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|Title:||Support structures to facilitate the dissemination and implementation of a national standard for research information – the German case of the Research Core Dataset||Authors:||Biesenbender, Sophie
|Keywords:||research information management;national coordination;Core Data Set (CDS);higher education institutions;research evaluation||Issue Date:||14-Jun-2018||Publisher:||euroCRIS||Source:||"FAIRness of Research Information": Proceedings of the 14th International Conference on Current Research Information Systems (CRIS2018)
Procedia Computer Science 146: 131-141 (2019)
|Series/Report no.:||CRIS2018: 14th International Conference on Current Research Information Systems (Umeå, June 13-16, 2018)||Conference:||CRIS2018 – Umeå||Abstract:||
The German science and higher education system is characterized by federalism, multi-level governance and interwoven regulatory competences of different levels of government. Establishing binding standards and harmonized policies for German higher education institutions (HEIs) and non-university research institutions is a complex task that requires concerted action and co-operation between the federal and state governments. In this context, the German science council (short for German Council of Science and Humanities) – an advisory body for the German federal and state governments – develops and publishes recommendations on how to advance the German science system and to deal with current challenges and policy needs.
One aspect of system-wide political relevance concerns the regulation and use of research information (RI) for different purposes (e.g. for informed decision-making or evaluation). RI comprises information to describe research processes and output, such as data on research staff, projects, publications, patents etc. Until 2016 there were not any nationwide regulations or standards for RI. The gathering and processing of these data in the German science system are often ad-hoc (related to a special occasion), context-specific, non-reproducible and not comparable over different research institutions or types of research institutions (HEIs or non-university research institutions). Research institutions collect and process these data for different external and internal recipients, such as e.g. statistical offices, funding organizations, accreditation agencies or institutional boards and committees, and purposes, such as e.g. reporting (e.g. periodical reports, controlling, internal evaluations) or public relations and outreach (institutional websites, rankings etc.).
Presentation delivered at the CRIS2018 Conference Umeå within parallel session 4 "Research Information Management"
Contains extended abstract accepted at the conference and presentation (12 slides) delivered at the event
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|Biesenbender_Herwig_CRIS2018_paper_Research_Core_Dataset.pdf||Extended abstract (PDF)||487.95 kB||Adobe PDF||View/Open|
|20180606_CRIS2018_Biesenbender_Herwig_v02_print.pdf||PDF presentation||824.55 kB||Adobe PDF||View/Open|
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