As research institutions expand and improve their data management services, so, inevitably, the complexity of their data architectures increase. Getting an institutional data repository to talk to a research management and reporting system may be a challenge, but integrating both with a managed data storage system, a project costing system, HR records, data management planning tools, HPC systems, and the myriad of data generating tools that researchers rely on in their specific disciplines can seem overwhelming.

This session will explore the need for interoperability between institutional systems and services, and the challenges that such interoperability presents. Does it really matter whether data management systems can pass data and metadata between each other? If so, where is this most important? Where are the pain points? How can these best be addressed?

Beginning with a couple of examples from institutions actively wrestling with these questions, this session will provide a forum for people to share their own challenges, experiences, ideas, and suggestions. The emphasis of this meeting will be on establishing and prioritizing shared challenges rather than finding immediate solutions to every issue raised (although we would welcome anyone who has already solved them all!).

Collaborative session notes: https://docs.google.com/document/d/1kpBHO5rZdc5-j-Qjw7HHlRarB2-6NSFZmr70wy9nQJg/edit

10 mins: Introduction to RDARI and scene setting
10 mins: Challenges at UCL designing an interoperable infrastructure (James Wilson)
10 mins: Challenges at the University of Cape Town designing an interoperable infrastructure (Renate Meyer, Kimi Keith)
70 mins: Plenary discussion on drivers and challenges
10 mins: Wrap up and Next steps

Those working at Research institutions involved in designing research data Architectures or elements of these. Or those responsible for connecting the elements of the Data Architectures into a valuable, well-connected whole. This may include senior managers, IT staff, librarians, project managers, research office staff, researchers and data stewards working with cross-disciplinary data, and so forth.