Designing and Building Enterprise Knowledge Graphs Synthesis Lectures on Data, Semantics, and Knowledge Series

This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.

Preface.- Foreword by an Anonymous CDO.- Foreword by Tom Plasterer.- Acknowledgments.- Disclaimer.- Introduction.- Designing Enterprise Knowledge Graphs.- Mapping Design Patterns.- Building Enterprise Knowledge Graphs.- What's Next?.- Conclusions.- Bibliography.- Authors' Biographies.

Juan Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. Juan’s goal is to reliably create knowledge from inscrutable data. His academic and industry work has been on designing and building knowledge graphs for enterprise data integration where he has researched and developed technologies for semantic and graph data virtualization, ontology and graph data modeling and schema mapping, and data integration methodologies. Juan serves as a bridge between academia and industry through standardization committees, like serving as the co-chair of the Property Graph Schema Working Group and a past member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC), as well as a past invited expert member and standards editor at the World Wide Web Consortium (W3C). Juan holds a Ph.D. in Computer Science from The University of Texas at Austin. He is the recipient of the NSF Graduate Research Fellowship, 2nd place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at International Semantic Web Conference 2014, and the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics.