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FAIR in action - a flexible framework to guide FAIRification.
Welter, Danielle; Juty, Nick; Rocca-Serra, Philippe; Xu, Fuqi; Henderson, David; Gu, Wei; Strubel, Jolanda; Giessmann, Robert T; Emam, Ibrahim; Gadiya, Yojana; Abbassi-Daloii, Tooba; Alharbi, Ebtisam; Gray, Alasdair J G; Courtot, Melanie; Gribbon, Philip; Ioannidis, Vassilios; Reilly, Dorothy S; Lynch, Nick; Boiten, Jan-Willem; Satagopam, Venkata; Goble, Carole; Sansone, Susanna-Assunta; Burdett, Tony.
  • Welter D; Luxembourg Centre for Systems Biomedicine, ELIXIR Luxembourg, University of Luxembourg, L-4367, Belval, Luxembourg.
  • Juty N; University of Manchester, Department of Computer Science, The University of Manchester, Manchester, M13 9PL, UK.
  • Rocca-Serra P; Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, OX13QG, Oxford, UK.
  • Xu F; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK.
  • Henderson D; Bayer AG, Business Development & Licensing & OI, Muellerstrasse 178, 13353, Berlin, Germany.
  • Gu W; Luxembourg Centre for Systems Biomedicine, ELIXIR Luxembourg, University of Luxembourg, L-4367, Belval, Luxembourg.
  • Strubel J; The Hyve BV, Arthur van Schendelstraat 650, 3511 MJ, Utrecht, The Netherlands.
  • Giessmann RT; Bayer AG, Business Development & Licensing & OI, Muellerstrasse 178, 13353, Berlin, Germany.
  • Emam I; Institute for Globally Distributed Open Research and Education (IGDORE), Gothenburg, Sweden.
  • Gadiya Y; Data Science Institute, Imperial College, London, UK.
  • Abbassi-Daloii T; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP) and Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Schnackenburgallee 114, 22525 Hamburg, and Theodor Stern Kai 7, 60590, Frankfurt, Germany.
  • Alharbi E; Department of Bioinformatics (BiGCaT), NUTRIM, FHML, Maastricht University, Maastricht, The Netherlands.
  • Gray AJG; College of Computer and Information Systems, Umm Al-Qura University, Mecca, Saudi Arabia.
  • Courtot M; Department of Computer Science, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK.
  • Gribbon P; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK.
  • Ioannidis V; Ontario Institute for Cancer Research MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, M5G 0A3, Canada.
  • Reilly DS; Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP) and Fraunhofer Cluster of Excellence for Immune Mediated Diseases (CIMD), Schnackenburgallee 114, 22525 Hamburg, and Theodor Stern Kai 7, 60590, Frankfurt, Germany.
  • Lynch N; Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
  • Boiten JW; Novartis Institutes for BioMedical Research, Novartis Pharma AG, Basel, Switzerland.
  • Satagopam V; OpenPhacts Foundation, Cambridge, UK.
  • Goble C; Foundation Lygature, Utrecht, Netherlands.
  • Sansone SA; Luxembourg Centre for Systems Biomedicine, ELIXIR Luxembourg, University of Luxembourg, L-4367, Belval, Luxembourg.
  • Burdett T; University of Manchester, Department of Computer Science, The University of Manchester, Manchester, M13 9PL, UK.
Sci Data ; 10(1): 291, 2023 05 19.
Article in English | MEDLINE | ID: covidwho-2327037
ABSTRACT
The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Datasets as Topic / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Sci Data Year: 2023 Document Type: Article Affiliation country: S41597-023-02167-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Datasets as Topic / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Sci Data Year: 2023 Document Type: Article Affiliation country: S41597-023-02167-2