Toward interoperable bioscience data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-02

AUTHORS

Susanna-Assunta Sansone, Philippe Rocca-Serra, Dawn Field, Eamonn Maguire, Chris Taylor, Oliver Hofmann, Hong Fang, Steffen Neumann, Weida Tong, Linda Amaral-Zettler, Kimberly Begley, Tim Booth, Lydie Bougueleret, Gully Burns, Brad Chapman, Tim Clark, Lee-Ann Coleman, Jay Copeland, Sudeshna Das, Antoine de Daruvar, Paula de Matos, Ian Dix, Scott Edmunds, Chris T Evelo, Mark J Forster, Pascale Gaudet, Jack Gilbert, Carole Goble, Julian L Griffin, Daniel Jacob, Jos Kleinjans, Lee Harland, Kenneth Haug, Henning Hermjakob, Shannan J Ho Sui, Alain Laederach, Shaoguang Liang, Stephen Marshall, Annette McGrath, Emily Merrill, Dorothy Reilly, Magali Roux, Caroline E Shamu, Catherine A Shang, Christoph Steinbeck, Anne Trefethen, Bryn Williams-Jones, Katherine Wolstencroft, Ioannis Xenarios, Winston Hide

ABSTRACT

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. More... »

PAGES

121

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ng.1054

DOI

http://dx.doi.org/10.1038/ng.1054

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014202300

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22281772


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