Data Science Journal (Sep 2023)

Umbrella Data Management Plans to Integrate FAIR Data: Lessons From the ISIDORe and BY-COVID Consortia for Pandemic Preparedness

  • Romain David,
  • Audrey S. Richard,
  • Claire Connellan,
  • Katharina B. Lauer,
  • Maria Luisa Chiusano,
  • Carole Goble,
  • Martin Houde,
  • Isabel Kemmer,
  • Antje Keppler,
  • Philippe Lieutaud,
  • Christian Ohmann,
  • Maria Panagiotopoulou,
  • Sara Raza Khan,
  • Arina Rybina,
  • Stian Soiland-Reyes,
  • Charlotte Wit,
  • Rudolf Wittner,
  • Rafael Andrade Buono,
  • Sarah Arnaud Marsh,
  • Pauline Audergon,
  • Dylan Bonfils,
  • Jose-Maria Carazo,
  • Remi Charrel,
  • Frederik Coppens,
  • Wolfgang Fecke,
  • Claudia Filippone,
  • Eva Garcia Alvarez,
  • Sheraz Gul,
  • Henning Hermjakob,
  • Katja Herzog,
  • Petr Holub,
  • Lukasz Kozera,
  • Allyson L. Lister,
  • José López-Coronado,
  • Bénédicte Madon,
  • Kurt Majcen,
  • William Martin,
  • Wolfgang Müller,
  • Elli Papadopoulou,
  • Christine M.A. Prat,
  • Paolo Romano,
  • Susanna-Assunta Sansone,
  • Gary Saunders,
  • Niklas Blomberg,
  • Jonathan Ewbank

DOI
https://doi.org/10.5334/dsj-2023-035
Journal volume & issue
Vol. 22
pp. 52 – 52

Abstract

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The Horizon Europe project ISIDORe is dedicated to pandemic preparedness and responsiveness research. It brings together 17 research infrastructures (RIs) and networks to provide a broad range of services to infectious disease researchers. An efficient and structured treatment of data is central to ISIDORe’s aim to furnish seamless access to its multidisciplinary catalogue of services, and to ensure that users’ results are treated FAIRly. ISIDORe therefore requires a data management plan (DMP) covering both access management and research outputs, applicable over a broad range of disciplines, and compatible with the constraints and existing practices of its diverse partners. Here, we describe how, to achieve that aim, we undertook an iterative, step-by-step, process to build a community-approved living document, identifying good practices and processes, on the basis of use cases, presented as proof of concepts. International fora such as the RDA and EOSC, and primarily the BY-COVID project, furnished registries, tools and online data platforms, as well as standards, and the support of data scientists. Together, these elements provide a path for building an umbrella, FAIR-compliant DMP, aligned as fully as possible with FAIR principles, which could also be applied as a framework for data management harmonisation in other large-scale, challenge-driven projects. Finally, we discuss how data management and reuse can be further improved through the use of knowledge models when writing DMPs and, how, in the future, an inter-RI network of data stewards could contribute to the establishment of a community of practice, to be integrated subsequently into planned trans-RI competence centres.

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