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Making Common Fund data more findable: catalyzing a data ecosystem
- Charbonneau, Amanda L;
- Brady, Arthur;
- Czajkowski, Karl;
- Aluvathingal, Jain;
- Canchi, Saranya;
- Carter, Robert;
- Chard, Kyle;
- Clarke, Daniel JB;
- Crabtree, Jonathan;
- Creasy, Heather H;
- D'Arcy, Mike;
- Felix, Victor;
- Giglio, Michelle;
- Gingrich, Alicia;
- Harris, Rayna M;
- Hodges, Theresa K;
- Ifeonu, Olukemi;
- Jeon, Minji;
- Kropiwnicki, Eryk;
- Lim, Marisa CW;
- Liming, R Lee;
- Lumian, Jessica;
- Mahurkar, Anup A;
- Mandal, Meisha;
- Munro, James B;
- Nadendla, Suvarna;
- Richter, Rudyard;
- Romano, Cia;
- Rocca-Serra, Philippe;
- Schor, Michael;
- Schuler, Robert E;
- Tangmunarunkit, Hongsuda;
- Waldrop, Alex;
- Williams, Cris;
- Word, Karen;
- Sansone, Susanna-Assunta;
- Ma'ayan, Avi;
- Wagner, Rick;
- Foster, Ian;
- Kesselman, Carl;
- Brown, C Titus;
- White, Owen
- et al.
Published Web Location
https://doi.org/10.1093/gigascience/giac105Abstract
The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.
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