Data Description Registry Interoperability WG

Group Co-Chairs: Amir Aryani, Australian National Data Service Adrian Burton, Australian National Data Service

Recommendation Title: Data Description Registry Interoperability Model

Authors: Amir Aryani

Impact: Provides researchers a mechanism to connect datasets in various data repositories based on various models such as co-authorship, joint funding, grants, etc.

Recommendation package: https://dx.doi.org/10.15497/RDA00003

Citation: Amir Aryani (2015): Data Description Registry Interoperability WG: Interlinking Method and Specification of Cross – Platform Discovery. DOI: 10.15497/RDA00003

Data Description Registry Interoperability WG is working on a series of bi-lateral information exchange projects and an open, extensible, and flexible cross-platform research data discovery software solutions. Research Data Switchboard is a collaborative project by the members of the DDRI WG. This project leverages DataCite DOI, ORCID and other persistent identifiers, and uses simple but effective research graph technology to link datasets. This system currently links datasets across the following platforms: Dryad, INSPIREHEP (at CERN), ORCID, Figshare and link Australian research datasets through Research Data Australia – supported by ANDS.

This document describes the outcome of the Data Description Registry Interoperability (DDRI) working group and specification of the interoperability model implemented by the partners in this group. In addition, this document shows the testing of this model through an implementation called Research Data Switchboard, a collaborative project by the participants in this working group. The intended audience is the Research Data Alliance community.

Further information

Publications:

• Amir Aryani, Marta Poblet, Kathryn Unsworth, Jingbo Wang, Ben Evans, Anusuriya Devaraju, Brigitte Hausstein, Claus-Peter Klas, Benjamin Zapilko and Samuele Kaplun: A Research Graph dataset for connecting research data repositories using RD-Switchboard. Scientific Data volume 5, Article number: 180099 (2018). doi:10.1038/sdata.2018.99

Webinars: