
Slidedeck from the second LEARNFAIR trainer community meeting on 10 March 2026, 13.00 - 17.00. The goal of this community is to foster collaboration and to work towards open educational resources in order to strengthen FAIR data skills in the Life Sciences & Health (LSH) domain. The first part of the meeting focused on strengthening the community, with ample room to get to know each other and pitches from community members on topics related to RDM and FAIR training and datastewardship. The second part of the agenda focused on FAIR and Open Educational Resources, with results from the LEARNFAIR survey and literature and repository reviews conducted in the project. Finally, Maria Vivas-Romero led a hands-on session on how to turn training materials into FAIR and Open Educational Resources. LEARNFAIR (Life Science & Health Educational Alignment for Research and Networking in FAIR Data Management) is a two-year national project funded by the NWO - TDCC LSH 2023 challenge call aimed at strengthening digital competences in the data-driven life sciences and health domain.
Training, Open Educataional Resources, community building, FAIR
Training, Open Educataional Resources, community building, FAIR
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
