General Electric Company

Vijay Shiv Kumar

Kareem Sherif Aggour

Paul Edward Cuddihy

Jenny Marie Weisenberg Williams

Anthony Joseph Vinciquerra

Achalesh Kumar Pandey

Varish Vyankatesh Mulwad

Justin Despenza McHugh

Gerald Bowden Wise

Helena Goldfarb

Jenny Weisenberg Williams

Jenny Marie Williams

Paul Cuddihy

According to some embodiments, a system, method and non-transitory computer-readable medium are provided comprising receiving a node group at an integration module, wherein the node group includes one or more requests for internal data and external data, wherein internal data is data stored in an internal datastore and external data is data stored outside of the internal data store; identifying in a configuration data, one or more meta-data nodes from the node group, wherein each meta-data node indicates a request for external data; retrieving the internal data via execution of an internal data query; determining an order of execution for the one or more meta-data nodes; executing a first meta-data node based on the determined order to generate a first result; ingesting the first result into a semantic datastore; and executing a query to generate a final result, wherein the query includes the retrieved internal data and the ingested first result. Numerous other aspects are provided.

System and method for performing semantically-informed federated queries across a polystore

A system for querying a federated data store includes a metadata knowledge graph describing the contents and relationships among one or more underlying data stores, an interactive user interface receiving requests from a data consumer, a predefined constrainable query ('nodegroup') store containing predefined constrainable queries that define data subsets of interest across one or more of the underlying data repositories, a knowledge-driven querying layer generating and executing queries against the federated data store and merging responsive results, a scalable analytic execution layer receiving the search results from the federated data store and applying machine learning/artificial intelligence techniques to analyze the results, and a user interface presenting visualizations of raw or analyzed results to the consumer. A method and a non-transitory computer-readable medium are also disclosed.

Knowledge-driven federated big data query and analytics platform

A system to generate and run federated queries against a plurality of data stores storing disparate data types, the system including a user interface receiving query details from a data consumer, a metadata knowledge graph containing metadata for links and relationships of the data stores, a knowledge-driven querying layer accessing the graph and selecting predefined constrainable queries from a nodegroup store and applying the metadata links/relationships to the predefined constrainable queries to assemble subqueries, a query and analysis platform providing the subqueries to some of the data stores for execution, a scalable analytic execution layer receiving and aggregating search results from the data stores into a merged search result and/or obtaining analytic results by applying machine learning and artificial intelligence techniques to the distributed data, the user interface presenting visualizations generated from the merged search results, and/or the analytic results. A system and a non-transitory computer-readable medium are also disclosed.

According to some embodiments, system and methods for building a model are provided, comprising a display; a memory storing processor-executable process steps; and a processor to execute the processor-executable process steps to cause the system to: present a user interface on a display, the user interface including one or more user-entry fields to build a model, user-entry fields is associated with a selection of big data or small data for use with the model; receive at least one data source in a user-entry field associated with the model; determine if data in the data source includes big data or small data; and in response to the determination of big data or small data in the data source, execute the model with data from the data source in a big data or small data execution environment. Numerous other aspects are provided.

Multimodal, small and big data, machine tearing systems and processes

According to some embodiments, system and methods for representing nodes and data flows in a network are provided, comprising providing a hierarchical taxonomy for one or more concepts; providing one or more hierarchical taxonomies for one or more boundary types, wherein one or more values from each boundary type are combined to form a definition of a boundary; and associating the at least one concept and at least one boundary with a transmission of data between a first node and a second node, wherein the transmitted data is a data flow. Numerous other aspects are provided.

Growing community of inventors

Niskayuna, NY, United States of America

Vijay Shiv Kumar