NCI's Office of Data Sharing Annual Symposium (Abstract Submission): Submission #4

Submission information
Submission Number: 4
Submission ID: 144019
Submission UUID: 596eb535-7241-4901-9b6c-8d9126245327

Created: Wed, 06/04/2025 - 17:34
Completed: Wed, 06/04/2025 - 17:35
Changed: Wed, 06/04/2025 - 17:35

Remote IP address: 10.208.24.182
Submitted by: Anonymous
Language: English

Is draft: No





Presenter Information
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First Name: Jeff









Middle Initial: {Empty}









Last Name: Liu









Degree(s): MSc.









Position/Title/Career Status: Director, Data Management and Strategy









Organization: Dana-Farber Cancer Institute









Organization Address:
Boston










Email: J_Liu@dfci.harvard.edu













Abstract Information
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Abstract Category: Demo Table Request









Abstract Keywords: data, sharing, catalog, metadata, FAIR









Abstract Title: An Institutional Cancer Research Data Catalog for Enhanced Data Sharing, Findability, and Accessibility









Abstract Summary:
The exponential growth of scientific data in cancer research and precision medicine presents both significant opportunities and challenges for researchers. Data fragmentation and silos  across data repositories and institions, along with non-standardized formats and metadata, hampers access and utilization of diverse data resources. The Data Management Team in the Division of Population Science has collaborated with the National Cancer Institute’s Childhood Cancer Data Initiative Project team, customized its open-source codebase for the Childhood Cancer Data Catalog and launched the Dana-Farber Cancer Research Data Catalog (DFDC). Besides new metadata identified, we have also enhanced DFDC with advanced phrase-based search feature and metadata extraction utility. Our platform integrates rich metadata for institutional and community data resources, streamlining data discovery for researchers. By providing easy access to a wide range of cancer data resources, researchers and trainees at Dana-Farber are empowered to accelerate secondary data analysis, promoting data sharing and fostering collaboration and data reuse within the DFCI research community.










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