allows time-efficient analysis of problem statements so that the problem statements are solved virtually (i.e., in simulation) rather than physically. However, such digital twin technology does not support multiple file formats, and there are limitations on the number of file formats that can be supported by a given digital twin. Therefore, it is difficult to integrate multiple functions and / or software with digital twin technology.

[0004] Recently, some systems have been designed to integrate multiple application processing interfaces (APIs) for each type of file format for updating and querying in the digital twin. Since each type of file format uses an API, the system ends up with many APIs, which makes the system extremely cumbersome, reduces query response speed, and thus causes lag. In addition, such systems do not provide a coherent solution to integrate the availability of different file formats.

[0005] Therefore, based on the preceding discussion, there is a need to overcome the aforementioned shortcomings associated with updating and querying datasets in digital twins to generate query responses. Summary of the invention

[0006] A first aspect of the present invention provides a system, comprising at least one processor, wherein the at least one processor is configured to:

[0007] -Run at least one digital twin of at least one real-world asset;

[0008] - receiving data sets from a plurality of data sources via a first application programming interface (API), the plurality of data sources being communicatively coupled to at least one processor;

[0009] -updating at least one digital twin based on the received data set;

[0010] - receiving, via a second API, a query from a user device for obtaining information from at least one digital twin, the user device being communicatively coupled to the at least one processor;

[0011] - processing the query to generate a response including said information; and

[0012] -Send the response to the user device.

[0013] Throughout this disclosure, the term "processor" refers to hardware, software, firmware, or a combination of these that is configured to control the operation of a system. In this regard, at least one processor performs a number of complex processing tasks. At least one processor is communicatively coupled to other components of a system device in a wireless and / or wired manner. In one example, at least one processor can be implemented as a programmable digital signal processor (DSP). In another example, at least one processor can be implemented via a cloud server that provides cloud computing services.

[0014] Throughout this disclosure, the term "digital twin" refers to a virtual representation of a given real-world asset that serves as a real-time digital counterpart. This means that, depending on changes observed in at least one real-world asset, at least one digital twin is updated in real time throughout its lifecycle. In addition, at least one digital twin utilizes at least simulation, machine learning, and reasoning techniques to assist in decision making. The term "real-world asset" refers to an object or process that exists in the real world. It should be understood that at least one real-world asset is not a data source.

[0015] Optionally, the real-world asset has a physical form associated with it. In this article, at least one real-world asset can be implemented in various ways, including but not limited to aircraft in the atmosphere, submarines underwater, spacecraft in outer space, healthcare operations and patient care, cities, sports, or games. In one example, at least one real-world asset can be implemented as an aircraft in the atmosphere. In this case, at least one digital twin can be a simulation of an aircraft for pilot training or flight optimization. In another example, at least one real-world asset can be implemented as a city, where architects use digital twins to plan the city or optimize the current plan of the city. Advantageously, using at least one digital twin of at least one real-world asset minimizes risks, reduces costs associated with maintenance, and ensures a high level of accuracy.

[0016] Optionally, at least one processor is configured to run at least one digital twin of at least one real-world asset on the digital platform. In this context, the digital platform is optionally based on at least one of the following: artificial intelligence (AI) technology, machine learning (ML) technology, software analysis technology, Internet of Things (IoT) technology.

[0017] The term "dataset" refers to a collection of data or information. Optionally, the dataset is presented in a tabular format, where each column corresponds to a given variable and each row corresponds to a given member of a given dataset. Examples of datasets include, but are not limited to, numerical datasets, binary datasets, multivariate datasets, categorical datasets, correlation datasets. In addition, such datasets can be implemented as geospatial datasets (i.e., time-based data associated with a specific location on the earth's surface), meta-tagged datasets, etc.

[0018] Optionally, the received data set includes at least one of the following: automatic dependent surveillance broadcast (ADSB) data, weather forecast data, trajectory prediction data. In this article, ADSB data represents the precise location of at least one real-world asset, weather forecast data represents the probability of weather conditions based on weather-based research, and trajectory prediction data represents the identification of the current or future development of the trajectory. The technical benefit of the received data set including the above data is that the data provides a high level of insight into at least one real-world asset and improves the accuracy of the digital twin.

[0019] The term "data source" refers to a memory configured to store at least one or some of a plurality of data sets. Optionally, a given data source is implemented as at least one of the following: a data source of the system, an external data source. In this document, when a given data source is implemented as a data source of the system, data related to the system is stored at the data source of the system, and when a given data source is implemented as an external data source, data related to the system is stored at the external data source. The plurality of data sources may include a numerical weather prediction (NWP) data source, a atmospheric circulation model (GCM) data source, and the like. In addition, the plurality of data sources are communicatively coupled to sensing elements of real-world assets corresponding to at least one digital twin.

[0020] Throughout this disclosure, the term "application programming interface (API)" refers to a set of functions and processes that facilitate at least one processor to access data and features from other devices (i.e., multiple data sources and user devices). Such an API acts as a bridge between at least one processor and the other devices. A given API is optionally implemented as at least one of the following: a public or open API, a private or internal API, a partner API, a composite API. It should be understood that at least one processor is configured to receive data sets from multiple data sources via a first API.

[0021] Optionally, the first API is used to query indexes of multiple data sources for receiving data sets from multiple data sources. In this document, the term "query" refers to a request for data or information from a given data source, and the term "index" refers to a mapping of keys to row positions in a given data set. In this document, a query may mark a sequence for receiving data sets from multiple data sources in sequence. For example, a query may mark a sequence as: dataset 1, data source 1; dataset 2, data source 3; dataset 3, data source 2, etc. Optionally, such indexing is performed by adopting at least one of the following: geospatial filters, meta tag filters, parameter-based filters. Since the system is implemented in real time, at least one digital twin needs to be updated in real time or near real time. In addition, when querying an index, the parameters of the query provide a valid data set.

[0022] In this article, at least one processor receives data sets from multiple data sources using a first API. At least one processor identifies valid data sets from multiple data sources and allocates a sequence for receiving valid data sets in a consumable form. The technical advantage of using the first API to query indexes of multiple data sources to receive data sets is that at least one processor is provided with updated data sets at all times (i.e., real-time or near real-time). This facilitates easy determination of valid data sets for a given query and ensures that the system is efficient.

[0023] Updating the at least one digital twin includes removing obsolete data values ​​and replacing obsolete data values ​​with new (i.e., updated) data values. It should be understood that updating ensures that the at least one digital twin is a real-time virtual copy of the at least one real-world asset because the at least one digital twin is constantly updated depending on changes in the at least one real-world asset. This allows functions to be virtually executed on the at least one digital twin to improve performance and accuracy.

[0024] Optionally, at least one processor is configured to update at least one digital twin based on the received data set using at least one artificial intelligence technique. In this article, new information about at least one digital twin is analyzed in the received data set, and the at least one digital twin is updated using the information. For example, if at least one digital twin represents weather conditions in San Francisco as dry and sunny with a temperature of 40 degrees Celsius, and the received data set indicates hail in San Francisco, the weather conditions in the at least one digital twin can be updated to now represent hail and a reduced temperature of 10 degrees Celsius.

[0025] Optionally, at least one digital twin is updated by indexing or by running at least one data processing pipeline on the data belonging to the received data set. An index refers to a unique set of fields of the data, wherein the unique set of fields is combined to form a unique index on a given digital twin. For example, when data is passed between two digital twins of two real-world assets, there may be a local index. The term "data processing pipeline" refers to a set of instructions that determine the processing and transfer of data belonging to the received data set. It should be understood that at least one data processing pipeline specifies how to process the received data set. In this article, at least one data processing pipeline inputs data into at least one digital twin. The received data set is indexed by assigning a processing order to the data therein, identifying and extracting new data for updating at least one digital twin. This means that the index indicates when (i.e., according to which order) the received data set is processed. In this article, the received data set is processed and thereby merged into a single view in order to update at least one digital twin. The technical advantage of this index is that it is efficient and accurate.

[0026] Optionally, a given data processing pipeline includes a sequence of data processing based at least on the type of real-world asset corresponding to at least one digital twin. In this article, a given data processing pipeline corresponds to a plurality of received data sets, wherein the received data sets are used to update at least one digital twin. Since at least one digital twin depends on the type of the corresponding real-world asset, the given data processing pipeline also corresponds to the type of the real-world asset. This means that separate data processing pipelines can be run for digital twins of separate real-world assets. For example, if a given real-world asset is a fixed asset (e.g., an airport), the sequence of data processing in a given data processing pipeline may be different from when the given real-world asset is a dynamic asset (e.g., an aircraft). In this article, the sequence of data processing refers to a set of instructions for processing data (preferably in sequence). Optionally, the sequence of data processing is based on: a first-in, first-out method, a priority-based method, a size-based method, etc. The technical advantage of a given data processing pipeline based on the type of real-world asset is that the processing of the data is customized, which results in a more efficient and more accurately updated digital twin than without such customization. Another technical advantage of doing this is that it allows at least one digital twin to be continuously updated, increasing the scalability of the system.

[0027] Optionally, the user device is associated with the user. In this article, the user can interact with the system through the user device. In addition, the user can provide a query for obtaining information to the user device, and then at least one processor can receive the query together with it. Examples of user devices include, but are not limited to, mobile phones, computers, laptops, and smart watches. The query for obtaining information refers to a request for obtaining information from at least one digital twin. Optionally, the query for obtaining information is executed asynchronously. This means that multiple queries can be executed simultaneously. One technical advantage of asynchronous queries is that they are time-efficient because they do not require the user to wait for the query to be sent. In addition, another technical advantage is that the query for obtaining information can be returned in any selected open support format, providing versatility to the system. The technical advantage of receiving queries from a user device is that it provides users with precise and easy access to request queries. In this article, the user can be anyone (such as an administrator of the system, a business owner using the system, etc.).

[0028] Optionally, at least one processor is configured to receive a custom tag associated with the query from the user device, wherein the custom tag provides additional information to facilitate the processing of the query. In this article, the term "custom tag" refers to a tag that requires custom information from the user. It should be understood that the custom tag assists in distinguishing data sets in terms related to humans. Such custom tags are based on at least one of the following: geographic area, customer, date and time. In one example, the custom tag can be "London", which covers the physical area of ​​London. In another example, the custom tag can be UKGVT, which is customer-specific to the UK government. In addition, the custom tag provides additional insight for accurately processing the query. For example, the query can identify the flights that utilize the most fuel per unit distance. Therefore, the custom tag may require additional information, such as: the amount of fuel utilized by the flight when the flight approaches the equator, the way in which the amount of fuel utilized by the flight varies depending on the flight altitude, etc. It has been shown that these factors control the use of fuel due to the gravity of the earth. Therefore, when running a query for the most fuel-burning flights, longer flights flying at low altitudes and close to the equator may be a possible result. Advantageously, the custom tag assists the end user in identifying the data. Examples of custom tags include, but are not limited to, airports, forecasts, aftercasts, weather conditions, and SO2 generation. In this context, a given custom tag may represent a given received data set or data therein. A technical advantage of including custom tags is that it provides additional information that enables accurate retrieval of relevant data to process a query, resulting in more precise and / or accurate results.

[0029] The query is processed by matching the terms of the query with the received data set, such as by matching the terms of the query with the rows and columns in the received data set. For example, for a query about a flight that was shortened or ended abruptly, the processor may be configured to identify flights in the data set that originally had a set destination and arrival time but did not arrive at the set destination at the arrival time. Since at least one digital twin is continuously updated with information received from the received data set, the query is processed at at least one digital twin. It should be understood that the query is similar to a filter that filters data from the received data set based on at least one parameter. In one example, the query may be for flights departing from Heathrow Airport on February 20, 2020. When the query is processed, all flights matching the parameters—departing from Heathrow Airport and departing on February 20, 2020—will be found from the received data set. In this article, the query is initially processed to determine the validity of the query (i.e., to ensure that the received data set includes the information). When it is determined that the query is valid, an index of the information is queried, and the index is received by at least one processor. Thereafter, at least one processor uses the index to retrieve at least one data source including the information to generate a response.

[0030] Optionally, the response is generated in an open format, which is at least one of the following: comma separated value (CSV) format, JavaScript object notation (JSON) format, keyhole markup language (KML) format. The CSV format is a delimited file format that uses commas to separate values ​​in the file. The JSON format is a standard text-based file format for representing structured data. Examples of the JSON format include, but are not limited to, the GeoJSON format, the XArrayJSON format, the HJSON format, the HOCON format, and the JSON5 format. The KML format is a file format for displaying geographic data in a globe browser. These formats are well known in the art. The term "open format" refers to a file format with publicly published specifications so that anyone can use it. The technical advantage of using at least one of the above open formats (i.e., multiple open formats) is that it allows a variety of different use cases and implementations, making the system versatile.

[0031] The response is sent from the at least one processor to the user device via the second API. Since the user device is associated with the user, the user can perform multiple operations on the response. Such operations include, but are not limited to, displaying the response, running the response, viewing the response, deleting the response, analyzing the response, and further processing the response. For different responses received from the at least one processor, different models of the interactive digital twin with different use cases can be determined.

[0032] In an exemplary scenario, a digital twin of an aircraft (at least one real-world asset) runs on at least one processor of the system. In this article, sensors and cameras can be used to capture information related to the aircraft, thereby transmitting updated information in real time or near real time. For example, sensors can be used to map the position of the aircraft, monitor the speed of the aircraft, fuel availability, the path followed, etc. In addition, cameras can be mounted on the outside of the aircraft to view the entire part of the aircraft (e.g., the wing). The camera can also be used to assess the weather. Such information can be stored at a cloud-based database and sent to at least one processor via a first API. The digital twin of the aircraft can then be updated with information to accurately represent the aircraft. The query being received can be related to fuel usage at a given time during the flight, which can be processed using a digital twin to send a response to the user device via a second API, which can be 3511 liters.

[0033] Optionally, the first API and the second API jointly provide an open multi-API specification, and a platform for data query is built on the open multi-API specification. The open multi-API specification refers to an open source format for describing and recording multiple APIs. Since the first API communicatively connects at least one processor to multiple data sources, and the second API communicatively connects at least one processor to a user device, the open multi-API specification serves as a network that connects at least at least one processor, multiple data sources, and a user device. The platform for data query provides a set of tools to facilitate building different models for different use cases and presenting such data on a user device in an insightful manner. The technical advantage of having an open multi-API specification is that it provides the flexibility to build different models, use different formats, etc.

[0034] Optionally, at least one processor is configured to send the received data set to at least one other digital twin running on at least one other processor, wherein the at least one processor and the at least one other processor are communicatively coupled to each other. In this article, each digital twin is continuously updated based on the received data set. In addition, this communication coupling between at least one processor and at least one other processor facilitates seamless sharing of data between at least one digital twin and at least one other digital twin. Multiple digital twins running on multiple processors optionally send data to each other, wherein the multiple processors are communicatively coupled to each other. In this article, at least one data processing pipeline transfers data between at least one digital twin and at least one other digital twin. Optionally, at least one other processor is configured to access a digital platform for data query. The technical advantage of this data sharing between digital twins is that all digital twins (although run separately by different processors) are updated in real time with shared data. This means that each digital twin represents data from each other digital twin, so that a given digital twin also represents data from all other digital twins. This provides a higher level of insight into the system and makes a given digital twin more accurate than when data is not shared.

[0035] Optionally, the type of real-world asset is an aircraft, and wherein the response sent to the user device is used to determine the CO2 emissions from the aircraft and the trajectory data of the aircraft to subsequently propose a flight path for the aircraft. CO2 emissions and trajectories have a negative impact on the environment. Recently, due to the negative impact, aircraft providers have to pay fees based on their carbon footprint. Due to this, aircraft providers are now trying to find an optimized route that will result in lower CO2 emissions and lower trajectory formation. It should be understood that the response sent by at least one processor to the user device is used to calculate the CO2 emissions of the formed trajectory. In this article, initially, the response is used to determine whether a trajectory has been formed for a given flight path. On it, if a trajectory has been formed, the CO2 emissions for the given flight path are calculated. Optionally, CO2 emissions from the aircraft are calculated by estimating engine fuel consumption. In one example, an A320 aircraft can use 3125 liters of kerosene per hour, that is, 2560 kilograms of kerosene. In this example, the carbon offset emissions will be 3×engine fuel consumption=3×2560=7680 kilograms per hour. Such calculations are performed for all possible flight paths, and a flight path with the minimum amount of carbon offset emissions is proposed. The technical advantage of the response used to propose a flight path is that the calculation of such a flight path includes a lot of environmental (and other) details and requires a lot of processing. Therefore, using a digital twin to calculate and propose such a flight path is time efficient, precise and accurate.

[0036] A second aspect of the present invention provides a method comprising:

[0037] -Run at least one digital twin of at least one real-world asset;

[0038] - receiving data sets from a plurality of data sources via a first application programming interface (API);

[0039] -updating at least one digital twin based on the received data set;

[0040] - receiving, via a second API, a query for obtaining information from at least one digital twin;

[0041] - processing the query to generate a response including said information; and

[0042] -Send the response to the user device.

[0043] The technical advantage of the method is that receiving a data set using a first API and receiving a query using a second API simplifies the process by having specific functions dedicated to each API. This simplifies processing queries in at least one digital twin (since digital twins have a large amount of data) and sending responses in an efficient and precise manner. Another technical benefit of the method is that it can process various types of geometries and assets in a timely manner (i.e., without any lag).

[0044] In one embodiment, the step of receiving the data set from the plurality of data sources includes querying an index of the plurality of data sources.

[0045] In one embodiment, the step of updating at least one digital twin includes indexing or running at least one data processing pipeline on data belonging to the received data set.

[0046] In one embodiment, the method further includes receiving, from the user device, a custom tag associated with the query, wherein the custom tag provides additional information to facilitate processing of the query.

[0047] In one embodiment, the method further includes sending the received data set to at least one other digital twin.

[0048] A third aspect of the present invention provides a computer program product for implementing at least one interactive digital twin, the computer program product comprising a non-transitory machine-readable data storage medium having program instructions stored thereon, the program instructions, when accessed by a processing device, causing the processing device to:

[0049] -Run at least one digital twin of at least one real-world asset;

[0050] - receiving data sets from a plurality of data sources communicatively coupled to the processing device via a first application programming interface (API);

[0051] -updating at least one digital twin based on the received data set;

[0052] - receiving, via a second API, a query from a user device for obtaining information from at least one digital twin, the user device being communicatively coupled to the processing device;

[0053] - processing the query to generate a response including said information; and

[0054] -Send the response to the user device.

[0055] Throughout this disclosure, the term “computer program product” refers to a software product comprising program instructions recorded on a non-transitory machine-readable data storage medium, wherein the software product is executable on computing hardware (ie, at least one processor).

[0056] In one embodiment, program instructions stored on a non-transitory machine-readable data storage medium may direct a processing device to function in a particular manner so that the processing device performs processing steps for managing data in a digital twin. Examples of non-transitory machine-readable data storage media include, but are not limited to, electronic storage devices having instructions recorded thereon, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding devices such as punched cards or raised structures in grooves, or any suitable combination thereof.

[0057] Throughout the description and claims of this specification, the words "comprise" and "contain" and variations of these words, such as "comprising" or "comprises", mean "including but not limited to", and do not exclude other components, integers or steps. In addition, unless the context requires otherwise, the singular includes the plural: in particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

[0058] Preferred features of each aspect of the invention may be as described in conjunction with any other aspect. Within the scope of the present application, it is expressly intended that the various aspects, embodiments, examples and alternatives set forth in the preceding paragraphs, claims and / or the following description and drawings, and in particular individual features thereof, may be employed independently or in any combination. That is, all embodiments and / or features of any embodiment may be combined in any manner and / or combination, unless such features are incompatible. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] One or more embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0060] Figure 1 is a schematic diagram of a system according to an embodiment of the present disclosure;

[0061] Figure 2 is an exemplary illustration of the execution of the processor 200 of the system and the information contained therein according to an embodiment of the present disclosure; and

[0062] Figure 3 The steps of a method according to an embodiment of the present disclosure are shown. DETAILED DESCRIPTION

[0063] Figure 1 1 is a schematic diagram of a system 100 according to an embodiment of the present disclosure. The system 100 includes at least one processor (depicted as processor 102). The processor 102 runs at least one digital twin of at least one real-world asset. The processor 102 is communicatively coupled to a plurality of data sources 104a, 104b, 104c (hereinafter collectively referred to as 104). At least data sets are stored at the plurality of data sources 104. The processor 102 is communicatively coupled to a user device 106. The processor 102 receives a query from the user device 106 for obtaining information from at least one digital twin.

[0064] Figure 2 2 is an exemplary illustration of the execution of a processor 200 of a system according to an embodiment of the present disclosure and the information contained therein. The processor 200 executes a data processing pipeline 202. The data processing pipeline 202 includes: at least one numerical weather prediction (NWP) data processing pipeline, at least one general circulation model (GCM) data processing pipeline, and at least one other data processing pipeline. The processor 200 has an index 204 of multiple data sources (not shown). The processor 200 executes a first application programming interface (API) 206 and a second application programming interface (API) 208. The index 204 is coupled to the first API 206 and the second API 208.

[0065] refer to Figure 3, showing the steps of a method according to an embodiment of the present disclosure. In step 302, run at least one digital twin of at least one real-world asset. In step 304, receive a data set from a plurality of data sources via a first application programming interface (API). In step 306, update at least one digital twin based on the received data set. In step 308, receive a query for obtaining information from at least one digital twin from a user device via a second API. In step 310, process the query to generate a response including the information. In step 312, send the response to the user device.

[0066] The above steps are merely illustrative, and other alternatives may also be provided, wherein one or more steps are added, one or more steps are removed, or one or more steps are provided in a different order without departing from the scope of the claims herein.

Claims

1. A system comprising at least one processor, wherein the at least one processor is configured to: -Run at least one digital twin of at least one real-world asset; - receiving data sets from a plurality of data sources via a first application programming interface (API), the plurality of data sources being communicatively coupled to the at least one processor; - Updating the at least one digital twin based on the received data set; - receiving, via a second API, a query from a user device for obtaining information from the at least one digital twin, the user device being communicatively coupled to the at least one processor; - processing the query to generate a response including the information; as well as - sending the response to the user equipment.

2. The system according to claim 1, wherein: The first API is used to query indexes of the multiple data sources and to receive the data sets from the multiple data sources.

3. The system according to claim 1 or 2, wherein: The at least one digital twin is updated by indexing or by running at least one data processing pipeline on data belonging to the received data set.

4. The system according to claim 3, wherein: A given data processing pipeline includes a data processing sequence based at least on a type of real-world asset corresponding to the at least one digital twin.

5. A system according to any one of the preceding claims, wherein: The at least one processor is configured to receive, from the user device, a custom tag associated with the query, wherein the custom tag provides additional information to facilitate processing of the query.

6. A system according to any one of the preceding claims, wherein: The response is generated in an open format, the open format being at least one of the following formats: a comma separated value (CSV) format, a JavaScript Object Notation (JSON) format, a Keyhole Markup Language (KML) format.

7. A system according to any one of the preceding claims, wherein: The first API and the second API jointly provide an open multi-API specification, and a platform for data query is built on the open multi-API specification.

8. A system according to any one of the preceding claims, wherein: The at least one processor is configured to send the received data set to at least one other digital twin running on at least one other processor, wherein the at least one processor and the at least one other processor are communicatively coupled to each other.

9. A system according to any one of the preceding claims, wherein: The received data set includes at least one of: Automatic Dependent Surveillance Broadcast (ADSB) data, weather forecast data, trajectory prediction data.

10. The system according to claim 4, wherein: The type of real world asset is an aircraft, and wherein the response sent to the user device is used to determine carbon dioxide emissions from the aircraft and trajectory data for the aircraft to subsequently propose a flight path for the aircraft.

11. A method comprising: -Run at least one digital twin of at least one real-world asset; - receiving data sets from a plurality of data sources via a first application programming interface (API); - Updating the at least one digital twin based on the received data set; - receiving, via a second API, a query for obtaining information from the at least one digital twin; - processing the query to generate a response including the information; as well as - sending the response to the user equipment.

12. The method according to claim 11, wherein: Receiving the data set from the plurality of data sources includes querying an index of the plurality of data sources.

13. The method according to claim 11 or 12, wherein: The step of updating the at least one digital twin comprises indexing or running at least one data processing pipeline on data belonging to the received data set.

14. The method according to any one of claims 11-13, further comprising receiving a custom tag associated with the query from the user device, wherein: The custom tags provide additional information to facilitate processing of the query.

15. A computer program product for implementing at least one interactive digital twin, the computer program product comprising a non-transitory machine-readable data storage medium having program instructions stored thereon, the program instructions, when accessed by a processing device, causing the processing device to: -Run at least one digital twin of at least one real-world asset; - receiving data sets from a plurality of data sources via a first application programming interface (API), the plurality of data sources being communicatively coupled to the processing device; - Updating the at least one digital twin based on the received data set; - receiving, via a second API, a query from a user device for obtaining information from the at least one digital twin, the user device being communicatively coupled to the processing device; - processing the query to generate a response including the information; as well as - sending the response to the user equipment.

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