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The FAIR Guiding Principles for scientific data management and stewardship

Abstract (Expand)

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.

Author: Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingr Mons

Date Published: 15th Mar 2016

Publication Type: Not specified

Semantic Data and Models Sharing in Systems Biology: The Just Enough Results Model and the SEEK Platform

Abstract

Not specified

Authors: Katherine Wolstencroft, Stuart Owen, Olga Krebs, Wolfgang Mueller, Quyen Nguyen, Jacky L. Snoep, Carole Goble

Date Published: 2013

Publication Type: Not specified

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