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Toward interoperable bioscience data

2012-01-27 , 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

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.

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