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Toward interoperable bioscience data

delete2012-01-27
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OA
AI
S
Susanna‐Assunta Sansone *
P
Philippe Rocca‐Serra
D
Dawn Field
E
Eamonn Maguire
C
Chris Taylor
O
Oliver Hofmann
H
Hong Fang
S
Steffen Neumann
W
Weida Tong
L
Linda Amaral-Zettler
K
Kimberly Begley
T
Tim Booth
L
Lydie Bougueleret
G
Gully Burns
B
Brad Chapman
T
Tim W. Clark
L
L.‐A. Coleman
J
Jay Copeland
S
Sudeshna Das
A
Antoine de Daruvar
P
Paula de Matos
I
Ian Dix
S
Scott Edmunds
C
Chris T. Evelo
M
Mark J Forster
P
Pascale Gaudet
J
Jack A. Gilbert
C
Carole Goble
J
Julian L. Griffin
D
Daniel Jacob
J
Jos Kleinjans
L
Lee Harland
K
Kenneth Haug
H
Henning Hermjakob
S
Shannan J. Ho Sui
A
Alain Laederach
S
Shaoguang Liang
S
Stephen Marshall
A
Annette McGrath
E
Emily Merrill
D
Dorothy Reilly
M
Magali Roux
C
Caroline E. Shamu
C
Catherine A. Shang
C
Christoph Steinbeck
A
Anne Trefethen
B
Bryn Williams-Jones
K
Katherine Wolstencroft
I
Ioannis Xénarios
W
Winston Hide
DOI:10.1038/ng.1054delete
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Abstract

Abstract

En 中文
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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Nature Reviews Endocrinology cover
Nature Reviews Endocrinology
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