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Sharing research data needs to go beyond the simple publication of a research paper. For this reason, allowing the sharing of full data and metadata compliant with the FAIR requirements is an essential cornerstone of data stewardship. This is possible thanks to the Materials Cloud Archive, an online repository for computational materials science registered on FAIRsharing.org, re3data, recommended by Nature’s journal Scientific Data, and indexed by Google Dataset Search and the EUDAT/EOSC service B2FIND.
The Materials Cloud Archive is open to the world and guarantees long-term storage (see the policies).
We provide tools to researchers to facilitate sharing of FAIR-compliant data and, thus, be automatically compliant with data management plans required by, e.g., EU in H2020 projects (see data management plan templates).
Findability is achieved by releasing DOIs for research data published on the Materials Cloud Archive. We are also extending the Materials Cloud Archive to scale to tens of thousands of entries and more.
For what concerns the other FAIR pillars, the integration of all flagship codes with AiiDA enables us to go significantly beyond current standards in terms of interoperability, reusability and completeness by storing not only the results of calculations, but automatically recording their full provenance with rich metadata in a standardized format (Figure 1). Indeed, the AiiDA automatic tracking of provenance guarantees the reproducibility of computational research, and makes the research data reusable and interoperable with the other codes.
Accessibility is provided by the Materials Cloud Discover and Explore sections, displaying respectively curated sets of scientific results and the corresponding AiiDA databases, allowing to browse with ease the provenance of the data with interactive and custom visualizations.
Fig. 1: an example of a provenance graph created by AiiDA.