Accessibility Tools
Making data FAIR – findable, accessible, interoperable, reusable – is becoming more and more the standard expectation for European research projects.
The future European Open Science Cloud (EOSC) will also rely on FAIR data. To make this happen, EUA is a core partner of the FAIRsFAIR project funded through Horizon 2020.
FAIRsFAIR aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle with emphasis on fostering FAIR data culture and the uptake of good practices in making data FAIR. FAIRsFAIR will facilitate sharing of knowledge, expertise, guidelines, courses and education needed to turn the FAIR principles into reality.
Within the project, EUA is leading a work package on “FAIR Data Science and Professionalisation” (WP7). FAIRsFAIR WP7 aims to support higher education institutions to sustainably increase their capacity to equip more students and doctoral researchers with FAIR data-related skills and competences. To achieve this, the activities of WP7 are centred around four main objectives:
For more information, please visit the project website.
For questions about FAIRsFAIR and the involvement of EUA, please contact Federica Garbuglia.
FAIRsFAIR has received funding from the European Union’s Horizon 2020 project call H2020-INFRAEOSC-2018-5-2018-2019 (c), grant agreement 831558.
FAIRsFAIR WP7 ultimately aims to foster the uptake of FAIR data-related skills and material in university curricula and programmes across levels and disciplines. To do so, project partners involved in WP7 have developed two practical tools guiding universities in developing new teaching and training activities that can support the ability of students and researchers to put the FAIR principles into practice.
The handbook provides ready-to-use model lesson plans on a variety of topics, including FAIR data, Data Management Plans (DMPs), repositories, data creation and reuse. Furthermore, it offers FAIR competence profiles and learning outcomes for the bachelor, master and doctoral levels as well as information on course design and the implementation of the FAIR principles on the institutional level. The handbook is available in three versions: as a project deliverable on Zenodo, as an Open Access PDF and as a print publication.
The deliverable presents a collection of seven good practices highlighting stories of successful integration of Research Data Management (RDM) and FAIR data-related skills in university curricula and training. In this report, universities will find points of inspiration and practical examples of how fellow institutions and organisations in the higher education sector addressed the need for more RDM and FAIR data-related skills to be taught at the bachelor, master and doctoral levels. The report is available on Zenodo, here.
The handbook and the good practices report are deeply rooted in previous results and activities achieved by WP7 partners within their efforts to map and advance the integration of FAIR data skills in higher education curricula. These include:
To promote the results and gather feedback for the deliverables, WP7 organised two series of workshop to bring results from FAIRsFAIR closer to universities and key stakeholders and gather feedback from the community.
This series of three online workshops explored different topics related to FAIR data education and was organised in collaboration with stakeholder organisations in the field of higher education and research to maximise synergies and foster cooperation.
Results from the workshop are available here. The recording of the event can be found here.
EUA together with partners from FAIRsFAIR WP7 organised three online workshops to support higher education institutions in embedding FAIR competences in their curricular and research training programmes.
Results from the workshop are available here. The recording of the event can be found here (day 1) and here (day 2).
The FAIRsFAIR project addresses the development and concrete realisation of an overall knowledge infrastructure on academic quality data management, procedures, standards, metrics and related matters, based on the FAIR data principles.
FAIRsFAIR will play a key role in the development of global standards for FAIR certification of repositories and the data within them contributing to those policies and practices that will turn the EOSC programme into a functioning infrastructure. By the end of its activities, FAIRsFAIR will provide a platform for using and implementing the FAIR principles in the day-to-day work of European research data professionals and repositories.
On the technical level, the project seeks to support the development and certification of repositories. By doing so it will contribute to the broader change required to achieve widespread adoption of FAIR practices within the EOSC and beyond.
The objectives of FAIRsFAIR in a nutshell are to:
