Experts from ELIXIR-coordinated project FAIRplus worked with the RESOLUTE consortium to FAIRify their early data outcomes and to establish sustainable FAIR data processes.
Data FAIRification makes research data FAIR: Findable, Accessible, Interoperable and Reusable. FAIR data are then easily accessible to other researchers who can combine them with their own data or re-use them in different contexts. This in turn leads to wider sharing of knowledge and greater opportunities for innovation.
The objective of RESOLUTE - an Innovative Medicine Initiative (IMI) project - is to boost research on solute carriers (SLCs) - a group of proteins that transport substances across biological membranes. FAIRplus experts were working with the RESOLUTE consortium throughout 2019 to FAIRify the baseline data generated early on in the project and to establish data management processes based on FAIR principles.
As a result of the collaboration, the baseline expression data produced by the project are now available in a public database. All future results and data generated by RESOLUTE will have to be compared with the baseline data, so it’s essential that they be findable and accessible. Even though this was just the first step in the FAIRification process, it already has a big impact on the potential reuse of RESOLUTE outcomes.
The FAIRplus experts have summarised their experience from FAIRifying the RESOLUTE transcriptomic data in a step-by-step recipe published in FAIRplus’s FAIR cookbook. The recipe identifies the appropriate identifiers for the data and proposes a new schema for transcriptomic data, based on existing community standards and submission guidelines of popular transcriptomics databases.
Read the full story on the FAIRplus website »
About FAIRplus
The FAIRplus project - led by ELIXIR and Janssen and funded by EU’s Innovative Medicine Initiative (IMI) - develops tools and guidelines for making life science data Findable, Accessible, Interoperable, Reusable (FAIR). One of the activities of the project is to support selected IMI projects to FAIRify their datasets and adopt FAIR data principles. In 2019, the project FAIRified datasets from four IMI projects (including RESOLUTE), data from further nine projects are being FAIRified in 2020.
Other activities include the FAIR cookbook or the FAIRplus Fellowship Programme. In January 2020, the project organised the first FAIRplus Innovation and SME Forum to present the first outcomes of the project and discuss practical challenges in adopting and implementing FAIR data principles in life science research.
FAIRplus is a public-private partnership with 22 partners from academia, pharmaceutical companies and SMEs.
More information: https://fairplus-project.eu
Acknowledgement
FAIRplus project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 802750. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA Companies. This communication reflects the views of the authors and neither IMI nor the European Union, EFPIA or any Associated Partners are liable for any use that may be made of the information contained herein.