Marjan Grootveld & Ingrid Dillo

Marjan Grootveld & Ingrid Dillo

Last updated on 17 June 2021

Marjan Grootveld is Research Data Expert Team Leader at DANS and Ingrid Dillo is Deputy Director at DANS and FAIRsFAIR project coordinator.

Ever since the origin of the FAIR data guiding principles in 2014, Data Archiving and Networked Services (DANS) staff have been involved in activities on thinking about their implications and implementing them. The conviction that research data sets in our long-term repository and in other repositories should be Findable, Accessible, Interoperable, and Reusable is deeply ingrained in the DANS organisation and in our services. We were involved as co-authors of the original publication on the FAIR principles, developed and tested FAIR metrics, worked on tools to rate the FAIRness of datasets, evaluated how our own data archives score on FAIRness, compared the principles to the requirements of the Data Seal of Approval and the CoreTrustSeal, and explored the applicability of the FAIR principles to Software Sustainability. At iPRES 2019 we presented an overview of our first five years of FAIR activities.

Last year DANS celebrated its 15th anniversary. In 2005, we started out as a team of 15; now there are 60 of us. With more than 170,000 datasets, DANS is in the top five of similar long-term repositories in the world. And FAIRness made it to the title of our multi-annual strategy: “Focus on FAIR: DANS 2021-2025”. The use of FAIR data improves the verifiability and reproducibility of research. It also enhances efficiency because building datasets is expensive. What is more, linking data can lead to new discoveries and insights. Reusing and connecting data accelerates knowledge circulation and increases our ability to solve complex issues. In short, making better use of data leads to better science, which matters to society.

However, mentioning this in a DPC blog post is preaching to the choir. It is others who we need to convince and, more importantly, to support: researchers. Many researchers are as yet unfamiliar with the FAIR principles, as for instance the State of Open Data 2020 indicates,and may not put them into practice. FAIR-Aware is the very tool for this situation: it is an online self-assessment tool which helps researchers and data stewards to assess and increase their knowledge on how to make a dataset FAIR before depositing it in a repository. Ten questions take them along data aspects such as discovery metadata, licence and provenance information, sustainable file formats and persistent identifiers, with rich guidance for each question. After submitting the online questionnaire, the tool returns a “FAIR Awareness” score and suggestions for making the dataset more FAIR.

FAIR-Aware is co-developed by DANS, together with DCC and PANGAEA, in the context of the FAIRsFAIR - Fostering FAIR Data Practices in Europe – project, led by DANS. In a process of continuous improvement we have learned that the tool does what it should do, is easy to use, and is getting popular with data management trainers. This encourages us to share it with you, hoping that it fits your organisation’s outreach programme. You can get started with the FAIR-Aware tool yourself via the website or watch the video first. DANS and FAIRsFAIR would love to hear your feedback.

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