The Research Core Dataset for the German science system: developing standards for an integrated management of research information

Scientometrics

Volumn 108, Issue 1, 2016, Pages 401-412

  Biesenbender, Sophie ^a   Hornbostel, Stefan ^a  

^a Abteilung Infrastruktur und Methoden Forschungsdatenzentrum   (Germany)

Author keywords

Comparability; Data integration; Data quality; Standardization

Indexed keywords

EID: 84961126537     PISSN: 01389130     EISSN: 15882861     Source Type: Journal    
DOI: 10.1007/s11192-016-1909-2     Document Type: Article

References (13)

1. Biesenbender, S., & Hornbostel, S. (2016). The Research Core Dataset for the German science system: Challenges, processes and principles of a contested standardization project. Scientometrics, 106(2), 837–847. doi:10.1007/s11192-015-1816-y.
2. Bittner, S., Hornbostel, S., & Scholze, F. (eds.). (2012). Forschungsinformation in Deutschland: Anforderungen, Stand und Nutzen existierender Forschungsinformationssysteme. Workshop Forschungsinformationssysteme 2011. iFQ-Working Paper, No. 10.
3. Breitbach, M. (2009). Empfehlungen zur Gestaltung von Steuerungssystemen auf der Ebene Land/Hochschule. Arbeitskreis der deutschen Universitätskanzler(innen): Leistungsorientierte Mittelverteilung und Zielvereinbarungen. http://www.uni-kanzler.de/fileadmin/Dateien/UAK1_Publikation-1(1).pdf.
4. DINI AG Research Information Systems. (2015). Research information systems at universities and research institutions—Position paper. Zenodo. doi:10.5281/zenodo.17491.
5. German Council of Science and Humanities. (2013). Empfehlungen zu einem Kerndatensatz Forschung (Drs. 2855-13), Berlin, Germany. http://www.wissenschaftsrat.de/download/archiv/2855-13.pdf.
6. German Council of Science and Humanities. (2016), Empfehlungen zur Spezifikation des Kerndatensatz Forschung (Drs. 5066-16), Berlin, Germany. http://www.wissenschaftsrat.de/download/archiv/5066-16.pdf.
7. Glänzel, W. (2015). The Challenge of Data Collection, Harmonisation and Standardisation for Use in Research Funding, Output Measurement and Research Assessment. Paper presented at the special session on “New frontiers and empirical evidence on the Efficiency, Effectiveness and Impact of Education, Research and Innovation” organised by C. Daraio at the 15th International Conference on Scientometrics and Informetrics (ISSI 2015), Boğaziçi University, Istanbul, Turkey.
8. Glänzel, W., Beck, R., Milzow, K., Slipersæter, S., Tóth, G., Kołodziejski, M., et al. (2015). Data collection and use in research funding and performing organisations. General outlines and first results of a project launched by Science Europe. Scientometrics, 106(2), 825–835. doi:10.1007/s11192-015-1815-z.
9. Nickel, S., Duong, S., & Ulrich, S. (2013). Informationsstrukturen zur Beurteilung von Leistungen in Forschung, Lehre und Studium: Akteure und Datenangebote in Deutschland. Gütersloh: CHE Gemeinnütziges Centrum für Hochschulentwicklung. ISBN 978-3-941927-45-2.
10. OECD. (2002). Proposed standard practice for surveys of research and experimental development—Frascati manual. Paris: OECD. doi:10.1787/9789264199040-en.
11. Quix, C., & Jarke, M. (2014). Information integration in research information systems. Procedia Computer Science, 33(2014), 18–24.
12. Riechert, M., Biesenbender, S., Dees, W., & Sirtes, D. (2016). Developing Definitions of Research Information Metadata as a Wicked Problem? Characterisation and Solution by Argumentation Visualisation. Program (forthcoming).
13. Wilsdon, J., et al. (2015). The metric tide: Report of the independent review of the role of metrics in research assessment and management. HEFCE. doi:10.13140/RG.2.1.4929.1363.