Quality of Research Information in RIS Databases: A Multidimensional Approach

  • Otmane AzeroualEmail author
  • Gunter Saake
  • Mohammad Abuosba
  • Joachim Schöpfel
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)


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.


Research information systems (RIS) Research information Utility System acceptance Data quality dimensions Data quality measurement Data quality improvement Reliability Validity Structural equation modeling 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.German Center for Higher Education Research and Science Studies (DZHW)BerlinGermany
  2. 2.Otto-von-Guericke-University MagdeburgMagdeburgGermany
  3. 3.University of Applied Sciences (HTW) BerlinBerlinGermany
  4. 4.GERiiCO-LaborUniversity of LilleVilleneuve-d’AscqFrance

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