the University of Sheffield Library worked with researchers in seven disciplines to develop subject-specific FAIR checklists for the use of colleagues before, during and at the end of their research project.
This handbook aims to support higher education institutions with the integration of FAIR-related content in their curricula and teaching. It was written and edited by a group of about 40 collaborators in a series of six book sprint events that took place between 1 and 10 June 2021. The document provides practical material, such as competence profiles, learning outcomes and lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021.
This handbook aims to support higher education institutions with the integration of FAIR-related content in their curricula and teaching. It was written and edited by a group of about 40 collaborators in a series of six book sprint events that took place between 1 and 10 June 2021. The document provides practical material, such as competence profiles, learning outcomes and lesson plans, and supporting information. It incorporates community feedback received during the public consultation which ran from 27 July to 12 September 2021.
online tool which helps researchers and data managers assess how much they know about the requirements for making datasets findable, accessible, interoperable, and reusable (FAIR) before uploading them into a data repository.
Representatives from journals, journal publishers and scholarly communication organisations have come together in the FAIRsharing Community to propose a set of criteria for the identification and selection of those data repositories that accept research data submissions. These repositories can be recommended to researchers when they are preparing to release and publish the data underlying their findings. This work intends to (i) reduce complexity and inconsistencies for researchers in journal data policies, (ii) increase efficiency for data repositories that currently have to work with all individual publishers, and (iii) simplify the process of recommending data repositories by publishers. This work will make the implementation of research data policies more efficient and consistent, which may help to improve approaches to data sharing through the promotion and the use of reliable and sustainable data repositories.
The Top 10 FAIR Data & Software Things are brief guides (stand alone, self paced training materials), called ‘Things’, that can be used by the research community to understand how they can make their research (data and software) more FAIR (Findable, Accessible, Interoperable and Reusable).
A. Ferraro, X. Serra, и C. Bauer. том 12933 из Lecture Notes in Computer Science, глава 33, стр. 562-584. Springer International Publishing, Cham, Germany, (2021)