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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
Joshua Shinavier | Anything To Graph
Show me your schemas, and I will show you a graph! Although graph databases have become very popular in the enterprise, deep expertise in graphs is still in short supply (see "Building an Enterprise Knowledge Graph @Uber: Lessons from Reality" from KGC 2019). Developers often think of graphs as a completely different kind of thing from the rest of their company's data, and will go to great lengths to force their data into a "graph" shape. The amount of manual effort involved in building and maintaining ETL pipelines can become a bottleneck and a maintenance burden. In fact, there is usually a rich domain data model of entities, relationships, and properties which is already implicit in the company's existing schemas, be they interface descriptions for microservices, relational schemas, or various other kinds of storage schemas. Taking advantage of these schemas, and mapping conforming data into the graph, ought to require relatively little extra work, but developers need appropriate tools. In this presentation, we will illustrate such mappings with real-world examples from Uber, as well as introducing formal techniques for schema and data migration. We will also look ahead to the emerging GQL standard as the foundation for a new generation of highly interoperable graph database tools.