by: Juan Sequeda
Knowledge Graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at a large scale. We observe the adoption of Knowledge Graphs by the Googles of the world. However, not everybody is a Google. Enterprises still struggle to understand their relational databases which consist of thousands of tables, tens of thousands of attributes and how the data all work together. How can enterprises adopt Knowledge Graphs successfully to integrate data, without boiling the ocean?
This tutorial will be hands-on and will focus on two parts: design and building. The content of this tutorial is applicable to knowledge graphs being built either with Property Graph or RDF Graph technologies.
Juan F. 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. He holds a PhD in Computer Science from The University of Texas at Austin. Wearing his scientific hat, Juan's goal is to reliably create knowledge from inscrutable data. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management, and what now is called Knowledge Graphs. Wearing his business hat, Juan is a product manager, does business development and strategy, technical sales and works with customers to understand their problems to translated back to R&D. Juan has served as a bridge between academia and industry as the current chair of the Property Graph Schema Working Group, member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC) and past invited expert member and standards editor at the World Wide Web Consortium (W3C).