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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
Eelke van der Horst | Building an Immuno-Oncology & Cell Therapy Knowledge Graph
Bristol-Myers Squibb (BMS) is a global pharmaceutical company with drug discovery and development programs in several therapeutic areas. As part of its enterprise information governance, there is an ongoing effort to unlock research data from siloed systems, by building a knowledge graph that transcends research domains and departments.
The Hyve, a Dutch IT services provider for the biomedical domain, assists in this effort by creating semantic models of particular areas, such as computational genomics or clinical trials.
In this case-study, we will share our experience modelling research data in Immuno-Oncology & Cell Therapy (IOCT). Here, traceability of research data through the development pipeline poses a particular problem because most data is currently stored in particular vendor solutions and departments. We will first introduce the semantic model that was created to model the IOCT research domain and data, and how it builds on public domain ontologies and existing BMS ontologies. We will then present our efforts to build a knowledge graph by instantiating this model using a selected set of research data. We will evaluate the strategies and tools we explored to unlock as much of the data as possible, and the end-to-end use cases that can now be answered using the knowledge graph.
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