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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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Ensuring Customer Data Integrity with Graphs in Oracle Database

29m

AI, graph analytics, and enterprise database features simplify building intelligent, connected applications. Hear from Industrial Scientific, a world leader in gas detection for worker safety programs, who was facing data integrity challenges because of data inconsistencies across multiple systems that contain customer information, leading to lost revenue and frustrated customers. With an innovative use of graph technology to connect data instances across systems they have improved governance, workflows, data discovery, and data lineage in their management of customer data. Their TCO with Autonomous AI Database is a fraction of the cost (< 5%) of traditional enterprise data intelligence platforms.

Presentors : Melli Annamalai, Oracle, and Phani Chilakapati, Industrial Scientific