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      Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud

      research-article
      a , b , c , * , d , e , f , b , g , h
      Information Services & Use
      IOS Press
      FAIR Data, Open Science, interoperability, data integration, standards

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          Abstract

          The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not.

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          Most cited references3

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          The operated Markov´s chains in economy (discrete chains of Markov with the income)

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            The center for expanded data annotation and retrieval.

            The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments.
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              Enterprise Interoperability in the Digitized and Networked Factory of the Future

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                Author and article information

                Journal
                ISU
                Information Services & Use
                IOS Press (Nieuwe Hemweg 6B, 1013 BG Amsterdam, The Netherlands )
                1875-8789
                0167-5265
                17 February 2017
                7 March 2017
                2017
                : 37
                : 1
                : 49-56
                Affiliations
                [a ] Leiden University Medical Centre , Leiden, The Netherlands. E-mail:  b.mons@ 123456lumc.nl
                [b ] Dutch Techcentre for Life Sciences , Utrecht, The Netherlands
                [c ] Netherlands eScience Centre , Amsterdam, The Netherlands
                [d ]Centre for Culture and Technology, Curtin University , Perth, Western Australia
                [e ] Independent Open Access Publishing Consultant , Guildford, United Kingdom
                [f ]Institute for Data Science, Maastricht University , Maastricht, The Netherlands
                [g ] Vrije Universiteit Amsterdam , Amsterdam, The Netherlands
                [h ] Centre for Plant Biotechnology and Genomics U.P.M. – I.N.I.A. , Madrid, Spain
                Author notes
                [* ]Corresponding author: Barend Mons, Einthovenweg 20, 2333 ZC Leiden, P.O. Box 9600, 2300 RC Leiden, The Netherlands. Tel.: +31624879779; E-mail:  b.mons@ 123456lumc.nl .
                Article
                ISU824
                10.3233/ISU-170824
                98eea929-d7f2-43e2-87d0-094838f3830d
                IOS Press and the authors.

                This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Categories
                Regular Papers

                Information & Library science,Communication & Media studies
                interoperability,standards,data integration,Open Science,FAIR Data

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