Toward interoperable bioscience data

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Sansone, Susanna-Assunta
Rocca-Serra, Philippe
Field, Dawn
Maguire, Eamonn
Taylor, Chris
Hofmann, Oliver
Fang, Hong
Neumann, Steffen
Tong, Weida
Amaral-Zettler, Linda A.
Begley, Kimberly
Booth, Tim
Bougueleret, Lydie
Burns, Gully
Chapman, Brad
Clark, Tim
Coleman, Lee-Ann
Copeland, Jay
Das, Sudeshna
de Daruvar, Antoine
de Matos, Paula
Dix, Ian
Edmunds, Scott
Evelo, Chris T.
Forster, Mark K.
Gaudet, Pascale
Gilbert, Jack A.
Goble, Carole
Griffin, Julian L.
Jacob, Daniel
Kleinjans, Jos
Harland, Lee
Haug, Kenneth
Hermjakob, Henning
Ho Sui, Shannan J.
Laederach, Alain
Liang, Shaoguang
Marshall, Stephen
McGrath, Annette
Merrill, Emily
Reilly, Dorothy
Roux, Magali
Shamu, Caroline E.
Shang, Catherine A.
Steinbeck, Christoph
Trefethen, Anne
Williams-Jones, Bryn
Wolstencroft, Katherine
Xenarios, Ioannis
Hide, Winston
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To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.
© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.
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Nature Genetics 44 (2012): 121-126
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