DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Applicant has amended claims 1, 2, 6, 10-12, 15 and 18-20; and canceled claims 4 and 13 in the amendment filed on 8/21/2026. Claims 1-3, 5-12 and 14-20 are currently pending in the present application.
Response to Arguments
Applicant’s arguments filed on 8/21/2026 with respect to the claims 1-3, 5-12 and 14-20 have been considered but they are moot in view of the new ground of rejection.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-12 and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chu et al. (US 6,493,720 B1), and further in view of Crabtree et al. (US 2024/0231909 A1).
As per claim 1, Chu et al. and Crabtree et al. disclose A computing system comprising:
a memory storing a plurality of information assets; and as (Chu et al., see e.g., Col. 4 lines 13-17 and 51-58: as one or more data storage resources).
a processing system of an enterprise, the processing system comprising one or more processors implemented in circuitry, the processing system being configured to:
receive, via an application programming interface (API), a query for metadata for an information asset stored in one or more data catalogs of the enterprise; as (Chu et al., see e.g., Col. 6 lines 28-34: as “The information catalog system enables users to: locate data in the information catalog by keyword text search or navigation (“drill down”) through a subject area and business groupings, to understand data by browsing metadata descriptions in business terms, and to access the data by launching applications directly from the information catalog system”, wherein the keyword text search is referred to as the query), but Chu et al. does not explicitly disclose using the API in this process. However, the using the API is taught as (Crabtree et al., see e.g., ¶¶ 0081 and 0122: as “A combination of the above features allows for contextual universalization of computing assets across different aspects of a platform, such that customers using the platform can search for, select, and use computing assets appropriate to their computing needs. Some examples of computing assets that may be universalized in this manner include datasets, data feeds and streams, data stores or databases; stored queries schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”; and “The exemplary list of assets 1020 shows examples of computing assets that may be available to satisfy a customer's computing needs, including datasets, data feeds and streams, data stores or databases; stored queries, schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”).
determine, via the API, a location of the metadata using a metadata registry that stores mapping data that maps information assets to locations of metadata for the information assets, the locations corresponding to the data catalogs of the enterprise; as (Crabtree et al., see e.g., ¶¶ 0052, 0079 and 0116: as “the asset registry may include provenance information for each asset which may include such information as who created the asset, when the asset was created, asset source type information, where the asset is located or stored, ownership, licensing, pricing and royalty information, data validation, schema, compliance and auditing information, trustworthiness scores, re-use, expiration and staleness, and known or suspected biases associated with the asset. This provenance information can be used to determine a suitability, reliability, or trustworthiness of the asset or of outputs of workflows associated with an asset”; and using the asset registry via the API (see e.g., ¶¶ 0081 and 0122) to locate the provenance information in the asset registry).
retrieve, via the API, the metadata from the determined location; and provide, via the API, the metadata in response to the query, as (Chu et al., see e.g., Col. 6 lines 28-38: as “The information catalog system enables users to: locate data in the information catalog by keyword text search or navigation ("drill down") through a subject area and business groupings, to understand data by browsing metadata descriptions in business terms, and to access the data by launching applications directly from the information catalog system. Additionally, the information catalog system communicates comments and corrections on metadata descriptions to the information catalog system administrator via a comments object and shares administration of the information catalog system information catalog (when authorized)”), but Chu et al. does not explicitly disclose using the API in the processes. However, the using the API is taught as (Crabtree et al., see e.g., ¶¶ 0081 and 0122: as “A combination of the above features allows for contextual universalization of computing assets across different aspects of a platform, such that customers using the platform can search for, select, and use computing assets appropriate to their computing needs. Some examples of computing assets that may be universalized in this manner include datasets, data feeds and streams, data stores or databases; stored queries schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”; and “The exemplary list of assets 1020 shows examples of computing assets that may be available to satisfy a customer's computing needs, including datasets, data feeds and streams, data stores or databases; stored queries, schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing data of the claimed invention to modify the Chu et al. invention to include technique of using of database registries containing provenance-related and ontologically-related metadata, as taught by Crabtree et al., for the benefit of using an asset registry that contains provenance information and ontological information about available computing assets, a provenance manager which tracks the provenance of each asset for data validation and contextual analysis purposes, an ontology manager that uses ontological relationships among assets to determine other domains in which an asset may be useful, and an interoperability manager which combines the provenance and ontology outputs to suggest computing assets that may be useful in a given context (Crabtree et al., Abstract lines 7-16).
As per claim 2, Chu et al. and Crabtree et al. disclose The computing system of claim 1, wherein the processing system is further configured to: receive, via the API, a change event message from one of the data catalogs via a change event queue; and update, via the API, the metadata registry according to the change event message, as (Chu et al., see e.g., Col. 7 lines 25-32: as “Once these objects are registered, changes in the metadata of the objects at their source or tool (e.g., at the Visual Warehouse.TM.) are detected by the metadata synchronizer 118. The metadata synchronizer 118 monitors the tools on a timed basis. The user who registers the objects specifies how often synchronization is to occur. The metadata synchronizer 118 will refresh metadata in the information catalog, if needed”), but Chu et al. does not explicitly disclose using the API in the processes. However, the using the API is taught as (Crabtree et al., see e.g., ¶¶ 0081 and 0122: as “A combination of the above features allows for contextual universalization of computing assets across different aspects of a platform, such that customers using the platform can search for, select, and use computing assets appropriate to their computing needs. Some examples of computing assets that may be universalized in this manner include datasets, data feeds and streams, data stores or databases; stored queries schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”; and “The exemplary list of assets 1020 shows examples of computing assets that may be available to satisfy a customer's computing needs, including datasets, data feeds and streams, data stores or databases; stored queries, schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing data of the claimed invention to modify the Chu et al. invention to include technique of using of database registries containing provenance-related and ontologically-related metadata, as taught by Crabtree et al., for the benefit of using an asset registry that contains provenance information and ontological information about available computing assets, a provenance manager which tracks the provenance of each asset for data validation and contextual analysis purposes, an ontology manager that uses ontological relationships among assets to determine other domains in which an asset may be useful, and an interoperability manager which combines the provenance and ontology outputs to suggest computing assets that may be useful in a given context (Crabtree et al., Abstract lines 7-16).
As per claim 3, Chu et al. as modified by Crabtree et al. discloses The computing system of claim 1, wherein to receive the query, the processing system is configured to receive the query from a user via a user interface (UI), as (Chu et al., see e.g., Col. 7 lines 14-24 and Col. 8 lines 24-40).
As per claim 5, Chu et al. as modified by Crabtree et al. discloses The computing system of claim 1, wherein the metadata includes one or more of a location of a corresponding information asset, business metadata for the corresponding information asset, a lineage of data for the corresponding information asset, where the corresponding information asset has been used, or a data quality score for the corresponding information asset, as (Chu et al., see e.g., Col. 6 lines 20-27: as “The information catalog system provides a powerful business-oriented solution to help end users locate, understand, and access enterprise data. In client/server information catalogs, business metadata (data about data) can be described in business terms, organized into subject areas, and customized for a user workgroup's or enterprise's needs. The information catalog system is a Data Warehouse facility for integrating and managing end-user business metadata”).
As per claim 6, Chu et al. and Crabtree et al. disclose The computing system of claim 1, wherein the processing system is further configured to: maintain, via the API, the metadata registry, wherein each of the data catalogs stores a respective subset of the information assets; determine, via the API, that an information asset of one of the data catalogs has been modified; and update, via the API, the metadata registry in response to the modification, as (Chu et al., see e.g., Col. 9 lines 18-25: as “FIG. 8 is a flow diagram illustrating the steps performed by the metadata synchronizer 118. In Block 800, the metadata synchronizer 118 monitors, at specified intervals, a tool that operates on an object to identify changes to metadata of that object. In Block 802, when changes to the metadata are identified, the metadata synchronizer 118 updates an information catalog containing corresponding metadata for the object”), but Chu et al. does not explicitly disclose using the API in the processes. However, the using the API is taught as (Crabtree et al., see e.g., ¶¶ 0081 and 0122: as “A combination of the above features allows for contextual universalization of computing assets across different aspects of a platform, such that customers using the platform can search for, select, and use computing assets appropriate to their computing needs. Some examples of computing assets that may be universalized in this manner include datasets, data feeds and streams, data stores or databases; stored queries schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”; and “The exemplary list of assets 1020 shows examples of computing assets that may be available to satisfy a customer's computing needs, including datasets, data feeds and streams, data stores or databases; stored queries, schemas, indices, ontologies; connector workflows, data transformation workflows, and data processing workflows; data sources and sinks, data collectors and actuators; plugins for application programming interfaces (APIs) or cloud-based services or microservices; models, algorithms, and simulations; rules, scratchpads, reports, notes, and forms”).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing data of the claimed invention to modify the Chu et al. invention to include technique of using of database registries containing provenance-related and ontologically-related metadata, as taught by Crabtree et al., for the benefit of using an asset registry that contains provenance information and ontological information about available computing assets, a provenance manager which tracks the provenance of each asset for data validation and contextual analysis purposes, an ontology manager that uses ontological relationships among assets to determine other domains in which an asset may be useful, and an interoperability manager which combines the provenance and ontology outputs to suggest computing assets that may be useful in a given context (Crabtree et al., Abstract lines 7-16).
As per claim 7, Chu et al. as modified by Crabtree et al. discloses The computing system of claim 6, wherein at least one of the data catalogs comprises a unified data catalog, as (Chu et al., see e.g., Col. 4 lines 13-17: as “The information catalog system allows knowledge workers to define metadata (or "meta information") of objects types and object instances corresponding to information managed by one or more data storage resources under the control of one or more data processing nodes”).
As per claim 8, Chu et al. as modified by Crabtree et al. discloses The computing system of claim 6, wherein the modification comprises one of an addition, a change, or a deletion, as (Chu et al., see e.g., Col. 9 lines 18-25: as “FIG. 8 is a flow diagram illustrating the steps performed by the metadata synchronizer 118. In Block 800, the metadata synchronizer 118 monitors, at specified intervals, a tool that operates on an object to identify changes to metadata of that object. In Block 802, when changes to the metadata are identified, the metadata synchronizer 118 updates an information catalog containing corresponding metadata for the object”).
As per claim 9, Chu et al. as modified by Crabtree et al. discloses The computing system of claim 1, wherein the metadata is related to one or more Data Management & Governance requirements for the enterprise, as (Chu et al., see e.g., Col. 6 lines 20-27: as “The information catalog system provides a powerful business-oriented solution to help end users locate, understand, and access enterprise data. In client/server information catalogs, business metadata (data about data) can be described in business terms, organized into subject areas, and customized for a user workgroup's or enterprise's needs. The information catalog system is a Data Warehouse facility for integrating and managing end-user business metadata”).
As per claims 10 and 18, the claims are rejected under the same premise as the claim 1.
As per claims 11 and 19, the claims are rejected under the same premise as the claim 2.
As per claims 12 and 14, the claims are rejected under the same premises as the claims 3 and 5 respectively.
As per claims 15 and 20, the claims are rejected under the same premise as claim 6.
As per claims 16 and 17, the claims are rejected under the same premises as the claims 7 and 8 respectively.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bai D. Vu whose telephone number is (571) 270-1751. The examiner can normally be reached 9:00 - 5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi can be reached at (571) 272-4078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BAI D VU/Primary Examiner, Art Unit 2163 9/4/2026
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