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Influence of Information Quality via Implemented German RCD Standard in Research Information Systems

Author

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  • Otmane Azeroual

    (German Center for Higher Education Research and Science Studies (DZHW), 10117 Berlin, Germany)

  • Joachim Schöpfel

    (GERiiCO-Labor, University of Lille, 59650 Villeneuve-d’Ascq, France)

  • Dragan Ivanovic

    (University of Novi Sad, Novi Sad 21000, Serbia)

Abstract

With the steady increase in the number of data sources to be stored and processed by higher education and research institutions, it has become necessary to develop Research Information Systems, which will store this research information in the long term and make it accessible for further use, such as reporting and evaluation processes, institutional decision making and the presentation of research performance. In order to retain control while integrating research information from heterogeneous internal and external data sources and disparate interfaces into RIS and to maximize the benefits of the research information, ensuring data quality in RIS is critical. To facilitate a common understanding of the research information collected and to harmonize data collection processes, various standardization initiatives have emerged in recent decades. These standards support the use of research information in RIS and enable compatibility and interoperability between different information systems. This paper examines the process of securing data quality in RIS and the impact of research information standards on data quality in RIS. We focus on the recently developed German Research Core Dataset standard as a case of application.

Suggested Citation

  • Otmane Azeroual & Joachim Schöpfel & Dragan Ivanovic, 2020. "Influence of Information Quality via Implemented German RCD Standard in Research Information Systems," Data, MDPI, vol. 5(2), pages 1-10, March.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:2:p:30-:d:337825
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    References listed on IDEAS

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    1. Sophie Biesenbender & Stefan Hornbostel, 2016. "The Research Core Dataset for the German science system: challenges, processes and principles of a contested standardization project," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 837-847, February.
    2. Azeroual, Otmane & Saake, Gunter & Schallehn, Eike, 2018. "Analyzing data quality issues in research information systems via data profiling," International Journal of Information Management, Elsevier, vol. 41(C), pages 50-56.
    3. Otmane Azeroual & Gunter Saake & Jürgen Wastl, 2018. "Data measurement in research information systems: metrics for the evaluation of data quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1271-1290, June.
    4. Otmane Azeroual & Joachim Schöpfel, 2019. "Quality Issues of CRIS Data: An Exploratory Investigation with Universities from Twelve Countries," Publications, MDPI, vol. 7(1), pages 1-18, February.
    5. Dragan Ivanović & Dušan Surla & Miloš Racković, 2011. "A CERIF data model extension for evaluation and quantitative expression of scientific research results," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(1), pages 155-172, January.
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