Connecting the World's Medical Research with the Biomedical Data Translator



With the explosion in biomedical data, the current scarcity is not in information, but in time and expertise to connect and analyze it. It would take somewhere on the order of half a million manhours to read just the abstracts of every journal article published in PubMed, and nearly a year of 24/7 reading to keep up with the 500,000 added each year.


The Biomedical Data Translator is an effort to integrate multiple types of existing data from disparate sources to derive knowledge from data, and knowledge graphs play a key part in this effort. Learn from the Biomedical Data Translator team lead, Mark Williams, about the importance and difficulty of entity resolution, data standards, and integrating data across a wide range of domains.


Feel free to share this meetup with anyone who might be interested in learning more about knowledge graphs or who would like to learn about connecting disparate government data.

Agenda:
6:00 - 7:00 PM - Networking & Snacks
7:00 - 8:00 PM - Presentation by Mark Williams

Speaker and Presenter Information

Mark Williams is a software engineer on the Biomedical Data Translator team at the National Center for Advancing Translational Sciences (NCATS). NCATS’ goal is to accelerate the process of turning observations in the laboratory, clinic and community into interventions that improve the health of individuals and the public — from diagnostics and therapeutics to medical procedures and behavioral changes. Mark studied computer science at the University of South Carolina before working in various aspects of bioinformatics.

Expected Number of Attendees

20

Relevant Government Agencies

Dept of Health & Human Services, FDA, NIH


This event has no exhibitor/sponsor opportunities


When
Wed, May 15, 2019, 6:00pm - 8:30pm


Cost
Complimentary:    $ 0.00


Where
Stardog
2101 Wilson Blvd
Stardog Suite 800
Arlington, VA 22201
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Website
Click here to visit event website


Organizer
Knowledge Graphs DC


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Join the event conversation:
@KGraphsDC
#KnowledgeGraph


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