The health care and life sciences community profile for dataset descriptions
Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of d...
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Published in | PeerJ (San Francisco, CA) Vol. 4; p. e2331 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
PeerJ. Ltd
16.08.2016
PeerJ, Inc PeerJ Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets. |
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Bibliography: | European Union’s Seventh Framework Programme the BBSRC Institute Strategic Programme USDOE Office of Science (SC) European Commission (EC) Swiss Federal Government State Secretariat for Education, Research and Innovation Open PHACTS project AC02-05CH11231; U54 HG008033-01; 115191; FP7/2007-2013; FP7-ICT-2012-6-270253; U41 HG006623; BB/J004456/1 Big Data to Knowledge (BD2K) initiative and Innovative Medicines Initiative Joint Undertaking EFPIA companies Database Center for Life Sciences (DBCLS - Japan) National Institutes of Health (NIH) National Institute of Allergy and Infectious Diseases (NIAID) National Bioscience Database Center, Japan Ministry of Education, Culture, Sports Science and Technology, Japan |
ISSN: | 2167-8359 2167-8359 |
DOI: | 10.7717/peerj.2331 |