An update from the RDIVA Team at UCA
I thought I’d take a moment to fill you all in on one of the RDIVA work that is feeding in to the collaborative project: A consortial approach to building an integrated RDM system: “small and specialist”. The aim of this project is . The main objectives for us in Phase 1 are:
- To create a case study looking at the implementation of EPrints as a RDM System. This follows up from our previous project KAPTUR
- To create a pilot system that will enable the Recollect plugin to function within a Kultur repository (currently the plugin breaks if tools such as MePrints are installed).
- To run a workshop focused on arts institutions running the Kultur plugin (or other visual plugins) to specify user requirements and ‘hand-pick’ the tools and functionalities that we believe are needed to create the latest version of Kultur (hopefully something like Kultur V2.0 which is standard and can be installed on the latest version of EPrints)
The idea behind the RDIVA partners is to promote the engagement with RDM from the visual research community focusing on visual rather than textual, however we would also like to provide an RDM framework flexible enough to store and publish large and complex data and datasets.There will need to be a distinction between other types of RDM within the partner institutions and their repositories and it is hoped with this project that we will be able to answer the questions about ‘what metadata to capture and what type of files to support’, etc.
Part of the rationale is trying to use existing tools available and developed through similar Jisc funded projects (Recollect, Kultur, Video upload) and make them work together rather than independently, check what the community actually needs in terms of workflow and come up with a framework that not only arts and humanities institutions can use but also any visual related institution who wants/needs to collect visual data.
It will also serve to boost engagement with visual researchers in RDM to collect, publish and preserve complex data and datasets, rather than having these data stored around in memory sticks, dropbox or other non-reliable/non-suitable areas.