The Front Office–Back Office Model: Supporting Research Data Management in the Netherlands

High quality and timely data management and secure storage of data, both during and after completion of research, are an essential prerequisite for sharing that data. It is therefore crucial that universities and research institutions themselves formulate a clear policy on data management within their organization. For the implementation of this data management policy, high quality support for researchers and an adequate technical infrastructure are indispensable. This practice paper will present an overview of the merging federated data infrastructure in the Netherlands with its front office... Mehr ...

Verfasser: Ingrid Dillo
Peter Doorn
Dokumenttyp: Artikel
Erscheinungsdatum: 2014
Reihe/Periodikum: International Journal of Digital Curation, Vol 9, Iss 2 (2014)
Verlag/Hrsg.: University of Edinburgh
Schlagwörter: Bibliography. Library science. Information resources / Z
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27191319
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doaj.org/article/8293dfd9b68a4377998666554045975b

High quality and timely data management and secure storage of data, both during and after completion of research, are an essential prerequisite for sharing that data. It is therefore crucial that universities and research institutions themselves formulate a clear policy on data management within their organization. For the implementation of this data management policy, high quality support for researchers and an adequate technical infrastructure are indispensable. This practice paper will present an overview of the merging federated data infrastructure in the Netherlands with its front office – back office model, as a use case of an efficient and effective national support infrastructure for researchers. We will elaborate on the stakeholders involved, on the services they offer each other, and on the benefits of this model not only for the front and back offices themselves, but also for the researchers. We will also pay attention to a number of challenges that we are facing, like the implementation of a technical infrastructure for automatic data ingest and integrating access to research data.