The FAIR Guiding Principles for scientific data management and stewardship
Copyright policy )The FAIR Guiding Principles for scientific data management and stewardship
Abstract There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
- National Institutes of Health United States
- Leiden University Netherlands
- Harvard University United States
- University Medical Center Groningen Netherlands
- University of Lausanne Switzerland
Medicin och hälsovetenskap, environment assessment, EMC NIHES-03-77-01, Medical and Health Sciences, invasive species, 46 Information and Computing Sciences (for-2020), Chapter 2, data stewardship, Reproducibility of Results (mesh), Alien Invasive Species Assessment AIS, Data Curation, Chapter 6, biodiversity, Informática, PROTEIN DATA-BANK, FAIR principles, Data Collection, scientific data, Database Management Systems (mesh), 004, Computer Science Applications, Research Design, publication characteristics, Statistics, Probability and Uncertainty, Healthy Living, Information Systems, Statistics and Probability, Computer and Information Sciences, 330, Publication characteristics, 4610 Library and Information Studies (for-2020), BIOLOGY, Guidelines as Topic, Library and Information Sciences, Education, SDG 17 - Partnerships for the Goals, Library and Information Studies, Information and Computing Sciences, Life Science, IPBES, Data Collection (mesh), 020, Data Curation (mesh), Comment, Reproducibility of Results, 028, Data- och informationsvetenskap, Guidelines as Topic (mesh), Research data, Database Management Systems, Research Design (mesh)
Medicin och hälsovetenskap, environment assessment, EMC NIHES-03-77-01, Medical and Health Sciences, invasive species, 46 Information and Computing Sciences (for-2020), Chapter 2, data stewardship, Reproducibility of Results (mesh), Alien Invasive Species Assessment AIS, Data Curation, Chapter 6, biodiversity, Informática, PROTEIN DATA-BANK, FAIR principles, Data Collection, scientific data, Database Management Systems (mesh), 004, Computer Science Applications, Research Design, publication characteristics, Statistics, Probability and Uncertainty, Healthy Living, Information Systems, Statistics and Probability, Computer and Information Sciences, 330, Publication characteristics, 4610 Library and Information Studies (for-2020), BIOLOGY, Guidelines as Topic, Library and Information Sciences, Education, SDG 17 - Partnerships for the Goals, Library and Information Studies, Information and Computing Sciences, Life Science, IPBES, Data Collection (mesh), 020, Data Curation (mesh), Comment, Reproducibility of Results, 028, Data- och informationsvetenskap, Guidelines as Topic (mesh), Research data, Database Management Systems, Research Design (mesh)
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