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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: Industry diversity Professional Diversity: Industry practitioners, Business Users, Faculty, Scientists, Students Gender & Age diversity Geographical 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.

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Peter Hicks | Visualizing Data Lineage

KGC 2021 Conference, Workshops and Tutorials • 17m

Extracting metadata from data pipelines and building useful graphs for real production environments.

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Paolo Manghi | The OpenAIRE Research ...

Paolo Manghi | The OpenAIRE Research ...

The presentation will introduce the motivations, architecture, and operation of the OpenAIRE Research Graph (http://graph.openaire.eu), one of the largest (if not the largest) public, open access, collections of metadata and semantic links (~1Bi) between research-related entities: articles (124M+...
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Paco Nathan | Graph Based Data Science

Paco Nathan | Graph Based Data Science

Python offers excellent libraries for working with graphs: semantic technologies, graph queries, interactive visualizations, graph algorithms, probabilistic graph inference, as well as embedding and other integrations with deep learning. However, most of these approaches share little common groun...
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Olaf Hartig | RDF Star: Metadata For ...

Olaf Hartig | RDF Star: Metadata For ...

The lack of a convenient way to capture annotations and statements about individual RDF triples has been a long standing issue for RDF. Such annotations are a native feature in other contemporary graph data models (e.g., edge properties in the Property Graph model). In recent years, the RDF* app...