Improving Citation of evolving data in distributed asynchronous infrastructures

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18 December 2018 2862 reads

Implementing RDA Recommendations Data Citation and Scholix in VAMDC for molecular and atomic data.


The Virtual Atomic and Molecular Data Centre (VAMDC) implemented on the one hand, the RDA recommendations for Data Citation to identify and cite dynamic data. On the other hand the Scholix output to link datasets from from the VAMDC.


“Citation is a key element in the production of new knowledge, since it enhances trust, makes the process described into the cited work reproducible and gives credits to the author of the cited intellectual product. According to the FAIR principles, most of the data should be re-used in derived works: the role of Citation is crucial in open-data-driven science. The RDA has successfully defined new models for citation in the digital era.  Several communities already adopted these RDA outputs and shown the implementation way: it is now easy for “newcomers” to adopt those useful recommendations by capitalizing on the community experience.


Dr. Carlo Maria Zwölf, Nicolas Moreau and Yaye-Awa Ba from PSL Research University, CNRS and the Sorbonne University.


Which RDA outputs have been implemented?

The VAMDC Consortium is a consortium of Institutes and Research Institutions that share a common technical and political framework for the distribution and curation of atomic and molecular data. The VAMDC Consortium technical framework relies on the use of the e-science VAMDC infrastructure that provides the international research community with access to a broad range of atomic and molecular (A&M) data compiled within a set of A&M databases accessible through the provision of a single portal. Furthermore, VAMDC aims to provide A&M data providers and compilers with a large dissemination platform for their work.


By adopting the Data Citation recommendation, we provide the VAMDC users with the capability to uniquely refer-to and cite a given datum extracted from VAMDC. This increases the FAIR-ness of our data, since reusability relies on the ability of making clear what is reused. On the other hand, Scholix motivates data producers to share their data through the VAMDC infrastructure rather than through personal websites, reducing fragmentation. Indeed, each time their data extracted from VAMDC is cited into a publication, they receive automatically credits via the Scholix-underlying mechanism.


Lessons learned on RDA Outputs

We succeeded in implementing the new RDA-data citation paradigms (Data Citation and Scholix) on the VAMDC distributed infrastructure. This removed the technical barriers preventing  automatic data citation and delegation of bibliographic credits for VAMDC extracted data. However, the success of a technical solution does not only depend on its intrinsic qualities, but also on its level of adoption and acceptance by the wider community of final users: we are actually focusing on increasing the impact of the aforementioned citation service through community awareness-raising and training around these new tools.



The adoption story series

The Research Data Alliance (RDA) currently hosts over 60 Interest Groups and more than 30 Working Groups consisting of experts who are working on various topics related to (open) research data and innovation. These working groups produce the RDA outputs: the technical and social infrastructure solutions enabling data sharing, exchange, and interoperability.


For you, to see how to implement the RDA outputs to improve the sharing, exchange and interoperability of your own data. We’ve asked RDA members who have already adopted RDA outputs, to share their experience and lessons learned in a story. Find here a series of RDA adoption stories by individuals, organisations and projects.


Your Organisation: 

This adoption story was brought forward by the RDA Europe 4.0 French National Node.



Stakeholder Classification of your organisation: 
Additional support for this adoption story: 
RDA in France
PDF icon VAMDC_adoption story.pdf348.17 KB