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FAIR-4-GSC-Sansone-Aug23.pdf

Susanna-Assunta Sansone
Susanna-Assunta Sansone

FAIR principle, FAIR Cookbook and FAIRsharing: https://genomicsstandardsconsortium.github.io/GSC23-Bangkok

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The FAIR Principles: from theory to practice GSC 23rd meeting, Bangkok, Thailand, 7-11 August, 2023 slideshare.net/SusannaSansone Academic Lead for Research Practice Professor of Data Readiness Susanna-Assunta Sansone, PhD Associate Director 0000-0001-5306-5690 @SusannaASansone susanna-assunta.sansone@oerc.ox.ac.uk datareadiness.eng.ox.ac.uk
This requires data that are: Cited and stored to be discoverable Retrievable and structured in standard format(s) Richly described to be understandable Discovery are made using shared data https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-ti me-consuming-least-enjoyable-data-science-task-survey-says/#276a35e6f637
A set of principles to enhance the value of all digital resources and its reuse by humans and machines Data that is discoverable and usable at scale
Globally unique and persistent identi鍖ers Community de鍖ned descriptive metadata Community de鍖ned terminologies Detailed provenance Terms of access Terms of use The FAIR Principles in a nutshell
doi.org/10.2777/1524 www.gov.uk/government/publications/open-researc h-data-task-force-final-report www.turing.ac.uk/research/impact-stories/changing-culture-data- science FAIR has become a global norm for good research data management practices www.fair-access.net.au doi.org/10.1787/25186167 https://unesdoc.unesco.org/ark:/482 23/pf0000379949.locale=en
Biopharma R&D productivity can be improved by implementing the FAIR Principles FAIR enables powerful new AI analytics to access data for machine learning and prediction FAIR-driven digital transformation in pharmas
https://doi.org/10.1371/journal.pcbi.1007854 https://doi.org/10.1371/journal.pcbi.1007854 Software Training material Extending the reach of FAIR to other digital objects
Turning FAIR into practice: what is the problem? These high-level FAIR Guiding Principles precede implementation choices, and do not suggest any speci鍖c technology, standard, or implementation-solution; moreover, the Principles are not, themselves, a standard or a speci鍖cation. They act as a guide to data publishers and stewards to assist them in evaluating whether their particular implementation choices are rendering their digital research artefacts Findable, Accessible, Interoperable, and Reusable.
Turning FAIR into practice: what is the problem? It is a set of guiding principles that provide for a continuum of increasing reusability, via many different implementations These high-level FAIR Guiding Principles precede implementation choices, and do not suggest any speci鍖c technology, standard, or implementation-solution; moreover, the Principles are not, themselves, a standard or a speci鍖cation. They act as a guide to data publishers and stewards to assist them in evaluating whether their particular implementation choices are rendering their digital research artefacts Findable, Accessible, Interoperable, and Reusable.
Connect Discover Describe fairsharing.org contact@fairsharing.org Practical guidance on how to FAIR and standards faircookbook.elixir-europe.org faircookbook-ed@elixir-europe.org
Authored by almost 100 data professionals from industry and academia, led by ELIXIR Nodes, with participation of USA NIH An open, live resource for the life science with recipes that cover the operation steps of FAIR data management Adopted internationally! Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools Recommend in policies, use in educational material Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools
Goal: improving visibility of content, e.g.: Goal: semantic integration of datasets from multiple sources, e.g.: Goal: security compliance and with regulators, e.g.: https://w3id.org/faircookbook/FCB010 https://w3id.org/faircookbook/FCB007 https://w3id.org/faircookbook/FCB006 https://w3id.org/faircookbook/FCB020 https://w3id.org/faircookbook/FCB004 https://w3id.org/faircookbook/FCB014 https://w3id.org/faircookbook/FCB035 Hands-on recipes, focused on addressing needs
Contribute: citable, credited, hands-on focused
As educational material on FAIR in a training context As a practical guidance to improve day-to-day tasks for FAIRer data As contributor towards changing the culture and to identify investment areas in research data management Utility and value: academics and pharma context https://doi.org/10.1038/s41597-023-02166-3
https://w3id.org/faircookbook/FCB079 FAIRification paths: one size does not fit all Molecular data Clinical (observation based) data Clinical trial (event based) data Different contexts mandate different metadata strategies and standards https://doi.org/10.1038/s41597-023-02167-2
A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies Adopted internationally! Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools 1. Guides consumers to discover, select and use these resources with confidence 2. Helps producers to make their resources more visible, more widely adopted and cited 3. Powers third party tools by providing trustworthy content to promote standards and databases Promote the value and use of these resources across all disciplines Adopted internationally!
Over 2885 standards & databases in the Life Science Identifiers Terminologies Guidelines Formats
GSC collection of standards interlinked to databases and policies fairsharing.org/GSC
GSC collection of standards interlinked to databases and policies fairsharing.org/GSC
Educational material on standards and databases for all stakeholders fairsharing.org/educational
European Research Landscape Study 2022 Publications Office of the European Union, 2022, https://data.europa.eu/doi/10.2777/3648; Also https://indico.lip.pt/event/1249/contributions/4555/ Objectives: To collect data on the level of maturity with respect to FAIR data implementation To assess responsiveness and readiness of research data repositories in terms of implementation of FAIR principles Scope: All fields of science Survey of researchers: 15066 responses Desk research; case studies; FAIRness assessment
And not everything that can be measured matters! Strive for the FAIR enough! Follow your data journey and your needs! More importantly in the current tools the tests used and the result given, are not comparable!! The cottage industry of FAIR evaluation fairassist.org As of July 2023, there are 25 independent evaluation tools!
Turning FAIR into reality requires we: deliver a number of research infrastructures and tools implement standards for data and metadata address policies, education and training overcome technical, social and cultural challenges identify motivators, credit and rewards mechanisms The road to FAIR data
Let's keep building and sharing good research data management practices! Researchers Developers and curators Journal publishers Societies and Alliances Librarians and Trainers Funders dataset software models workflows code
fairsharing.org faircookbook.elixir-europe.org faircookbook.elixir-europe.org/cont ent/recipes/afterword/people.html sansonegroup.eng.ox.ac.uk

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FAIR-4-GSC-Sansone-Aug23.pdf

  • 1. The FAIR Principles: from theory to practice GSC 23rd meeting, Bangkok, Thailand, 7-11 August, 2023 slideshare.net/SusannaSansone Academic Lead for Research Practice Professor of Data Readiness Susanna-Assunta Sansone, PhD Associate Director 0000-0001-5306-5690 @SusannaASansone susanna-assunta.sansone@oerc.ox.ac.uk datareadiness.eng.ox.ac.uk
  • 2. This requires data that are: Cited and stored to be discoverable Retrievable and structured in standard format(s) Richly described to be understandable Discovery are made using shared data https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-ti me-consuming-least-enjoyable-data-science-task-survey-says/#276a35e6f637
  • 3. A set of principles to enhance the value of all digital resources and its reuse by humans and machines Data that is discoverable and usable at scale
  • 4. Globally unique and persistent identi鍖ers Community de鍖ned descriptive metadata Community de鍖ned terminologies Detailed provenance Terms of access Terms of use The FAIR Principles in a nutshell
  • 5. doi.org/10.2777/1524 www.gov.uk/government/publications/open-researc h-data-task-force-final-report www.turing.ac.uk/research/impact-stories/changing-culture-data- science FAIR has become a global norm for good research data management practices www.fair-access.net.au doi.org/10.1787/25186167 https://unesdoc.unesco.org/ark:/482 23/pf0000379949.locale=en
  • 6. Biopharma R&D productivity can be improved by implementing the FAIR Principles FAIR enables powerful new AI analytics to access data for machine learning and prediction FAIR-driven digital transformation in pharmas
  • 8. Turning FAIR into practice: what is the problem? These high-level FAIR Guiding Principles precede implementation choices, and do not suggest any speci鍖c technology, standard, or implementation-solution; moreover, the Principles are not, themselves, a standard or a speci鍖cation. They act as a guide to data publishers and stewards to assist them in evaluating whether their particular implementation choices are rendering their digital research artefacts Findable, Accessible, Interoperable, and Reusable.
  • 9. Turning FAIR into practice: what is the problem? It is a set of guiding principles that provide for a continuum of increasing reusability, via many different implementations These high-level FAIR Guiding Principles precede implementation choices, and do not suggest any speci鍖c technology, standard, or implementation-solution; moreover, the Principles are not, themselves, a standard or a speci鍖cation. They act as a guide to data publishers and stewards to assist them in evaluating whether their particular implementation choices are rendering their digital research artefacts Findable, Accessible, Interoperable, and Reusable.
  • 10. Connect Discover Describe fairsharing.org contact@fairsharing.org Practical guidance on how to FAIR and standards faircookbook.elixir-europe.org faircookbook-ed@elixir-europe.org
  • 11. Authored by almost 100 data professionals from industry and academia, led by ELIXIR Nodes, with participation of USA NIH An open, live resource for the life science with recipes that cover the operation steps of FAIR data management Adopted internationally! Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools Recommend in policies, use in educational material Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools
  • 12. Goal: improving visibility of content, e.g.: Goal: semantic integration of datasets from multiple sources, e.g.: Goal: security compliance and with regulators, e.g.: https://w3id.org/faircookbook/FCB010 https://w3id.org/faircookbook/FCB007 https://w3id.org/faircookbook/FCB006 https://w3id.org/faircookbook/FCB020 https://w3id.org/faircookbook/FCB004 https://w3id.org/faircookbook/FCB014 https://w3id.org/faircookbook/FCB035 Hands-on recipes, focused on addressing needs
  • 13. Contribute: citable, credited, hands-on focused
  • 14. As educational material on FAIR in a training context As a practical guidance to improve day-to-day tasks for FAIRer data As contributor towards changing the culture and to identify investment areas in research data management Utility and value: academics and pharma context https://doi.org/10.1038/s41597-023-02166-3
  • 15. https://w3id.org/faircookbook/FCB079 FAIRification paths: one size does not fit all Molecular data Clinical (observation based) data Clinical trial (event based) data Different contexts mandate different metadata strategies and standards https://doi.org/10.1038/s41597-023-02167-2
  • 16. A curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies Adopted internationally! Hands-on, technical step-by-step examples Write recipes, share your expertise, showcase your tools 1. Guides consumers to discover, select and use these resources with confidence 2. Helps producers to make their resources more visible, more widely adopted and cited 3. Powers third party tools by providing trustworthy content to promote standards and databases Promote the value and use of these resources across all disciplines Adopted internationally!
  • 17. Over 2885 standards & databases in the Life Science Identifiers Terminologies Guidelines Formats
  • 18. GSC collection of standards interlinked to databases and policies fairsharing.org/GSC
  • 19. GSC collection of standards interlinked to databases and policies fairsharing.org/GSC
  • 20. Educational material on standards and databases for all stakeholders fairsharing.org/educational
  • 21. European Research Landscape Study 2022 Publications Office of the European Union, 2022, https://data.europa.eu/doi/10.2777/3648; Also https://indico.lip.pt/event/1249/contributions/4555/ Objectives: To collect data on the level of maturity with respect to FAIR data implementation To assess responsiveness and readiness of research data repositories in terms of implementation of FAIR principles Scope: All fields of science Survey of researchers: 15066 responses Desk research; case studies; FAIRness assessment
  • 22. And not everything that can be measured matters! Strive for the FAIR enough! Follow your data journey and your needs! More importantly in the current tools the tests used and the result given, are not comparable!! The cottage industry of FAIR evaluation fairassist.org As of July 2023, there are 25 independent evaluation tools!
  • 23. Turning FAIR into reality requires we: deliver a number of research infrastructures and tools implement standards for data and metadata address policies, education and training overcome technical, social and cultural challenges identify motivators, credit and rewards mechanisms The road to FAIR data
  • 24. Let's keep building and sharing good research data management practices! Researchers Developers and curators Journal publishers Societies and Alliances Librarians and Trainers Funders dataset software models workflows code
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