Quality of Research Information in RIS Databases: A Multidimensional Approach

Abstract : For the permanent establishment and use of a RIS in universities and academic institutions, it is absolutely necessary to ensure the quality of the research information, so that the stakeholders of the science system can make an adequate and reliable basis for decision-making. However, to assess and improve data quality in RIS, it must be possible to measure them and effectively distinguish between valid and invalid research information. Because research information is very diverse and occurs in a variety of formats and contexts, it is often difficult to define what data quality is. In the context of this present paper, the data quality of RIS or rather their influence on user acceptance will be examined as well as objective quality dimensions (correctness, completeness, consistency and timeliness) to identify possible data quality deficits in RIS. Based on a quantitative survey of RIS users, a reliable and valid framework for the four relevant quality dimensions will be developed in the context of RIS to allow for the enhancement of research information driven decision support.
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Otmane Azeroual, Gunter Saake, Mohammad Abuosba, Joachim Schöpfel. Quality of Research Information in RIS Databases: A Multidimensional Approach. Business Information Systems, pp.337-349, 2019, 22nd International Conference, BIS 2019, Seville, Spain, June 26–28, 2019, Proceedings, Part I, ⟨10.1007/978-3-030-20485-3_26⟩. ⟨hal-02163029⟩



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