TRUST article in SCIENTIFIC DATA

Just published: our article on TRUST in the Springer journal Scientific Data https://doi.org/10.1038/s41597-020-0486-7

The TRUST principles for digital repositories are a natural consequence of the FAIR data principles. FAIR (Findable, Accesible, Interoperable and Re-usable) data cannot stay FAIR for the longer term if they are not taken care for by repositories that act according to the TRUST principles.

The TRUST principles are about Transparancy, Responsibility, User focus, Sustainability and Technology. The principles are based on OAIS and various certification approaches like the CoreTrustSeal and ISO 163636 and translate the essence of these ‘standards’ into a set of principles that will be more appealing to an audience that is not familiair with digital preservation. An audience that need to have their data preserved for the longer term and will need repositories to do this. With TRUST they will know what they can expect from the repositories.

I became involved in this work after my blog post about the white paper on TRUST. My criticism in that post was partly based on misunderstanding and missing concepts – too little digital preservation in the draft. But they asked me to join and I’m happy I did. The white paper received public feedback and the idea was presented at various conferences like the meetings of the Research Data Alliance, where the idea for TRUST started. I did a 5 minute presentation during the Ad Hoc programme of iPRES 2019 to inform the digital preservation community about this concept.

It was really a joy to work with people from so many different disciplines of which I only knew a few from sharing drinks and snacks at an RDA meeting. We are missing those meetings now but the publication of the article shows that there is so much possible in the virtual world!

Lin, D., Crabtree, J., Dillo, I. et al. The TRUST Principles for digital repositories. Sci Data 7, 144 (2020). https://doi.org/10.1038/s41597-020-0486-7

© 2020 Barbara Sierman

b-s-i-e-r-m-a-n-@-d-i-g-i-t-a-l-p-r-e-s-e-r-v-a-t-i-o-n-.-n-l