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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
Peter Rose | Integrating Heterogeneous Data Sources Into A COVID-19 Graph
The COVID-19 pandemic has mobilized researchers worldwide to investigate many aspects of the outbreak, ranging from case statistics, patient demographics, transportation modeling, epidemiological studies, to viral genome sequencing. Relevant data are produced and publically shared at an unprecedented pace and updated daily. Given the urgency of the outbreak and the high levels of velocity and variety of pandemic-related data, efforts have not focused on data interoperability across domains. The avalanche of COVID-19-related data streams from agencies and public and private research teams, with little coordination and without reliance on best interoperability practices, creates enormous challenges for researchers attempting to analyze the pandemic in all its multi-disciplinary complexity and develop a comprehensive policy response. With data collection and analysis efforts largely fragmented and siloed, this goal can be addressed by the roll-out of a comprehensive semantic integration platform that organizes available information into an easily queryable transdisciplinary knowledge system. We developed the COVID-19-Net Knowledge Graph that integrates epidemiological, biological, and population characteristic data. The challenges of integrating data across diverse domains, proposed solutions, and calls for actions to prepare for future outbreaks will be discussed.