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Sunday, February 10, 2019

Data Governance and Knowledge Graphs

Knowledge Graphs and Data Governance

A Note from TopQuadrant's CEO, Irene Polikoff 

As 2018 comes to a close we took a look back at key topics that were of most interest in our conversations with customers, prospects and at the many industry events we attended throughout the year.

A very popular topic continues to be Knowledge Graphs. Looking ahead, we believe that the use of knowledge graphs in the enterprise will be substantially expanded in key areas including data relationship discovery and exploration, semantic interoperability, and especially data governance. Knowledge graphs are foundational to data governance because they catalog diverse enterprise data by capturing both the technical and business context, and meaning of the data through connections across all assets in the enterprise ecosystem.

On the more technical side, we continue to receive a lot of questions about SHACL and its importance to data management. SHACL, a W3C standard for graph data modeling and validation can be used to support many capabilities needed for data governance. I cover some examples in this blog post, “How does SHACL Support Data Governance?” With the addition of SHACL to the standards that support knowledge graphs, it is possible to ensure that the knowledge remains consistent against multiple viewpoints, retains a good quality, and supports the inference of new knowledge that is not explicitly stated in the data.

For these and other reasons I can't cover in this brief note, we believe knowledge graphs are an ideal and, arguably, the only viable foundation for bridging and connecting enterprise metadata silos. For more on TopQuadrant’s views on these topics, see the newly published DATAVERSITY article: “Achieving Data Governance 2.0 with Knowledge Graph Technology.”  ... "


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