Accelerating the adoption of research data management strategies

Johanne Medina*, Abdul Wahab Ziaullah, Heesoo Park, Ivano E. Castelli, Arif Shaon, Halima Bensmail, Fedwa El-Mellouhi*

*Corresponding author for this work

Research output: Contribution to journalComment/debateResearchpeer-review


The need for good research data management (RDM) practices is becoming more recognized as a critical part of research. This may be attributed to the 5V challenge in big data: volume, variety, velocity, veracity, and value. The materials science community is no exception to these challenges as it heralds its new paradigm of data-driven science, which uses artificial intelligence to accelerate materials discovery but requires massive datasets to perform effectively. Hence, there are efforts to standardize, curate, pre-serve, and disseminate these data in a way that is findable, acces-sible, interoperable, and reusable (FAIR). To understand the cur-rent state of data-driven materials science and learn about the challenges faced with RDM, we gather user stories of researchers from small-and large-scale projects. This enables us to provide relevant recommendations within the data-driven research life cy-cle to develop and/or procure an effective RDM system following the FAIR guiding principles.
Original languageEnglish
Issue number11
Pages (from-to)3614-3642
Number of pages29
Publication statusPublished - 2022


  • FAIR guiding principles
  • Research data management
  • Data-driven research
  • Materials science
  • Batteries
  • Perovskite crystal structure
  • Photovoltaic devices


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