Knowledge Graph Conference 2020

For the second year in a row, Ontotext is sponsoring the Knowledge Graph Conference organized by Columbia University School of Professional Studies in New York. The Knowledge Graph Conference 2020 will take place between 4 – 7 May 2020 and its main theme is  Knowledge Graphs for AI in the Enterprise.

During the second day of the conference, Vassil Momtchev (CTO) will hold a presentation with a topic: “Semantic Objects Please Application Developers with GraphQL and Facilitate Quality Knowledge Graphs”. For more information regarding the presentation, click here.

At the conference, Ontotext will also do a tutorial about “Rapid Knowledge Graph development with GraphQL and RDF databases“. It will go over the basics of how to build an enterprise knowledge graph beyond the RDF database and SPARQL with GraphQL protocol. Overcome critical challenges like exposing simple to use interface for data consumption to users who may be unfamiliar with information schemas. Control information access by implementing robust security. Open the graph for updates, but preserve its consistency and quality. For additional information regarding the tutorial, click here.

The Conference

Offered on Columbia University’s Morningside campus in New York City, the Knowledge Graph Conference (KGC) is a world-class curated program that brings experienced practitioners, technology leaders, cutting-edge researchers, academics and vendors together for two days of presentations, discussions and networking on the topic of knowledge graphs.

The goals of the conference are to showcase major knowledge graphs implementations, to educate on how knowledge graphs are built, maintained and used and to develop a community around technology leaders.

Throughout the program, participants will learn thought leadership topics such as:

• Storing and Querying Knowledge Graphs
• Formats and Languages
• Metadata, Schemas, Ontologies, and Taxonomies
• Data Governance
• Data Quality
• Linked-data
• Master Data Management
• Knowledge Graphs for AI
• Natural Language Processing
• Understanding Knowledge Graph Embeddings
• Visualization
• Search and Answer Engine Optimization
• Applications in Healthcare, Finance, Media, and Open Data

More about the event can be found here.