Skip to main content
Connecting the Knowledge Ecosystem Founded in 2019 at Columbia University, The Knowledge Graphs Conference is emerging as the premiere source of learning around knowledge graph technologies. We believe knowledge graphs are an underutilized yet essential force for solving complex societal challenges like climate change, democratizing access to knowledge and opportunity, and capturing business value made possible by the AI revolution.
KGC bridges the gap between industry, which is increasingly recognizing the necessity of integrated data, and academia, where semantic technologies have been developing for over twenty years. Our events, education, content, and community efforts facilitate meaningful exchange between diverse groups, and increase awareness, development and adoption of this powerful technology.
Conference – bridging the gap between research and industry
We organize workshops and tutorials to progress a number of Tech4Good themes, targeting objectives such as the United Nations Sustainable Development Goals and the development of a COVID-19 vaccine. At our most recent conference, 530 attendees participated, representing over thirty industries across forty-two countries. Speakers ranged from Bell Labs pioneer John Sowa to Morgan Stanley, AstraZeneca, and leading academics from Europe and USA. A variety of workshops and tutorials were also given, including several on tech4good themes–from the UN SDGs to personal health graphs and fake news.
KGC Vision and Values
Our goal is to build the community and become a leading source of learning around knowledge graphs.
We will achieve this by engaging and convening industry leaders and innovators, across sectors.
We will focus on the diversity of perspectives:
Professional Diversity: Industry practitioners, Business Users, Faculty, Scientists, Students
Gender & Age diversity
We will gather, share and publish content to increase learning.
We will build the community online and in-person through our content, meetups and conferences.
Live stream preview
Tutorial Rapid Knowledge Graph Development with GraphQL and RDF Databases
The enterprise knowledge graphs help modern organizations to preserve the semantic context of abundant accessible information. They become the backbone of enterprise knowledge management and AI technologies with the ability to differentiate things versus strings. Still, beyond the hype of repackaging the semantic web standards for enterprise, few practical tutorials are demonstrating how to build and maintain an enterprise knowledge graph. This tutorial helps you learn 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. You will pass step by step process to (1) start a knowledge graph from a public RDF dataset, (2) generate GraphQL API to abstract the RDF database, (3) pass a quick GraphQL crash course with examples (4) develop a sample web application. Finally, we will discuss other possible directions like extending the knowledge graph with machine learning components, extend the graph with additional services, add monitoring dashboards, integrate external systems. The tutorial is based on Ontotext GraphDB and Platform products and requires basic RDF and SPARQL knowledge.