Rich Context | A Knowledge Graph for Linking Datasets with Research Outcomes
KGC 2020
•
18m
The Rich Context project at NYU Wagner is the knowledge graph complement to the ADRF platform for cross-agency social science research using sensitive data, currently used by 50+ agencies. Rich Context represents metadata about datasets and their use in research which in turn influences public policy, with a goal of producing recommender systems for analysts and policymakers. Most all of the code is open source. This talk introduces the background for the project, our team process for collaboration, and several areas where machine learning is used to infer or clean metadata obtained from scholarly infrastructure and for semi-automated graph construction, along with human-in-the-loop feedback mechanisms for domain experts to help improve our graph.
Up Next in KGC 2020
-
Using Graph Analytics in Enterprise A...
Graphs provide a new dimension to managing and analyzing data, and enterprises are keen to explore and adopt this technology. There have been some barriers to adoption, including a lack of familiarity with graph query languages and tools and challenges in integrating graph analytics into existing...
-
Inventory Management using Knowledge ...
Predictive analytics in inventory management has not been the traditional domain of knowledge graphs and semantics; however, it is a surprisingly natural fit. This talk will review knowledge graphs in the supply chain and look into the details of implementation. In our central case, using a seman...
-
A Data Catalog Should be Your Organiz...
In this presentation, we'll cover why a data catalog is the first knowledge graph that an organization should build. Most organizations don't have a clear picture of their data assets and how they're being used - a data datalog helps provide that picture and unlock the value of data. We'll explor...