Systems and methods for provisioning and digitizing asset profiles

Abstract

Embodiments include a system for affirming validity of sample data representing resources extracted at one or more locations. The system can include one or more processors that are configured to receive sample data associated with a resource, and determine at attribute profile for the resource based on the sample data. In examples, the one or more processors can generate a unique resource identifier for the resource at one or more points in time based on the sample data and the attribute profile. The unique resource identifier can affirm validity of the resource represented by the sample data.

Description

SYSTEMS AND METHODS FOR PROVISIONING ANDDIGITIZING ASSET PROFILESCROSS-REFERENCE TO RELATED APPLICATION

[0001] The present application claims priority to U.S. Provisional Patent Application No. 63 / 533,534 filed on August 18, 2023, the contents of which are hereby incorporated by reference in their entirety and for all purposes.TECHNICAL FIELD

[0002] This application generally relates to systems and methods for affirming validity of sample data representing resources and, in some examples, to the development and implementation of systems that obtain sample data based on resources extracted at one or more locations and affirm the validity of the sample data.BACKGROUND

[0003] When obtaining and evaluating resources such as precious metals and the like, it can be difficult to determine whether parties involved in such evaluation are relaying correct information about the resources. For example, individuals or organizations can assert, via virtual exchanges, that a given resource has been extracted and is available in a certain quantity and state. However, confirmation of the actual existence, quantity, and state of the resource still requires physical verification and, in many cases, chemical analysis. And even when parties are able to access and chemically analyze samples of the resources, such analysis can be prohibitively expensive. Further, in view of the increasing sophistication of individuals counterfeiting such resources, chemical analysis may still result in an incorrect determination of one or more aspects of the resource (e.g., that the resource was extracted in a given region, that the composition of the resource is as claimed, etc.).SUMMARY

[0004] In some aspects, the techniques described herein relate to a system for affirming validity of sample data representing resources extracted at one or more locations. The system can include one or more processors. The one or more processors can be configured to receive sample data associated with a resource, the sample data collected at a first point in time. The one or more processors can be configured to determine at attribute profile for the resource based on the sample data. In some implementations, the one or more processors can be configured to in response to determining that the sample data is valid, generate a uniqueresource identifier for the resource at the first point in time based on the sample data and the attribute profile. The unique resource identifier can affirming validity of the resource represented by the sample data. In some implementations, the one or more processors can be configured to transmit the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier including an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

[0005] In some aspects, the one or more processors configured to receive the sample data can be configured to receive the sample data based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource. In some implementations, the one or more processors configured to receive the sample data can be configured to receive values indicating one or more of a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated.

[0006] In aspects, the one or more processors configured to determine an attribute profile for the resource based on the sample data can be configured to transmit the sample data as an input to a neural network to cause the neural network to generate an output, the output including one or more aspects of the resource, and determine the attribute profile based on the one or more aspects of the resource. In some aspects, the one or more processors configured to receive the sample data can be configured to receive a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sample data, and the one or more processors can be further configured to: determine that the sample data is valid based on at least one aspect of the attribute profile.

[0007] In some aspects, the one or more processors configured to generate the unique resource identifier for the resource can be configured to execute one or more operations involved in generating a hash based on the sample data and the attribute profile; and determine the unique resource identifier based on the hash. The one or more processors configured to transmit the sample data and the unique resource identifier to the remote device can be configured to transmit the sample data and the unique resource identifier to a broadcasting device to cause the sample data and the unique resource identifier to be stored in an entry of a database associated with the broadcasting device. The one or more processors can configurethe broadcasting device to maintain an index sub-entries corresponding to the entry. The index of sub-entries can be provided to the broadcasting device based on execution of one or more operations involving the sample data and the unique resource identifier by one or more monitoring devices.

[0008] In some aspects, the techniques described herein relate to a method for affirming validity of sample data representing resources extracted at one or more locations. The method can include receiving, by one or more processors, sample data associated with a resource, the sample data collected at a first point in time. In some implementations, the method includes determining, by the one or more processors, at attribute profile for the resource based on the sample data. In response to determining that the sample data is valid, the method can include generating, by the one or more processors, a unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile, the unique resource identifier affirming validity of the resource represented by the sample data. The method can include transmitting, by the one or more processors, the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier including an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

[0009] In some aspects, receiving the sample data can include receiving, by the one or more processors. The sample data can be based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource.

[0010] In aspects, the receiving the sample data can include receiving, by the one or more processors, values indicating one or more of: a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated. In aspects, determining an attribute profile for the resource based on the sample data can include transmitting, by the one or more processors, the sample data as an input to a neural network to cause the neural network to generate an output, the output including one or more aspects of the resource; and determining, by the one or more processors, the attribute profile based on the one or more aspects of the resource.

[0011] In some aspects, receiving the sample data can include: receiving, by the one or more processors, a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sampledata. The method can further include: determining, by the one or more processors, that the sample data is valid based on at least one aspect of the attribute profile. In some aspects, generating the unique resource identifier for the resource can include: executing, by the one or more processors, one or more operations involved in generating a hash based on the sample data and the attribute profile; and determining, by the one or more processors, the unique resource identifier based on the hash.

[0012] In aspects, transmitting the sample data and the unique resource identifier to the remote device can include: transmitting, by the one or more processors, the sample data and the unique resource identifier to a broadcasting device to cause the sample data and the unique resource identifier to be stored in an entry of a database associated with the broadcasting device. The method can include configuring, by the one or more processors, the broadcasting device to maintain an index sub-entries corresponding to the entry, the index of sub-entries provided to the broadcasting device based on execution of one or more operations involving the sample data and the unique resource identifier by one or more monitoring devices.

[0013] In some aspects, a non-transitory, computer-readable medium storing instructions thereon is disclosed that, when executed by one or more processors, cause the one or more processors to receive sample data associated with a resource. The sample data can be collected at a first point in time. The instructions can cause the one or more processors to determine at attribute profile for the resource based on the sample data. In some implementations, the instructions can cause the one or more processors to, in response to determining that the sample data is valid, generate a unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile, the unique resource identifier affirming validity of the resource represented by the sample data. The instructions can cause the one or more processors to transmit the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier including an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

[0014] In some aspects, the instructions that cause the one or more processors to receive the sample data can cause the one or more processors to: receive the sample data based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource. In aspects, the instructions that cause the one or more processors toreceive the sample data can cause the one or more processors to: receive values indicating one or more of: a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated.

[0015] In some aspects, the instructions that cause the one or more processors to determine an attribute profile for the resource based on the sample data can cause the one or more processors to: transmit the sample data as an input to a neural network to cause the neural network to generate an output, the output including one or more aspects of the resource; and determine the attribute profile based on the one or more aspects of the resource.

[0016] In some aspects, the instructions that cause the one or more processors to receive the sample data can cause the one or more processors to: receive a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sample data, and wherein the instructions further cause the one or more processors to: determine that the sample data is valid based on at least one aspect of the attribute profile. In aspects, the instructions that cause the one or more processors to generate the unique resource identifier for the resource can cause the one or more processors to: execute one or more operations involved in generating a hash based on the sample data and the attribute profile; and determine the unique resource identifier based on the hash.

[0017] In some aspects, the techniques described herein relate to a system including: one or more processors configured to: generate a plurality of entries to include in a database. Each entry of the plurality of entries can correspond to a resource of a plurality of resources obtained during a first period of time. The one or more processors can be configured to, in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, provide entry data associated with the first set of entries to the first server and the second server. In some implementations, the one or more processors can be configured to receive, from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries, and determine an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes. In some implementations, the one or more processors can be configured to update the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

[0018] In some aspects, the one or more processors can be further configured to: receive sample data associated with a plurality of resources. The sample data can be generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources. In some aspects, the one or more processors can be further configured to determine an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, updating each entry of the plurality of entries to include the pseudo-identifier.

[0019] In some aspects, the one or more processors configured to update each entry of the plurality of entries can be configured to: remove the identifier associated with the client device from each entry of the plurality of entries. Each entry can be configured to include a plurality of sub-entries that correspond to a respective resource. Each sub-entry of the plurality of sub-entries can be associated with a point in time during the first period of time, and the one or more processors configured to receive the initial attribute data can be configured to: receive the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry.

[0020] In some aspects, the one or more processors can be further configured to: determine a final attribute for each entry based on the intermediate attribute for each sub-entry. The one or more processors can be further configured to: receive status data indicating that at least one resource transitioned from a first state to a second state. In some implementations, in response to determining that the at least one resource transitioned from the first state to the second state, the one or more processors can be configured to provide the status data to the first server and the second server, and receive, from the first server and the second server, second attribute data representing one or more second intermediate attributes corresponding to each entry of the first set of entries. In some implementations, the one or more processors can be configured to determine a second intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes. In some implementations, the one or more processors can be configured to update the plurality of entries based on the second intermediate attribute corresponding to each entry of the set of entries.

[0021] In some aspects, a method is disclosed. The method can include generating, by one or more processors, a plurality of entries to include in a database, each entry of the plurality of entries corresponding to a resource of a plurality of resources obtained during a first periodof time. The method can include, in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, providing, by one or more processors, entry data associated with the first set of entries to the first server and the second server. In some implementations, the method can include receiving, by one or more processors from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries, and determining, by the one or more processors, an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes. In some implementations, the method can include updating, by the one or more processors, the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

[0022] In some aspects, the method can include receiving, by the one or more processors, sample data associated with a plurality of resources, the sample data generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources. The method can further including: determining, by the one or more processors, an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, updating, by the one or more processors, each entry of the plurality of entries to include the pseudo-identifier.

[0023] In some aspects, updating each entry of the plurality of entries can include removing, by the one or more processors, the identifier associated with the client device from each entry of the plurality of entries. Each entry can be configured to include a plurality of subentries that correspond to a respective resource, where each sub-entry of the plurality of subentries is associated with a point in time during the first period of time. In some implementations, receiving the initial attribute data can include: receiving, by the one or more processors, the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry, where the one or more initial attributes represent one or more states of the resource when transitioning through one or more ISO-transitions.

[0024] In some aspects, the method can further include determining, by the one or more processors, a final attribute for each entry based on the intermediate attribute for each subentry. The method can further include receiving, by the one or more processors, status data indicating that at least one resource transitioned from a first state to a second state, and in response to determining that the at least one resource transitioned from the first state to thesecond state, providing, by the one or more processors, the status data to the first server and the second server. In some implementations, the method can include receiving, by the one or more processors from the first server and the second server, second attribute data representing one or more second intermediate attributes corresponding to each entry of the first set of entries. In aspects, the method can include determining, by the one or more processors, a second intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes. In some implementations, the method can include updating, by the one or more processors, the plurality of entries based on the second intermediate attribute corresponding to each entry of the set of entries.

[0025] In aspects, a non-transitory, computer-readable medium is disclosed herein as storing instructions thereon that, when executed by one or more processors, cause the one or more processors to: generate a plurality of entries to include in a database, each entry of the plurality of entries corresponding to a resource of a plurality of resources obtained during a first period of time. The instructions can cause the one or more processors to, in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, provide entry data associated with the first set of entries to the first server and the second server; receive, from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries; determine an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and update the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

[0026] In some aspects, the instructions can further cause the one or more processors to: receive sample data associated with a plurality of resources, the sample data generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources. The instructions can further cause the one or more processors to: determine an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, update each entry of the plurality of entries to include the pseudo-identifier.

[0027] In some aspects, the instructions that cause the one or more processors to update each entry of the plurality of entries can cause the one or more processors to: remove the identifier associated with the client device from each entry of the plurality of entries. Each entry can be configured to include a plurality of sub-entries that correspond to a respectiveresource, wherein each sub-entry of the plurality of sub-entries is associated with a point in time during the first period of time. The instructions that cause the one or more processors to receive the initial attribute data can cause the one or more processors to: receive the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry. In some aspects, the instructions can further cause the one or more processors to: determine a final attribute for each entry based on the intermediate attribute for each sub-entry.

[0028] In contrast with the conventional techniques of sampling a resource at a discrete point in time to determine one or more aspects related to that resource, the present disclosure describes systems and methods that allow for the evaluation of additional information during the entire lifecycle of a resource to affirm the existence of such resources and representations made about the resources. More specifically, the present disclosure describes the implementation of systems and methods that allow for the cumulative evaluation and tracking of more specific aspects representing a given resource as samples of a given resource are obtained and evaluated. This can allow for greater granularity of information available to evaluate representations made, thereby reducing the ability of counterfeiters to make false representations whose invalidity is undetectable (or difficult to detect). The presently disclosed techniques can further allow for improvements in the overall verification process, by extending information previously unavailable to remote individuals or organizations when validating, confirming, or certifying the validity of signatures and security pins (e.g., access privilege pins), related datasets, and ISO-Transitioning protocols of coalescing, analysis, and agglomeration. When implemented, the affirmation process described herein allows for the generation and maintenance of all of the product datasets and values that represent the entire process of affirmation (and represents a more inclusive multi-purpose process and protocols).

[0029] In aspects regarding the techniques described in this disclosure relate to systems described herein for among other things affirming validity, verification of sample data, and / or confirmation of a sample data representing resources extracted at one or more locations. In examples, the techniques described herein relate generally to affirmation processes that involve and incorporate information a greater resolution with more granularity, as is conventionally available, and rises above any mere confirmation process. For example, affirmation as a comprehensive process, can be represented by techniques which can involve incorporating a greater granularity to establish a more comprehensive view of a given resource (e.g., as a composite of the information generated and obtained) via common processes, such asverification, validation, confirmation, certification, and / or representative signatories, signatures and access privilege pins, related data sets, ISO-Transitioning protocols of coalescing, analysis and agglomeration. The affirmation process can incorporate not only the aforementioned data, but any and all of the product datasets and values that represent the entire process of affirmation (represents a more inclusive multi-purpose process and protocols). In some examples, the affirmation process, in relation to resources (sometimes referred to as assets) can represent a more comprehensive solution in regards to any and all resources (e.g., real property, natural resources, financial resources, and / or digital proxies representing a digital coins) representing physical resources. Moreover, the affirmation process can include a holographic hallmark implemented by authorized institutes maintaining either digital representative resources to be hallmarked or actual material / physical hallmarks that relate to an actual holding (e.g., in an authorized institution, a metals or minerals repository, and / or the) as described herein. This can increase the difficult encountered by counterfeiters when attempting to replicate holographic hallmarks and provide resources with misleading and / or incorrect representations about the resource.BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present disclosure can be better understood by referring to the following figures. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the disclosure. In the figures, reference numerals designate corresponding parts throughout the different views.

[0031] FIG. 1 shows an environment for confirming validity of sample data representing resources, according to an embodiment.

[0032] FIG. 2 shows an example process for affirming validity of sample data representing resources, according to an embodiment.

[0033] FIG. 3A-3C show an example implementation of a process for affirming validity of sample data representing resources, according to an embodiment.

[0034] FIG. 4 is a flow diagram for confirming validity of sample data representing resource, according to an embodiment.

[0035] FIGS. 5A-5D show an example implementation of a process for confirming validity of sample data representing resources, according to an embodiment.DETAILED DESCRIPTION

[0036] Reference will now be made to the illustrative embodiments depicted in the drawings, and specific language will be used here to describe the same. It will nevertheless be understood that no limitation of the scope of the claims or this disclosure is thereby intended. Alterations and further modifications of the features illustrated herein, and additional applications of the principles of the subject matter illustrated herein, which would occur to one skilled in the relevant art and having possession of this disclosure, are to be considered within the scope of the subject matter disclosed herein. Other embodiments can be used and / or other changes can be made without departing from the spirit or scope of the present disclosure. The illustrative embodiments described in the detailed description are not meant to be limiting to the subject matter presented.

[0037] Described herein are systems and methods for confirming validity of sample data generated during the extraction and testing of resources. In an example, systems described herein can include processors that are configured to receive sample data associated with a resource, determine at attribute profile for the resource based on the sample data, and generate a unique resource identifier for the resource that affirms the validity of the resource (e.g., indicating that the sample data represents a real (non-counterfeit) resource with a predetermined degree of probability). The processors can iteratively repeat this process and update the attribute profile based on input received from remote devices. In examples, the unique resource identifier can affirm validity of the resource represented by the sample data. The system can be further configured to transmit the sample data and the unique resource identifier to a remote device along with an affirmation instruction to indicate a status of the attribute profile of the resource as being valid or not valid.

[0038] By virtue of the implementation of the systems and methods described herein the validity of a resource can be affirmed. For example, an individual or organization can obtain an affirmation that a given resource exists, and that the resource is represented correctly. This can reduce the chances that malicious individuals (e.g., counterfeiters and / or the like) can misrepresent the existence of a given resource or state of such resource and cause one or more transitions to fraudulently be performed. Further, the presently-disclosed techniques can improve the quality of the data available for a given resource as other devices can be permitted to review the data and contribute information as to the value / state / etc., of the resources. This can reduce or eliminate the need for multiple, independent tests of samples of the resources to determine, for example, whether a given resource is represented correctly. And by virtue of theimplementation of the techniques described herein, resources can be tracked throughout their lifecycle, allowing for organization, sovereign entities, and / or the like to regulate the sale of such resources (e.g., to limit conflict-related sales of resources that are prohibited to be sold in a given country or region).

[0039] FIG. 1 shows an environment 100 configured for affirming validity of sample data representing resources, according to an embodiment. The environment 100 includes affirmation servers 102, null servers 104, publication servers 106, and a client device 108. The environment 100 can include asset databases 105a and client devices 105b (generally referred to as asset data sources 105). The components of the environment 100 can communicate with one another via one or more networks 109. In some embodiments, the affirmation server 102, null server 104, asset databases 105a, client devices 105b, publication server 106, and client device 108 can be communicative coupled to each other, either directly or indirectly, via the network 109. It will be understood that the environment 100 is not confined to the components described herein and can include additional or other components not shown for brevity, which are to be considered within the scope of the embodiments described herein.

[0040] The above-mentioned components can be connected to each other through a network 109. Examples of the network 109 can include, but are not limited to, private or public LAN, WLAN, MAN, WAN, and the Internet. The network 109 can include both wired and wireless communications according to one or more standards and / or via one or more transport mediums. Communication over the network 109 can be performed in accordance with various communication protocols such as Transmission Control Protocol and Internet Protocol (TCP / IP), User Datagram Protocol (UDP), and IEEE communication protocols. In one example, the network 109 can include wireless communications according to Bluetooth specification sets or another standard or proprietary wireless communication protocol. In another example, the network 109 can also include communications over a cellular network, including, e.g., a GSM (Global System for Mobile Communications), CDMA (Code Division Multiple Access), and / or EDGE (Enhanced Data for Global Evolution) network.

[0041] The affirmation server 102 can represent any computing device comprising a processor and a non-transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Non-limiting examples of an affirmation server 102 include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by acomputing device, and / or the like. During operation, various users (e.g., individuals engaging with the affirmation server 102 to affirm the validity or invalidity of one or more assets represented by sample data as described herein) can use the affirmation server 102 to access one or more other devices of the environment 100. In some embodiments, the affirmation server 102 can be associated with a fund hosting service that is implemented by an organization providing analytical financial services for hosting the asset-backed stability funds (ASFs). For example, the fund hosting service can configure the affirmation servers 102 to implement, for example, sovereign fund organizational models suited for, but not limited to, developing nations, investors, and development of domestic stock issuances and related market growth opportunity. In some embodiments, the affirmation servers 102 can be associated with a third- party organization that communicates with one or more other parties as described herein when affirming the validity of one or more assets as represented in, for example, a publication server 106

[0042] The affirmation server 102 can host or connect to a service database 103. The service database 103 can represent any computing device comprising a processor and a non- transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Non-limiting examples of an affirmation server 102 include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by a computing device, and / or the like. In some embodiments, the affirmation server 102 can host the ASFs on behalf of particular entities, such as nation- states, central banks, governments, and corporations, among others, and provide access to the service database 103. In some embodiments, the affirmation server 102 can function as an asset adjudication platform that obtains and evaluates sample data associated with assets as described herein. The service database 103 hosts information related to the evolution of, for example, financial holdings and natural resource reserves. The processes of the affirmation server 102 provide empirical and scientific verification, codification, valuation, and realization of value and assign such metrics to the various types of natural resources assets.

[0043] The null server 104 can represent any computing device comprising a processor and a non-transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Nonlimiting examples of the null server 104 can include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by a computing device,and / or the like that implement one or more Interplanetary file systems (IPFSs) and / or the like. During operation, the null server 104 can be configured to operate as a proxy server. In examples, the null server 104 can as an intermediary between the affirmation server 102 and one or more devices of FIG. 1 when communicating with the affirmation server 102 via the network 109. For example, the null server 104 can pass messages received from, or directed to, the affirmation server 102 to the publication server 104 when adding or updating entries in the publication server 104 as described herein. In some embodiments, the null server can be associated with an ASF as described herein.

[0044] The asset data sources 105 can include asset databases 105a and / or client devices 105b. The asset data sources 105 can represent any computing device comprising a processor and a non-transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Non-limiting examples of the asset data sources 105 (e.g., of the asset database 105a and / or the client devices 105b) can include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by a computing device, and / or the like. During operation, the asset data sources 105 can be configured to communicate with the publication server 106 to update one or more entries maintained by the publication server 106. In some embodiments, the asset data sources 105 can be associated with one or more organizations involved in determining a value for one or more of the resources represented by an entry maintained by the publication server 106 such as, for example, appraisal organizations (e.g., the Petroleum Resource Management System (PRMS), the Society of Petroleum Engineers (SPE), the US Geological Survey (USGS)), financial institutions involved in financing the sale of such resources (e.g., investment banks, brokerage firms, and / or the like), regulatory agencies of a given country or state (e.g., national or regional government or private agencies that regulate the sale of minerals or other resources), and / or the like.

[0045] The publication server 106 can represent any computing device comprising a processor and a non-transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Non-limiting examples of the publication server 106 can include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by a computing device, and / or the like. During operation, the publication server 106 can be configured to receive and / or transmit messages from the affirmation server 102, the client device 107, the disbursements portal 108 and / or the asset data sources 105. In examples, thepublication server 106 can provide access to data in a database including a plurality of entries representing a state of a given resource at a given point in time. In some embodiments, the publication server 106 can be associated with (e.g., operated at least in part by) an individual or organization that is similarly associated with the affirmation server 102.

[0046] The client device 108 can represent any computing device comprising a processor and a non-transitory, machine-readable storage medium capable of cooperating to execute instructions and perform one or more of the operations and processes described herein. Non-limiting examples of a client device 108 include workstation computers, laptop computers, phones, tablet computers, server computers, virtual machines hosted by a computing device, and / or the like. During operation, various users (e.g., individuals engaging with the client device 108 to obtain and / or update entries maintained by the publication server 106) can use the client device 108 to access websites hosted by the publication server 106. In some embodiments, the client device 108 can be operated by one or more types of end-users. For example, the client device 108 can be operated by individuals, groups of individuals (e.g., employees), and / or the like involved in managing (e.g., processing and / or selling), regulating, evaluating (e.g., valuing), and / or buying resources as represented by the entries included in the publication server 106.

[0047] In some embodiments, the client device 108 can host a unique resource identifier platform (sometimes referred to as an asset identification number or AIN) or communicate with one or more other devices of FIG. 1 (e.g., the affirmation server 102, the publication server 106, and / or the like) to establish and host the unique resource identifier platform. For example, the client device 108 can host a unique resource identifier platform that receives and maintains (e.g., registers) an index of digital holographic hallmarks, hybrid (e.g., part-digital, part physical) hallmarks, and / or a physical hallmarks. In some embodiments, the client device 108 or any other device hosting the unique resource identifier platform can receive requests for information about a resource identified by a unique resource identifier as described herein, and provide information about the unique resource identifier (e.g., a hash representing one or more aspects about the resource and / or the like) to one or more other devices (including one or more other client devices that are not explicitly illustrated) to allow organizations such as a financial system, a federal reserve system, a central bank digital proxy (CBDC) system, a virtual chimera, and / or the like to obtain information about a resource that is affirmed by the organization maintaining the unique resource identifier platform

[0048] FIG. 2 shows an example process 200 for affirming validity of sample data representing resources, according to an embodiment. In some embodiments, the techniques described with respect to the affirmation server can additionally, or alternatively, be implemented by systems controlled by institutions as described herein. In an example, for resources such as metals and / or minerals collected in repositories and managed throughout a lifecycle for that resource (e.g., through one or more stages of ISO-transitioning), an affirmation server can implement one or more of the techniques described herein to allow for the determination of a liquidity status (e.g., fractional liquidity) of the resource at one or more points in time. In this (and similar) examples, the affirmation server can generate unique resource identifiers that are the same as, or similar to, dynamically updated unique resource identifiers to index one or more ISO transitions. In examples, one or more ISO-transitions can include one or more updates to one or more resources when transitioning from a first state to a second state (e.g., in the context of oil, from crude oil to diesel fuel). These unique resource identifiers can correspond as a chimeric digital / virtual hallmark, a hybrid hallmark, a physical hallmark (e.g., a non-destructive inert add mixture chemical and molecular hallmark), and any other hallmarks. These hallmarks can be used to digitally and / or virtually stamp resources related to allow for sample data (e.g., related to financial services data) to be aggregated in a publication server and / or one or more other databases. And by virtue of the implementation of the process 200 descried herein, systems can be configured to implement a process suite to allow for a comprehensive understanding of a state of a given resource at a given point in time, regardless of whether such resource is represented physically, digitally, or in combination, as opposed to other techniques which may or may not allow for a mere accounting, asset listing, or account balance, or account item / holding under current, less granular financial, legal, and regulatory schemas.

[0049] The process 200 includes operations 202-208. However, other embodiments can include additional or alternative operations or can omit one or more operations altogether. The process 200 is described as being executed at least in part by an affirmation server that is the same as, or similar to, the affirmation server 102 described in FIG. 1. However, one or more operations of process 200 can also be executed by any number of computing devices operating in the distributed computing system described in FIG. 1. For instance, one or more computing devices (e.g., computing devices that can be the same as, or similar to, the null server 104, the publication server 106, the client device 108, and / or the asset data sources 105) can perform some or all of the operations described in FIG. 2 alone or in cooperation with oneor more other computing devices of FIG. 1. Using the methods and systems described herein, such as the process 200, the analytics server can affirm the validity of sample data representing a given resource, as described herein.

[0050] At operation 202, an affirmation server can receive sample data associated with a resource. For example, the affirmation server can receive sample data associated with one or more resources that are obtained (e.g., extracted, refined, and / or the like) at a first point in time during a period of time. In some embodiments, the resources can be extracted within at a specific location within a region. For example, the affirmation server can receive sample data based on a resource being extracted at a particular facility, or a particular region associated with one or more facilities (e.g., a region within a country and / or the like). In examples, the affirmation server can receive the sample data based on the resource being extracted such that the resource is in a first state. For example, the affirmation server can receive the sample data when the resource is initially extracted and prior to refinement of the resource or incorporation of the resource into one or more products as described herein.

[0051] In some embodiments, the affirmation server can receive the sample data based on execution of one or more operations by an analysis device. For example, an analysis device (e.g., a mass spectrometry device, an infrared spectroscopy device, and / or the like) can analyze one or more aspects of a resource extracted at a location. When analyzing the resource, the analysis device can measure the one or more physical properties of the sample of the resource and generate the at least a portion of the sample data based on the one or more physical properties of the sample. In this example, the affirmation server can receive the at least a portion of the sample data where the at least a portion of the sample data represents the resource at the first point in time. For example, the affirmation server can receive the at least a portion of the sample data from the analysis device, where the portion of the sample data is associated with one or more values measuring the one or more physical properties of the sample of the resource. In some embodiments, the one or more values measuring the one or more physical properties can represent one or more of a mass of the resource, a mass of the sample of the resource, a molecular weight of the resource, a molecular weight of the sample of the resource, and / or the like.

[0052] In some embodiments, the affirmation server can receive the sample data, where the sample data includes an identifier associated with an owner of the resource. For example, an organization involved in extracting the resource can perform one or more initialmeasurements using the analytics device. In this example, the organization can provide input via a client device (e.g., that is the same as, or similar to, the client device 108 of FIG. 1) indicating an identifier associated with an owner of the resource and / or the sample data. The identifier can include a network identifier that is associated with a device that generated the sample data. For example, the network identifier (e.g., an IP address) can represent a location at which the resource was generated and / or at which the sample was analyzed.

[0053] At operation 204, the affirmation server can determine an attribute profile for the resource based on the sample data. For example, the affirmation server can receive and / or generate the sample data, where the sample data represents one or more samples of one or more corresponding resources. In this example, the affirmation server can determine an attribute profile for each of the one or more resources. The affirmation server can generate the attribute profiles for each resource based on the sample data, where each attribute profile includes an entry and is configured to include a plurality of sub-entries. For example the affirmation server can generate the attribute profile where each entry includes sub-entries corresponding to the physical properties and / or identifiers represented by the sample data. In one example, an entry can include a sub-entry that identifies a type of a first resource (e.g., gold, silver, titanium, and / or the like), and a sub-entry that identifies one or more physical properties of the first resource (e.g., a mass, a molecular weight, and / or the like). In examples, the entry can additionally, or alternatively, include an identifier of an owner or an organization that extracted the first resource. The identifier of the owner or the organization can include a direct identifier (e.g., an organization identifier such as an address and / or the like) and / or an indirect identifier (e.g., a location, a location derived from the network identifier associated with the analysis device that generated the sample data, and / or the like).

[0054] In some examples, as the resource is tracked by the affirmation server over time (e.g., when transitioning from state to state throughout the lifecycle of the resource), the affirmation server can add one or more sub-entries. For example, the affirmation server can track data received from one or more devices of FIG. 1 and add one or more sub-entries based on the data received from the one or more devices. As described herein, this data can include additional sample data (e.g., representing states of resources as indicated by the International Organization for Standardization (ISO) or any similar standard setting organization or group managing one or more transitioning indexes) and / or attribute data associated with one or more attributes (e.g., a value such as a monetary value attributed to the resource based on analysisby one or more asset data sources that are the same as, or similar to, the asset data sources 105 of FIG. 1)

[0055] In some embodiments, the affirmation server can dynamically track one or more resources over time. For example, the affirmation server can dynamically track one or more resources using one or more unique resource identifiers as described herein. In this example, the affirmation server can track the one or more resources through one or more ISO-transitions and escribed herein. This can allow the affirmation server to track an evolutionary path for the resource and provide information to one or more other computing devices representing this evolutionary path.

[0056] In some embodiments, the affirmation server can implement one or more neural networks to process the sample data and / or data associated with one or more entries. For example, the affirmation server can provide entry data associated with one or more entries (including one or more sub-entries) to a neural network. In this example, the neural network can be configured to receive the entry data and generate an output, the output including revised entry data. In an example, the revised entry data can include the one or more sub-entries, where values represented by the one or more sub-entries are normalized. Where a plurality of analysis devices are used to generate sample data for a plurality of samples, the affirmation server can provide portions of the sample data (e.g., sequentially) to the neural network to cause the neural network to generate the output. The affirmation server can then update the one or more entries such that one or more values are updated to represent normalized values. In this way, the affirmation server can update entries (including one or more sub-entries) so as to allow one or more asset data sources to accurately determine values for resources while controlling for known variations in the ways in which the resources are represented.

[0057] In some embodiments, the affirmation server can train the neural network to receive the entry data as an input and output the revised entry data. For example, the affirmation server can provide entry data including one or more sub-entries that are not normalized to the neural network to cause the neural network to generate the revised entry data. The affirmation server can then compare the revised entry data to ground truth data, where the ground truth data is associated with a set of values corresponding to sub-entries that are known to be normalized. The affirmation server can then adjust the weights of the neural network and iteratively repeat the above-described process until the model converges (e.g., the values of the sub-entries represented by the revised entry data differ from the values of the sub-entries of theground truth data by less than a threshold amount). In this way, the affirmation server can be configured to receive data from a diverse set of sources and normalize the data based on, for example, known aspects of one or more regions from which the resources are being obtained such that the resource can be compared to other resources from other regions.

[0058] At operation 206, the affirmation server can generate a unique resource identifier (e.g., an asset identification number (AIN)) for a resource in response to determining that the sample data is valid. For example, the affirmation server can generate a unique resource identifier for each resource. In some embodiments, the affirmation server can generate the unique resource identifier based on the sample data. In some examples, the affirmation server can generate the unique resource identifier based on the sample data and map the sample data to the resource using the unique resource identifier. In these examples, the affirmation server can store the sample data in association with the unique resource identifier in a database maintained by the affirmation server such as a service database (e.g., that is the same as, or similar to, the service database 103).

[0059] In some embodiments, the affirmation server can generate the unique resource identifier for the resource at a first point in time. For example, the affirmation server can generate the unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile for the resource at that first point in time. In some examples, the affirmation server can generate the unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile for the resource at that first point in time and at one or more times prior to the first point in time. In these examples, the affirmation server can iteratively update the entry corresponding to the resource such that the sample data and / or one or more or more unique resource identifiers are stored in association with one another in the service database. In this way, the affirmation server can generate and maintain a ledger that tracks the resource as the resource is analyzed and processed throughout the lifecycle of the resource.

[0060] In some embodiments, the affirmation server can dynamically generate a unique resource identifier. For example, the affirmation server can receive input (e.g., via an analysis device, a keyboard or mouse, and / or the like) identifying one or more features of a digital, hybrid, or physical holographic hallmark. Examples of holographic hallmarks can include an inert materials (e.g., palladium, copper, silver, and / or the like when hallmarking a rare earth metal such as gold), microtags, or nanotags (e.g., when hallmarking oil to identify a particularrefinery the oil was extracted or refined by), colorants or dyes (e.g., when hallmarking fluids), morphological, molecular, and / or physical hallmarks, and / or the like that are introduced to the resource. In this way, the affirmation server can track one or more aspects involved in creating a unique resource identifier to allow any organizations such as a financial system, a federal reserve system, a central bank digital proxy (CBDC) system, a virtual chimera, and / or the like to obtain information about a resource that is affirmed by the organization maintaining the unique resource identifier platform. In some embodiments, the input can be associated with ongoing unique resource identifier transitioning variants (e.g., predetermined sequences of changes that are made to such unique resource identifiers that indicate a progression of a resource through stages of a lifecycle for that resource).

[0061] In some embodiments, the affirmation server can generate the unique resource identifier to affirm validity of a resource represented by sample data. For example, the affirmation server can generate the unique resource identifier to affirm the validity of the resource represented by the sample data to indicate (e.g., through a digital certification) that the resource is valid or not valid. In one example, the affirmation server can generate the unique resource identifier based on the affirmation server executing one or more operations involved in generating a hash based on the sample data. In this example, the affirmation server can execute the one or more operations based on the sample data and / or the attribute profile and generate a hash representing the sample data and / or the attribute profile. In this example, the affirmation server can include the unique resource identifier with the sample data and maintain the unique resource identifier in the service database. In this way, the affirmation server can receive requests for the unique resource identifier (e.g., from client devices that are controlled by parties involved in buying or selling resources as described herein) and provide the unique resource identifier to affirm the validity of sample data for a given resource.

[0062] At operation 208, the affirmation server can transmit the sample data and the unique resource identifier to a remote device. For example, the affirmation server can transmit the sample data and the unique resource identifier to one or more devices of FIG. 1. In some embodiments, the affirmation server can provide the sample data and the unique resource identifier to a publication server (e.g., that is the same as, or similar to, the publication server 106 of FIG. 1). In this example, the affirmation server can transmit the sample data and the unique resource identifier to cause the publication server to provide (e.g., make available) the sample data and the unique resource identifier upon request. In some examples, the affirmation server can transmit the sample data and the unique resource identifier to one or more devicesof FIG. 1 in response to the affirmation server receiving requests by the one or more devices for the sample data and the unique resource identifier.

[0063] In some embodiments, the affirmation server can transmit the sample data and the unique resource identifier where the unique resource identifier includes an affirmation instruction. For example, the affirmation server can transmit the sample data and the unique resource identifier based on the affirmation server configuring the unique resource identifier to include the affirmation instruction. In this example, the affirmation instruction can indicate a status of the attribute profile of a given resource as represented by the sample data and the unique resource identifier. For example, the affirmation instruction can identify a hashing algorithm that can be used by a device requesting affirmation of a resource to hash one or more aspects of the sample data to determine the unique resource identifier. In other examples, the affirmation instruction can include an identifier that can be transmitted to the affirmation server to affirm that the sample data and the unique resource identifier is valid. For example, the affirmation instruction can include an identifier of the affirmation server to indicate that the affirmation server is monitoring the resource during the lifecycle of the resource. In this example, the identifier can be used by one or more other device (e.g., the asset data sources) when reviewing sample data obtained from the publication server to affirm via the affirmation server (e.g., using an out-of-band communication connection) that the sample data is valid (e.g., not tampered with and / or the like).

[0064] In some embodiments, the affirmation server can transmit the sample data and the unique resource identifier to a broadcasting device to cause the sample data and the unique resource identifier to be stored in an entry of a database managed by the broadcasting device. For example, the affirmation server can transmit the sample data and the unique resource identifier to the publication server to cause the sample data and the unique resource identifier to be stored in an entry of a database managed by the publication server. By transmitting the sample data and the unique resource identifier to the broadcasting device, the affirmation server can configure the publication server to make available the sample data and the unique resource identifier to one or more other devices (e.g., the client devices 108 and / or the asset data sources 105) to verify that the resources represented by entries maintained by the publication server are affirmed at various points in time throughout the lifecycle of the resource.

[0065] In some embodiments, the affirmation server can configure the broadcasting device to maintain an index of sub-entries corresponding to the entry. For example, theaffirmation server can configure the broadcasting device to maintain the index of sub-entries based on execution of one or more operations involving the sample data and the unique resource identifier by one or more monitoring devices when evaluating the state of the resource. These monitoring devices can include the affirmation server, the asset data sources, and / or the like. In some embodiments, the affirmation server can configure the broadcasting device to maintain and index the sub-entries corresponding to the entry, where the index of sub-entries are provided to one or more monitoring devices to allow the execution of one or more operations by the one or more monitoring devices. In an example, where one or more client devices of the asset data sources obtain one or more sub-entries of a given entry maintained in the index of the broadcasting device, the one or more monitoring devices can analyze the subentries representing the resource. In this example, the one or more client devices can determine one or more aspects of the resource (e.g., a value for the resource when in the state as represented and affirmed by the sample data and the unique resource identifier and / or the like). The publication server can then receive update data associated with the one or more aspects of the resource determined by the monitoring devices and update (e.g., add) one or more subentries representing the one or more aspects as determined by the monitoring device. In an example where the updates include values for the resource at a given potin in time, the publication server can then provide the sub-entries representing the values for the resource to allow one or more other devices (e.g., the affirmation server and / or one or more other client devices of the asset data sources) to determine a final value for the resource at a given point in time. In this way, the affirmation server can configure the publication server to maintain an index of values that are calculated by a variety of monitoring devices to arrive at a determined final value for a given resource at a given point in time.

[0066] FIG. 3A-3C show an example implementation 300 of a process for affirming validity of sample data representing resources, according to an embodiment. The implementation 300 includes operations 310-326. However, other embodiments can include additional or alternative operations or can omit one or more operations altogether. The implementation 300 is described as being executed at least in part by an affirmation server 302 that is the same as, or similar to, the affirmation server 102 described in FIG. 1. However, one or more operations of implementation 300 can also be executed by any number of computing devices operating in the distributed computing system described in FIG. 1. For instance, one or more computing devices (e.g., computing devices that can be the same as, or similar to, the null server 104, the publication server 106, the client device 108, and / or the asset data sources105) can perform some or all of the operations described in FIG. 4 alone or in cooperation with one or more other computing devices of FIG. 1. Using the methods and systems described herein, such as the implementation 300, the analytics server can affirm the validity of sample data representing a given resource, as described herein.

[0067] At operation 310, a client device 308 can receive input from a user indicating a set of resources obtained from a site. For example, in the context of oil extraction and refinement, the client device 308 can receive input from an operator of an oil extraction facility. In this example, the operator can cause an analysis device 308a to process one or more samples of the oil to indicate one or more physical properties of the oil. The operator can then provide input to the client device 308 indicating the one or more physical properties and / or one or more additional aspects regarding the oil that was sampled and tested. For example, the operator can provide information regarding the facility at which the oil was extracted, a total volume of oil extracted for a period of time (e.g., a day, a week, and / or the like).

[0068] At operation 312, when receiving the input from the operator, the client device 308 can iteratively generate data associated with an index that represents each resource at a given point in time. For example, on a first day (Day 1), the client device 308 can receive input indicating a resource (Xi) and one or more properties of the resource such as a unit of mass, a molecular weight, an owner of the resource, and a location of the resource at the point at which it was initially obtained or sampled. The client device 308 can iteratively repeat this process for a number of times. In some embodiments, the client device 308 can iteratively generate the data associated with the index such that the data represents one or more hallmark identifiers (Hallmark ID (HHI)). The hallmark identifiers can represent one or more aspects of a hallmark associated with a given resource as described herein.

[0069] At operation 314, the client device 308 can provide the data associated with the index to the affirmation server 302. For example, the client device 308 can provide the data associated with the index to the affirmation server 302, where the data associated with the index includes sample data representing one or more aspects of the resources included in the index.

[0070] At operation 316 the affirmation server 302 can obtain additional information associated with the client device 308 based on (e.g., in response to) the affirmation server 302 receiving the data associated with the index. For example, the affirmation server 302 can obtain information such as a static or dynamic IP address for the client device 308, a timestamp at which the data was transmitted, and / or the like.

[0071] At operation 318, the affirmation server 302 can generate a unique resource identifier such as an asset identification number (AIN). For example, the affirmation server 302 can generate the unique resource identifier based on one or more hash algorithms. In this example, the affirmation server 302 can generate a hash value (e.g., a checksum and / or the like) based on one or more aspects of the data associated with the index. In examples, the affirmation server 302 can generate the hash value based on information obtained regarding the client device 308 such as the IP address of the client device 308 and / or the like. The affirmation server 302 can then store the unique resource identifier in a ledger maintained by the affirmation server 302.

[0072] In some embodiments, the affirmation server 302 can implement a neural network to normalize one or more values represented by the data associated with the index. For example, the affirmation server 302 can implement the neural network to normalize one or more values to control for location-based or organization-based variation in measurements of samples. In one example, where measurements are collected in a first unit (e.g., joules) the affirmation server 302 can implement the neural network to normalize the one or more values to correspond to a second unit (e.g., a British thermal unit). In this way, the affirmation server 302 can allow one or more other devices as described to accurately compare the resources represented by the index.

[0073] At operation 320, the affirmation server 302 can anonymize portions of the index. For example, the affirmation server 302 can replace a unique identifier (e.g., a business entity name, a tax identification number, a business registration number, and / or the like) with a pseudo-identifier (e.g., a random number, a number determined based on a hash of one or more values representing the organization such as the unique identifier, and / or the like). In this example, the affirmation server 302 can maintain a mapping and provide the unique identifier to one or more devices upon request when authorized to receive such information.

[0074] At operation 322, the affirmation server 302 can provide the data associated with the anonymized index for publication. For example, the affirmation server 302 can provide the data associated with the anonymized index for publication to a publication server 306. In this example, the publication server 306 can be configured to store the data associated with the anonymized index as one or more entries in a database maintained by the publication server 306. In some embodiments, the publication server 306 can be associated with (e.g., owned by and / or regulated by) one or more entities such as a sovereign entity and / or the like.

[0075] At operation 326, the publication server 306 can communicate with one or more servers 305 that are part of an asset data source (e.g., that is the same as, or similar to, the asset data sources 105 of FIG. 1). For example, the publication server 306 can communicate with the one or more servers 305 to affirm one or more aspects of the resources as represented by the anonymized index. Affirmation can include obtaining a binary indication of whether entry data representing a given resource or set of resources is accurate. Additionally, or alternatively, affirmation can include obtaining a binary indication of whether the representation of the resource is possible (e.g., whether one or more physical properties of a given resource are similar to representative physical properties of the given resource that were affirmed at an earlier point in time). In some embodiments, the publication server 306 can communicate with the one or more servers 305 to obtain information regarding one or more aspects about the resources in the anonymized index. For example, the publication server 306 can servers 305 to obtain a value for the resources based on a time at which the resources were obtained as represented by the anonymized index, a state of the resources as represented by the anonymized index, and / or the like.

[0076] FIG. 4 is a flow diagram of a process 400 for affirming validity of sample data representing resource, according to an embodiment. The process 400 includes operations 402- 410. However, other embodiments can include additional or alternative operations or can omit one or more operations altogether. The process 400 is described as being executed at least in part by an affirmation server that is the same as, or similar to, the affirmation server 102 described in FIG. 1. However, one or more operations of process 400 can also be executed by any number of computing devices operating in the distributed computing system described in FIG. 1. For instance, one or more computing devices (e.g., computing devices that can be the same as, or similar to, the null server 104, the publication server 106, the client device 108, and / or the asset data sources 105) can perform some or all of the operations described in FIG. 4 alone or in cooperation with one or more other computing devices of FIG. 1. Using the methods and systems described herein, such as the process 400, the analytics server can affirm the validity of sample data representing a given resource, as described herein

[0077] At operation 402, an affirmation server (e.g., that is the same as, or similar to, the affirmation server 102 of FIG. 1) can generate a plurality of entries to include in a database, each entry corresponding to a resource. For example, the affirmation server can receive sample data associated with one or more resources from one or more devices (e.g., such as asset data sources 105 and / or client devices 108 of FIG. 1). In this example, the affirmation server cananalyze the sample data corresponding to each resource and generate one or more entries. In some embodiments, each entry can be associated with one or more sub-entries. For example, each entry can include one or more sub-entries representing one or more aspects of the respective resources at a given point in time. As described herein, each entry can represent one or more aspects of the respective resources in one or more states of the resource throughout the lifecycle of the resource.

[0078] In some embodiments, the affirmation server can receive sample data associated with a plurality of resources. For example, the affirmation server can receive the sample data associated with the plurality of resources from one or more client devices (e.g., that are the same as, or similar to, the client device 108 of FIG. 1) and / or asset data sources (e.g., that are the same as, or similar to, the asset data sources 105 of FIG. 1). In this example, the affirmation server can receive the sample data based on the client devices analyzing at least a portion of the resource using an analysis device (as described herein) to determine one or more physical properties of the resource. The sample data can be generated based on one or more operations performed by the analysis device (e.g., the generation of sensor data by one or more sensors of the analysis device) when analyzing the sample to determine the one or more physical properties of the sample of the resource. Additionally, or alternatively, the affirmation server can receive the sample data based on the asset data sources analyzing the sample data (alone or in combination with a unique resource identifier) as described above with respect to FIG. 2. As will be understood, the sample data can represent the various resources when in one or more states throughout the lifecycle of the resources.

[0079] In some embodiments, the affirmation server can receive the sample data and determine an identifier associated with a client device involved in processing each entry of the plurality of entries. For example, the affirmation server can receive the sample data and determine the identifier of the device that initially processed the sample to generate at least a portion of the sample data for each resource. In this example, the analysis device can determine a pseudo-identifier that maps to the identifier. For example, the analysis device can determine a pseudo-identifier that maps to the identifier and the affirmation server can replace the identifier included in the respective entry with the pseudo-identifier. In this example, the analysis device can then remove the identifier associated with the client device from each respective entry when published by the publication server. In this way, the affirmation server can at least partially anonymize a device and / or an organization involved in extracting and / oranalyzing the samples of the resources from one or more other client devices involved in evaluating and attributing a value to the resource as described herein.

[0080] At operation 404, the affirmation server can provide entry data associated with the first set of entries to a first server and a second server. For example, the affirmation server can provide the entry data associated with the first set of entries to a first server and a second server that are implemented as client devices of an asset data source (e.g., that is the same as, or similar to, the asset data sources 105 of FIG. 1). In some embodiments, the affirmation server can provide the entry data to the first server and the second server based on (e.g., in response to) the affirmation server receiving requests for the first set of entries from the first server and the second server. For example, as sample data for various resources is analyzed and included as entries by the affirmation server (e.g., in a publication server and / or the like), the first server and the second server can send requests for the affirmation data stored by the affirmation server. In this example, the entry data requested by the first server and the second server can be further associated with a plurality of sub-entries. For example, the entry data can include a plurality of sub-entries where each sub-entry is associated with one or more aspects representing the respective resource at a point in time (e.g., within a period of time) and when in a given state.

[0081] At operation 406, the affirmation server can receive, from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry. For example, the affirmation server can receive the initial attribute data from the first server based on the affirmation server providing the entry data to at least the first server and the second server. In some examples, the initial attributes can represent one or more values attributed to the resources. For example, the first server and the second server can each determine a value for the resource as represented by a respective entry, and provide the initial attribute data to be included with the entry data (e.g., in the publication server). In this example, the value can be determined based on input provided by one or more users operating the first server and the second server respectively.

[0082] In some embodiments, the affirmation server can update the entry data based on the initial attribute data. For example, the affirmation server can monitor the entry data (e.g., stored in the publication server) and update the entry data as the initial attribute data is obtained and stored as sub-entries for the respective entries. In some embodiments, the affirmation server can update the entry data to set a value for an attribute such as the price of the resourceat the point in time. For example, where the first server and the second server both provide initial attribute data specifying a price at which the users of the first server and the second server set for the resources included in the entry data, the affirmation server can determine a price (e.g., a global price) for the resources. In this example, the affirmation server can select one or more of the initial attributes (e.g., a price set by the first server or the second server). In other examples, the affirmation server can determine the initial attributes based on the initial attributes received from the first server and the second server. In these examples, the affirmation server can determine an average value and / or the like based on the initial values set by the first server and the second server. The affirmation server can then include a sub-entry in the entry data corresponding to each resource, the sub-entry representing the attribute as determined by the affirmation server.

[0083] At operation 408, the affirmation server can determine an intermediate attribute corresponding to each sub-entry of the set of entries. For example, the affirmation server can determine the intermediate attribute based on the affirmation server determining that a status of a resource represented by an entry in the entry data has changed. In this example, the affirmation server can determine that the status of the resource has changed such that the resource transitioned from a first state to a second state. Transitions of the resource from the first state to the second state can include movement of the resource (e.g., from one location to another location), refinement of the resource (e.g., extracting unrefined oil and processing the unrefined oil to generate one or more oil products such as gasoline, diesel fuel, and / or the like), incorporation of the resource into one or more items (e.g., incorporation of gold or silver into one or more computing device components and / or the like), and / or the like. While the present disclosure discusses the determination of a single intermediate attribute, the affirmation server can determine one or more intermediate attributes iteratively as respective resources transition from state to state.

[0084] In some embodiments, the transition of a resource can be associated with a point in time. For example, the transition of a resource from the first state to the second state can be associated with a point in time where the resource is managed by (e.g., in the custody of) one or more individuals or organizations. In an example, where unrefined oil is being refined into one or more oil products, the unrefined oil can be associated with a first point in time and the refined oil products (e.g., gasoline, diesel fuel, and / or the like) can be associated with a second point in time. In some embodiments, the transition of a resource can be associated with a period of time. For example, where a resource is brought to a first location and / or region for a firstperiod of time to be refined, and to a second location and / or region for a second period of time to be incorporated into one or more products, the transition from refinement to incorporation into one or more products can each be associated with respective periods of time.

[0085] In some embodiments, the affirmation server can update the entry data for a given resource based on the state of a given resource at a given point in time. For example, the affirmation server can receive status data indicating that at least one resource transitioned from a first state to a second state. In this example, the affirmation server can provide the status data to the first server and the second server that generated the initial attribute data for the resource. The affirmation server can provide the status data to the first server and the second server to indicate to the first server and the second serve that the resource can be reevaluated to attribute an updated price to the resource. In examples, the affirmation server can then receive second attribute data from the first server and / or the second server respectively, the second attribute data representing one or more second intermediate attributes of the resource. The second intermediate attributes can include one or more attributes that are the same as, or similar to, the initial attributes. For example, the second intermediate attributes can include values attributed to a given resource represented by an entry in the entry data.

[0086] At operation 410, the affirmation server can update the plurality of entries based on the intermediate attribute and / or the second intermediate attributes corresponding to each entry of the set of entries. For example, the affirmation server can update the plurality of entries and include respective sub-entries with each entry of the plurality of entries. In this example the affirmation server can determine one or more values to associate with the sub-entries. For example, where a plurality of values are represented by the initial attribute, the intermediate attribute, and / or the second intermediate attribute, the affirmation server can determine a final value for the given resource at a given point in time and add the final value as a sub-entry to the plurality of entries.

[0087] In some embodiments, the affirmation server can determine a co-liquidity value based on the entries of the publication server. For example, the affirmation server can determine a co-liquidity value, where the co-liquidity value represents a value for a given resource remaining in the lifecycle of the resource. In some embodiments, the affirmation server can determine the co-liquidity value for a given resource based on the presence of one or more similar resources in the publication server. For example, in the context of refining oil, the affirmation server can determine that a certain number of resources correspond to oil for agiven country and that the oil is in one or more states within a lifecycle for the resource. In this example, the affirmation server can determine a value attributed to the oil at each stage of the oil lifecycle such as a value for unrefined oil, a value for gasoline, a value for diesel fuel, and / or the like. The value attributed to the oil at each stage of the oil lifecycle can be represented as a value at a given point in time (e.g., a snapshot). This co-liquidity data can then be provided to one or more devices (e.g., one or more devices of FIG. 1), where the co-liquidity data is associated with the value of the resource (e.g., the oil) at a point in time.

[0088] The co-liquidity data can be analyzed to determine a market value for the resource at various stages and at various points in time. For example, the co-liquidity data can be provided to one or more client devices (e.g., that are the same as, or similar to, the client device 108 of FIG. 1) to allow the client devices to determine a value for the resources. In an example, where the resource includes oil and is represented as being in either one of two states (e.g., unrefined or refined), the client device can obtain the co-liquidity data and determine a value for all of the oil available from a given organization (e.g., an oil refiner) a given region (e.g., an area where oil is extracted), a given country, and / or the like. The client device can then execute one or more operations based on the co-liquidity data. For example, the client device can affirm that the co-liquidity data is correct by establishing a communication connection with the affirmation server to affirm that a set of unique resource identifiers are accurate (e.g., that the affirmation server affirms the validity of the resources as represented in association with the unique resource identifiers in the publication server). The client device can then execute one or more additional operations associated with, for example, providing financial services to one or more parties involved in processing and / or selling / purchasing the resource. In this way, the affirmation server can affirm that entries in a database representing one or more resources are valid and allow one or more other devices to derive information from the entry data of the database (e.g., an amount by which a loan can be drawn against the resource as represented in the publication server) when, for example, providing financial services.

[0089] In some embodiments, the affirmation server can determine an amount of additional liquidity that is available without affecting one or more market conditions such that a value measuring the market condition exceeds or deviates by a predetermined amount. For example, the affirmation server can determine an amount of additional liquidity that can be provided (e.g., by one or more financial institutions, one or more government agencies, and / or the like) based on the value attributed to various resources as represented by a publication server.

[0090] FIGS. 5A-5D show an example implementation 500 of a process for affirming validity of sample data representing resources, according to an embodiment. The implementation 500 includes operations 530-542. However, other embodiments can include additional or alternative operations or can omit one or more operations altogether. The implementation 500 is described as being executed at least in part by an publication server 506 that is the same as, or similar to, the publication server 106 described in FIG. 1. However, one or more operations of implementation 500 can also be executed by any number of computing devices operating in the distributed computing system described in FIG. 1. For instance, one or more computing devices (e.g., computing devices that can be the same as, or similar to, the null server 104, the publication server 106, the client device 108, and / or the asset data sources 105) can perform some or all of the operations described in FIG. 4 alone or in cooperation with one or more other computing devices of FIG. 1. Using the methods and systems described herein, such as the implementation 500, the analytics server can affirm the validity of sample data representing a given resource, as described herein.

[0091] At operation 530, the publication server 506 can communicate with one or more servers 505a-505n (collectively referred to as servers 505). For example, the publication server 506 can communicate with one or more servers 505 to provide entry data associated with one or more entries representing resources at points in time (e.g., a first day (Day 1), a second day (Day 2), and a third day (Day 3)).

[0092] At operation 532a-532n, the servers 505 can each determine a value for each resource. For example, the servers 505 can each determine a market value for the resource in the state at which the resource is represented at the point in time at which the resource is represented and / or at which the information is obtained by the servers 505 from the publication server 506. The servers 505 can then communicate the market value for the resource to the publication server 506 to cause the publication server 506 to store and / or publish the value for one or more other devices to obtain when evaluating the resources.

[0093] At operation 534, the publication server 506 can update aggregate values for each entry of the index. For example, the publication server 506 can update the aggregate value for each entry based on the information obtained from the servers 505 (e.g., at operations 532a- 532n). In this example, the publication server 506 can determine an aggregate value at one or more points in time (e.g., time T=0, T=l, and / or the like). In other examples, the publicationserver can store a plurality of entries for each resource indicating values that were provided by the servers 505.

[0094] At operation 536, the publication server 506 can communicate with the servers 505 to provide entry data associated with one or more entries representing resources at points in time as well as the aggregate value for the resources determined by the publication server 506. For example, the publication server 506 can communicate with the servers 506 to allow the servers to determine values for the resources at point in time subsequent to the initial point in time (e.g., at times T=l, T=2, and / or the like.

[0095] At operation 538a-538n, the servers 505 can each determine a value for each resource. For example, the servers 505 can each determine a market value for the resource in the state at which the resource is represented at the point in time at which the resource is represented and / or at which the information is obtained by the servers 505 from the publication server 506. The servers 505 can then communicate the market value for the resource to the publication server 506 to cause the publication server 506 to store and / or publish the value for one or more other devices to obtain when evaluating the resources.

[0096] At operation 540, the publication server 506 can update aggregate values for each entry of the index. For example, the publication server 506 can update the aggregate value for each entry based on the information obtained from the servers 505 (e.g., at operations 538a- 538n) Similar to operation 536, the publication server 506 can determine an aggregate value at one or more points in time (e.g., time T=1 and / or the like). In other examples, the publication server can store a plurality of entries for each resource indicating values that were provided by the servers 505.

[0097] At operation 542, the publication server 506 can transmit an indication of an affirmation to a client device 508. For example, the publication server can transmit the indication of the affirmation to the client device 508 where the client device 508 is associated with one or more buyers, sellers, financial institutions, and / or the like that can be involved in trades of the resources. The indication can include, for example, a hash value that can be compared to a value as represented by a seller (e.g., when a buyer or financial institution is contemplating exchanging value for the resource (or a portion thereof). In this way, the publication server 506 can affirm the validity of a given resource without the buyer or financial institution necessarily needing to physically test a sample of the resource. Additionally, or alternatively, where the client device 508 is operated by sovereign entity (e.g., a country, aregulatory agency of a country, and / or the like) the client device 508 can obtain the indication of the affirmation and determine whether to participate in one or more financial operations (e.g., setting tax rates and / or tariffs for the resource, implementing monetary expansion, increasing a money supply of a given country, and / or the like).

[0098] All of the processes described herein can be embodied in, and fully automated, via software code modules executed by a computing system that includes one or more computers or processors. The code modules can be stored in any type of non-transitory computer-readable medium or other computer storage device. Some or all the methods can be embodied in specialized computer hardware.

[0099] Many other variations than those described herein will be apparent from this disclosure. For example, depending on the embodiment, certain acts, events, or functions of any of the algorithms described herein can be performed in a different sequence or can be added, merged, or left out altogether (for example, not all described acts or events are necessary for the practice of the algorithms). Moreover, in certain embodiments, acts or events can be performed concurrently, for example, through multi -threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially. In addition, different tasks or processes can be performed by different machines and / or computing systems that can function together.

[0100] The various illustrative logical blocks, modules, and engines described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a processing unit or processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A processor can be a microprocessor, but in the alternative, the processor can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor can include electrical circuitry configured to process computer-executable instructions. In another embodiment, a processor includes an FPGA or other programmable device that performs logic operations without processing computer-executable instructions. A processor can also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily withrespect to digital technology, a processor can also include primarily analog components. For example, some or all of the signal processing algorithms described herein can be implemented in analog circuitry or mixed analog and digital circuitry. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.

[0101] Conditional language such as, among others, “can,” “could,” “might” or “can,” unless specifically stated otherwise, are understood within the context as used in general to convey that certain embodiments include, while other embodiments do not include, certain features, elements and / or steps. Thus, such conditional language is not generally intended to imply that features, elements and / or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and / or steps are included or are to be performed in any particular embodiment.

[0102] Disjunctive language such as the phrase “at least one of X, Y, or Z,” unless specifically stated otherwise, is understood with the context as used in general to present that an item, term, etc., can be either X, Y, or Z, or any combination thereof (for example, X, Y, and / or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.

[0103] Any process descriptions, elements or blocks in the flow diagrams described herein and / or depicted in the attached figures should be understood as potentially representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or elements in the process. Alternate implementations are included within the scope of the embodiments described herein in which elements or functions can be deleted, executed out of order from that shown, or discussed, including substantially concurrently or in reverse order, depending on the functionality involved as would be understood by those skilled in the art.

[0104] Unless otherwise explicitly stated, articles such as “a” or “an” should generally be interpreted to include one or more described items. Accordingly, phrases such as “a device configured to” are intended to include one or more recited devices. Such one or more recited devices can also be collectively configured to carry out the stated recitations. For example, “aprocessor configured to carry out recitations A, B and C” can include a first processor configured to carry out recitation A working in conjunction with a second processor configured to carry out recitations B and C.

[0105] Some embodiments of the present disclosure are described herein in connection with a threshold or a range of thresholds. As described herein, satisfying a threshold can refer to a value being greater than the threshold, more than the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, fewer than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, and / or the like.

[0106] It should be emphasized that many variations and modifications can be made to the above-described embodiments, the elements of which are to be understood as being among other acceptable examples. All such modifications and variations are intended to be included herein within the scope of this disclosure.

Claims

CLAIMSWhat is claimed is:

1. A system for affirming validity of sample data representing resources extracted at one or more locations, the system comprising: one or more processors configured to: receive sample data associated with a resource, the sample data collected at a first point in time; determine at attribute profile for the resource based on the sample data; in response to determining that the sample data is valid, generate a unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile, the unique resource identifier affirming validity of the resource represented by the sample data; and transmit the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier comprising an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

2. The system of claim 1, wherein the one or more processors configured to receive the sample data are configured to: receive the sample data based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource.

3. The system of claim 2, wherein the one or more processors configured to receive the sample data are configured to: receive values indicating one or more of: a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated.

4. The system of claim 1, wherein the one or more processors configured to determine an attribute profile for the resource based on the sample data are configured to: transmit the sample data as an input to a neural network to cause the neural network to generate an output, the output comprising one or more aspects of the resource; and determine the attribute profile based on the one or more aspects of the resource.

5. The system of claim 1, wherein the one or more processors configured to receive the sample data are configured to: receive a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sample data, and wherein the one or more processors are further configured to: determine that the sample data is valid based on at least one aspect of the attribute profile.

6. The system of claim 1, wherein the one or more processors configured to generate the unique resource identifier for the resource are configured to: execute one or more operations involved in generating a hash based on the sample data and the attribute profile; and determine the unique resource identifier based on the hash.

7. The system of claim 1, wherein the one or more processors configured to transmit the sample data and the unique resource identifier to the remote device are configured to: transmit the sample data and the unique resource identifier to a broadcasting device to cause the sample data and the unique resource identifier to be stored in an entry of a database associated with the broadcasting device; and configure the broadcasting device to maintain an index sub-entries corresponding to the entry, the index of sub-entries provided to the broadcasting device based on execution of one or more operations involving the sample data and the unique resource identifier by one or more monitoring devices.

8. A method for affirming validity of sample data representing resources extracted at one or more locations, the method comprising: receiving, by one or more processors, sample data associated with a resource, the sample data collected at a first point in time; determining, by the one or more processors, at attribute profile for the resource based on the sample data; in response to determining that the sample data is valid, generating, by the one or more processors, a unique resource identifier for the resource at the first point in time basedon the sample data and the attribute profile, the unique resource identifier affirming validity of the resource represented by the sample data; and transmitting, by the one or more processors, the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier comprising an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

9. The method of claim 8, wherein receiving the sample data comprises: receiving, by the one or more processors, the sample data based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource.

10. The method of claim 9, wherein receiving the sample data comprises: receiving, by the one or more processors, values indicating one or more of: a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated.

11. The method of claim 8, wherein determining an attribute profile for the resource based on the sample data comprises: transmitting, by the one or more processors, the sample data as an input to a neural network to cause the neural network to generate an output, the output comprising one or more aspects of the resource; and determining, by the one or more processors, the attribute profile based on the one or more aspects of the resource.

12. The method of claim 8, wherein receiving the sample data comprises: receiving, by the one or more processors, a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sample data, the method further comprising: determining, by the one or more processors, that the sample data is valid based on at least one aspect of the attribute profile.

13. The method of claim 8, wherein generating the unique resource identifier for the resource comprises: executing, by the one or more processors, one or more operations involved in generating a hash based on the sample data and the attribute profile; and determining, by the one or more processors, the unique resource identifier based on the hash.

14. The method of claim 8, wherein transmitting the sample data and the unique resource identifier to the remote device comprises: transmitting, by the one or more processors, the sample data and the unique resource identifier to a broadcasting device to cause the sample data and the unique resource identifier to be stored in an entry of a database associated with the broadcasting device; and configuring, by the one or more processors, the broadcasting device to maintain an index sub-entries corresponding to the entry, the index of sub-entries provided to the broadcasting device based on execution of one or more operations involving the sample data and the unique resource identifier by one or more monitoring devices.

15. A non-transitory, computer-readable medium storing instructions thereon that, when executed by one or more processors, cause the one or more processors to receive sample data associated with a resource, the sample data collected at a first point in time; determine at attribute profile for the resource based on the sample data; in response to determining that the sample data is valid, generate a unique resource identifier for the resource at the first point in time based on the sample data and the attribute profile, the unique resource identifier affirming validity of the resource represented by the sample data; and transmit the sample data and the unique resource identifier to a remote device, the sample data and the unique resource identifier comprising an affirmation instruction indicating a status of the attribute profile of the resource as valid or not valid.

16. The non-transitory, computer-readable medium of claim 15, wherein the instructions that cause the one or more processors to receive the sample data cause the one or more processors to:receive the sample data based on execution of one or more operations by an analysis device when analyzing a sample of the resource, the analysis device configured to measure one or more physical properties of the sample of the resource.

17. The non-transitory, computer-readable medium of claim 16, wherein the instructions that cause the one or more processors to receive the sample data cause the one or more processors to: receive values indicating one or more of: a mass of the resource, a molecular weight of the resource, an identifier associated with an owner of the resource, or a location at which the resource was generated.

18. The non-transitory, computer-readable medium of claim 15, wherein the instructions that cause the one or more processors to determine an attribute profile for the resource based on the sample data cause the one or more processors to: transmit the sample data as an input to a neural network to cause the neural network to generate an output, the output comprising one or more aspects of the resource; and determine the attribute profile based on the one or more aspects of the resource.

19. The non-transitory, computer-readable medium of claim 15, wherein the instructions that cause the one or more processors to receive the sample data cause the one or more processors to: receive a network identifier associated with a device that generated the sample data, the network identifier indicating a location associated with the device that generated the sample data, and wherein the instructions further cause the one or more processors to: determine that the sample data is valid based on at least one aspect of the attribute profile.

20. The non-transitory, computer-readable medium of claim 15, wherein the instructions that cause the one or more processors to generate the unique resource identifier for the resource cause the one or more processors to: execute one or more operations involved in generating a hash based on the sample data and the attribute profile; and determine the unique resource identifier based on the hash.

21. A system comprising: one or more processors configured to: generate a plurality of entries to include in a database, each entry of the plurality of entries corresponding to a resource of a plurality of resources obtained during a first period of time; in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, provide entry data associated with the first set of entries to the first server and the second server; receive, from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries; determine an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and update the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

22. The system of claim 21, wherein the one or more processors are further configured to: receive sample data associated with a plurality of resources, the sample data generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources.

23. The system of claim 21, wherein the one or more processors are further configured to: determine an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, updating each entry of the plurality of entries to include the pseudo-identifier.

24. The system of claim 23, wherein the one or more processors configured to update each entry of the plurality of entries are configured to: remove the identifier associated with the client device from each entry of the plurality of entries.

25. The system of claim 21, wherein each entry is configured to comprise a plurality of sub-entries that correspond to a respective resource, wherein each sub-entry of the plurality of sub-entries is associated with a point in time during the first period of time, and wherein the one or more processors configured to receive the initial attribute data are configured to: receive the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry.

26. The system of claim 24, wherein the one or more processors are further configured to: determine a final attribute for each entry based on the intermediate attribute for each sub-entry.

27. The system of claim 21, wherein the one or more processors are further configured to: receive status data indicating that at least one resource transitioned from a first state to a second state; in response to determining that the at least one resource transitioned from the first state to the second state, provide the status data to the first server and the second server; receive, from the first server and the second server, second attribute data representing one or more second intermediate attributes corresponding to each entry of the first set of entries; determine a second intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and update the plurality of entries based on the second intermediate attribute corresponding to each entry of the set of entries.

28. A method comprising: generating, by one or more processors, a plurality of entries to include in a database, each entry of the plurality of entries corresponding to a resource of a plurality of resources obtained during a first period of time; in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, providing, by one or more processors, entry data associated with the first set of entries to the first server and the second server;receiving, by one or more processors from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries; determining, by the one or more processors, an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and updating, by the one or more processors, the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

29. The method of claim 28, wherein the one or more processors are further configured to: receiving, by the one or more processors, sample data associated with a plurality of resources, the sample data generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources.

30. The method of claim 28, further comprising: determining, by the one or more processors, an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, updating, by the one or more processors, each entry of the plurality of entries to include the pseudo-identifier.

31. The method of claim 30, updating each entry of the plurality of entries comrpises: removing, by the one or more processors, the identifier associated with the client device from each entry of the plurality of entries.

32. The method of claim 28, wherein each entry is configured to comprise a plurality of sub-entries that correspond to a respective resource, wherein each sub-entry of the plurality of sub-entries is associated with a point in time during the first period of time, and wherein receiving the initial attribute data are configured to: receiving, by the one or more processors, the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry, where the one or more initial attributes represent one or more states of the resource when transitioning through one or more ISO-transitions.

33. The method of claim 31, further comprising: determining, by the one or more processors, a final attribute for each entry based on the intermediate attribute for each sub-entry.

34. The method of claim 28, further comprising: receiving, by the one or more processors, status data indicating that at least one resource transitioned from a first state to a second state; in response to determining that the at least one resource transitioned from the first state to the second state, providing, by the one or more processors, the status data to the first server and the second server; receiving, by the one or more processors from the first server and the second server, second attribute data representing one or more second intermediate attributes corresponding to each entry of the first set of entries; determining, by the one or more processors, a second intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and updating, by the one or more processors, the plurality of entries based on the second intermediate attribute corresponding to each entry of the set of entries.

35. A non-transitory, computer-readable medium storing instructions thereon that, when executed by one or more processors, cause the one or more processors to: generate a plurality of entries to include in a database, each entry of the plurality of entries corresponding to a resource of a plurality of resources obtained during a first period of time; in response to receiving requests indicating a first set of entries of the plurality of entries from a first server and as second server, provide entry data associated with the first set of entries to the first server and the second server; receive, from the first server and the second server, initial attribute data representing one or more initial attributes corresponding to each entry of the first set of entries; determine an intermediate attribute corresponding to each sub-entry of the set of entries based on the one or more initial attributes; and update the plurality of entries based on the intermediate attribute corresponding to each entry of the set of entries.

36. The non-transitory, computer-readable medium of claim 35, wherein the instructions further cause the one or more processors to: receive sample data associated with a plurality of resources, the sample data generated based on one or more operations performed by an analysis device as a sensor of the analysis device measures samples of each of the plurality of resources.

37. The non-transitory, computer-readable medium of claim 35, wherein the instructions further cause the one or more processors to: determine an identifier associated with a client device involved in processing each entry of the plurality of entries; and in response to mapping the identifier to a pseudo-identifier, update each entry of the plurality of entries to include the pseudo-identifier.

38. The non-transitory, computer-readable medium of claim 37, wherein the instructions that cause the one or more processors to update each entry of the plurality of entries cause the one or more processors to: remove the identifier associated with the client device from each entry of the plurality of entries.

39. The non-transitory, computer-readable medium of claim 35, wherein each entry is configured to comprise a plurality of sub-entries that correspond to a respective resource, wherein each sub-entry of the plurality of sub-entries is associated with a point in time during the first period of time, and wherein the instructions that cause the one or more processors to receive the initial attribute data cause the one or more processors to: receive the initial attribute data where each attribute corresponds to a state of a resource at the point in time corresponding to a sub-entry.

40. The non-transitory, computer-readable medium of claim 38, wherein the instructions cause the one or more processors to: determine a final attribute for each entry based on the intermediate attribute for each sub-entry.

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