US 11,748,395 B2
Developing object ontologies and data usage models using machine learning
Benjamin Colby Jones, Tuscumbia, AL (US)
Assigned to Science Applications International Corporation, Reston, VA (US)
Filed by Science Applications International Corporation, Reston, VA (US)
Filed on Jun. 25, 2021, as Appl. No. 17/358,322.
Prior Publication US 2022/0414136 A1, Dec. 29, 2022
Int. Cl. G06F 16/00 (2019.01); G06F 16/36 (2019.01); G06N 20/00 (2019.01); G06F 40/30 (2020.01); G06F 16/242 (2019.01)
CPC G06F 16/367 (2019.01) [G06F 16/2445 (2019.01); G06F 40/30 (2020.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
ingesting, by a computing device, data accessed by a first application from one or more data stores;
generating, based on the ingested data, a data definition language repository that catalogs database object metadata associated with the data accessed by the first application;
accessing one or more code repositories to obtain source code of the first application;
analyzing, using natural language processing, the source code of the first application to identify one or more data statements that access the one or more data stores;
identifying, using a machine learning model, a link between the one or more data statements and the database object metadata;
generating, based on the link between the one or more data statements and the database object metadata, a first application data usage model illustrating a relationship between the first application and the one or more data stores;
generating, based on the first application data usage model and based on at least one second application data usage model, a semantic hub; and
generating, based on the semantic hub, a data abstraction model configured to transform data exchanges between a second application and at least one data store of the one or more data stores.