COPO: a metadata platform for brokering FAIR data in the life sciences
Scientific innovation is increasingly reliant on data and computational resources. Much of today’s life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Lenguaje: | Inglés |
| Publicado: |
Cold Spring Harbor Laboratory
2019
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| Acceso en línea: | https://hdl.handle.net/10568/106674 |
| _version_ | 1855541217871265792 |
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| author | Etuk, A. Shaw, F. González Beltran, A. Johnson, D. Laporte, Marie-Angélique Rocca Serra, Philippe Arnaud, Elizabeth Devare, Medha Kersey, Paul J. Sansone, Susanna-Assunta Davey, R.P. |
| author_browse | Arnaud, Elizabeth Davey, R.P. Devare, Medha Etuk, A. González Beltran, A. Johnson, D. Kersey, Paul J. Laporte, Marie-Angélique Rocca Serra, Philippe Sansone, Susanna-Assunta Shaw, F. |
| author_facet | Etuk, A. Shaw, F. González Beltran, A. Johnson, D. Laporte, Marie-Angélique Rocca Serra, Philippe Arnaud, Elizabeth Devare, Medha Kersey, Paul J. Sansone, Susanna-Assunta Davey, R.P. |
| author_sort | Etuk, A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Scientific innovation is increasingly reliant on data and computational resources. Much of today’s life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to process these data is at an all-time high, but these are not typically trained in good data management practices. That said, we have come a long way in the last decade, with funders, publishers, and researchers themselves making the case for open, interoperable data as a key component of an open science philosophy. In response, recognition of the FAIR Principles (that data should be Findable, Accessible, Interoperable and Reusable) has become commonplace. However, both technical and cultural challenges for the implementation of these principles still exist when storing, managing, analysing and disseminating both legacy and new data. COPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects (raw or processed data, publications, samples, images, etc.) using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share it with the wider scientific community. COPO encourages data generators to adhere to appropriate metadata standards when publishing research objects, using semantic terms to add meaning to them and specify relationships between them. This allows data consumers, be they people or machines, to find, aggregate, and analyse data which would otherwise be private or invisible. Building upon existing standards to push the state of the art in scientific data dissemination whilst minimising the burden of data publication and sharing. |
| format | Preprint |
| id | CGSpace106674 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Cold Spring Harbor Laboratory |
| publisherStr | Cold Spring Harbor Laboratory |
| record_format | dspace |
| spelling | CGSpace1066742025-11-12T05:49:05Z COPO: a metadata platform for brokering FAIR data in the life sciences Etuk, A. Shaw, F. González Beltran, A. Johnson, D. Laporte, Marie-Angélique Rocca Serra, Philippe Arnaud, Elizabeth Devare, Medha Kersey, Paul J. Sansone, Susanna-Assunta Davey, R.P. data bioinformatics information systems metadata standards interoperability case studies Scientific innovation is increasingly reliant on data and computational resources. Much of today’s life science research involves generating, processing, and reusing heterogeneous datasets that are growing exponentially in size. Demand for technical experts (data scientists and bioinformaticians) to process these data is at an all-time high, but these are not typically trained in good data management practices. That said, we have come a long way in the last decade, with funders, publishers, and researchers themselves making the case for open, interoperable data as a key component of an open science philosophy. In response, recognition of the FAIR Principles (that data should be Findable, Accessible, Interoperable and Reusable) has become commonplace. However, both technical and cultural challenges for the implementation of these principles still exist when storing, managing, analysing and disseminating both legacy and new data. COPO is a computational system that attempts to address some of these challenges by enabling scientists to describe their research objects (raw or processed data, publications, samples, images, etc.) using community-sanctioned metadata sets and vocabularies, and then use public or institutional repositories to share it with the wider scientific community. COPO encourages data generators to adhere to appropriate metadata standards when publishing research objects, using semantic terms to add meaning to them and specify relationships between them. This allows data consumers, be they people or machines, to find, aggregate, and analyse data which would otherwise be private or invisible. Building upon existing standards to push the state of the art in scientific data dissemination whilst minimising the burden of data publication and sharing. 2019 2020-01-22T12:48:06Z 2020-01-22T12:48:06Z Preprint https://hdl.handle.net/10568/106674 en Open Access application/pdf Cold Spring Harbor Laboratory Etuk, A.; Shaw, F.; Gonzalez-Beltran, A.; Johnson, D.; Laporte, M-A.; Rocca-Serra, P.; Arnaud, E.; Devare, M.; Kersey, P.J.; Sansone, S-A.; Davey, R.P. (2019) COPO: a metadata platform for brokering FAIR data in the life sciences. bioRxiv 782771. |
| spellingShingle | data bioinformatics information systems metadata standards interoperability case studies Etuk, A. Shaw, F. González Beltran, A. Johnson, D. Laporte, Marie-Angélique Rocca Serra, Philippe Arnaud, Elizabeth Devare, Medha Kersey, Paul J. Sansone, Susanna-Assunta Davey, R.P. COPO: a metadata platform for brokering FAIR data in the life sciences |
| title | COPO: a metadata platform for brokering FAIR data in the life sciences |
| title_full | COPO: a metadata platform for brokering FAIR data in the life sciences |
| title_fullStr | COPO: a metadata platform for brokering FAIR data in the life sciences |
| title_full_unstemmed | COPO: a metadata platform for brokering FAIR data in the life sciences |
| title_short | COPO: a metadata platform for brokering FAIR data in the life sciences |
| title_sort | copo a metadata platform for brokering fair data in the life sciences |
| topic | data bioinformatics information systems metadata standards interoperability case studies |
| url | https://hdl.handle.net/10568/106674 |
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