Making Common Fund Data More Findable: Catalyzing a Data Ecosystem. Charbonneau, A. L, Brady, A., Czajkowski, K., Aluvathingal, J., Canchi, S., Carter, R., Chard, K., Clarke, D. J B, Crabtree, J., Creasy, H. H, D'Arcy, M., Felix, V., Giglio, M., Gingrich, A., Harris, R. M, Hodges, T. K, Ifeonu, O., Jeon, M., Kropiwnicki, E., Lim, M. C W, Liming, R L., Lumian, J., Mahurkar, A. A, Mandal, M., Munro, J. B, Nadendla, S., Richter, R., Romano, C., Rocca-Serra, P., Schor, M., Schuler, R. E, Tangmunarunkit, H., Waldrop, A., Williams, C., Word, K., Sansone, S., Ma'ayan, A., Wagner, R., Foster, I., Kesselman, C., Brown, C T., & White, O. GigaScience, 11:giac105, November, 2022. ![Making Common Fund Data More Findable: Catalyzing a Data Ecosystem [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{Charbonneau2022,
abstract = {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.},
author = {Charbonneau, Amanda L and Brady, Arthur and Czajkowski, Karl and Aluvathingal, Jain and Canchi, Saranya and Carter, Robert and Chard, Kyle and Clarke, Daniel J B and Crabtree, Jonathan and Creasy, Heather H and D'Arcy, Mike and Felix, Victor and Giglio, Michelle and Gingrich, Alicia and Harris, Rayna M and Hodges, Theresa K and Ifeonu, Olukemi and Jeon, Minji and Kropiwnicki, Eryk and Lim, Marisa C W and Liming, R Lee and Lumian, Jessica and Mahurkar, Anup A and Mandal, Meisha and Munro, James B and Nadendla, Suvarna and Richter, Rudyard and Romano, Cia and {Rocca-Serra}, Philippe and Schor, Michael and Schuler, Robert E and Tangmunarunkit, Hongsuda and Waldrop, Alex and Williams, Cris and Word, Karen and Sansone, Susanna-Assunta and Ma'ayan, Avi and Wagner, Rick and Foster, Ian and Kesselman, Carl and Brown, C Titus and White, Owen},
date-added = {2024-01-22 12:05:54 -0800},
date-modified = {2024-01-22 12:05:54 -0800},
doi = {10.1093/gigascience/giac105},
eprint = {https://academic.oup.com/gigascience/article-pdf/doi/10.1093/gigascience/giac105/48360815/giac105.pdf},
file = {/Users/schuler/Zotero/storage/8LZZUHCX/Charbonneau et al. - 2022 - Making Common Fund data more findable catalyzing .pdf},
issn = {2047-217X},
journal = {GigaScience},
month = nov,
pages = {giac105},
title = {Making {{Common Fund}} Data More Findable: Catalyzing a Data Ecosystem},
url = {https://doi.org/10.1093/gigascience/giac105},
volume = {11},
year = {2022},
bdsk-url-1 = {https://doi.org/10.1093/gigascience/giac105}}
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