Toward interoperable bioscience data
Susanna-Assunta Sansone,Philippe Rocca-Serra,Dawn Field,Eamonn Maguire,Chris F. Taylor,Chris F. Taylor,Oliver Hofmann,Hong Fang,Steffen Neumann,Weida Tong,Linda A. Amaral-Zettler,Kimberly Begley,Kimberly Begley,Timothy F. Booth,Lydie Bougueleret,Gully A. P. C. Burns,Brad Chapman,Timothy Clark,Lee-Ann Coleman,Jay Copeland,Sudeshna Das,Antoine de Daruvar,Paula de Matos,Ian Dix,Scott C. Edmunds,Chris T. Evelo,Chris T. Evelo,Mark K. Forster,Pascale Gaudet,Pascale Gaudet,Jack A. Gilbert,Carole Goble,Julian L. Griffin,Julian L. Griffin,Daniel J. Jacob,Daniel J. Jacob,Jos C. S. 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 +55 more
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TL;DR: The prerequisites for data commoning are described and an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision are presented.
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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.
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The FAIR Guiding Principles for scientific data management and stewardship
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TL;DR: The FAIR Data Principles as mentioned in this paper are a set of data reuse principles that focus on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.
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TL;DR: This work describes the OBO Foundry initiative and provides guidelines for those who might wish to become involved and describes an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality.
Innovation in China
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NCBI GEO: archive for high-throughput functional genomic data
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TL;DR: The Gene Expression Omnibus at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data and offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives.
Big data: The future of biocuration.
Doug Howe,Maria C. Costanzo,Petra Fey,Takashi Gojobori,Linda Hannick,Winston Hide,Winston Hide,David P. Hill,Renate Kania,Mary L. Schaeffer,Mary L. Schaeffer,Susan E. St. Pierre,Simon N. Twigger,Owen White,Seung Y. Rhee +14 more
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