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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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Migrating from Hierarchies to a Graph: An Enterprise Case Study

31m

During a recent engagement, Factor led a client effort to migrate from a traditional RDBMS-based taxonomy management system to a graph-based environment.

The client's semantic ecosystem was complex, comprising dozens of taxonomes managed in two separate toolsets (a taxonomy management tool and a PIM system), including many duplicate, redundant, and outdated structures, and supplying taxonomy data to multiple downstream systems including content management, publishing, DAM, search, navigation, sales enablement, customer management, and other data repositories.

This migration presented opportunities to consolidate existing vocabularies, eliminate duplicate concepts and attributes, perform metadata cleanup, and update the model into a richer semantic structure, all while (insofar as possible) minimizing disruptions to downstream systems.

Along the way we learned many lessons about the scope of such efforts in terms of required research, remodeling, consolidation, cleanup, user engagement, and data migration and testing. This short case study outlines some of the challenges, solutions, and missed opportunities we encountered.

Attendees will come away with an understanding of the work involved in such migrations, including the critical importance of preparation and testing, as well as considerations around modeling and potential disruptions to downstream consuming systems as a result of changes.