Quality Issues of CRIS Data: An Exploratory Investigation with Universities from Twelve Countries

Otmane Azeroual (1) , Joachim Schöpfel (2)

1 DZHW - German Center for Higher Education Research and Science Studies
2 GERIICO - Groupe d'Études et de Recherche Interdisciplinaire en Information et COmmunication - ULR 4073

Collecting, integrating, storing and analyzing data in a database system is nothing new in itself. To introduce a current research information system (CRIS) means that scientific institutions must provide the required information on their research activities and research results at a high quality. A one-time cleanup is not sufficient; data must be continuously curated and maintained. Some data errors (such as missing values, spelling errors, inaccurate data, incorrect formatting, inconsistencies, etc.) can be traced across different data sources and are difficult to find. Small mistakes can make data unusable, and corrupted data can have serious consequences. The sooner quality issues are identified and remedied, the better. For this reason, new techniques and methods of data cleansing and data monitoring are required to ensure data quality and its measurability in the long term. This paper examines data quality issues in current research information systems and introduces new techniques and methods of data cleansing and data monitoring with which organizations can guarantee the quality of their data.

Mots clés: Current research information systems CRIS; Data quality; Research information management; Data cleansing; Data monitoring

Domaines: Sciences de l'information et de la communication; Informatique [cs]; Base de données [cs.DB]

Otmane Azeroual, Joachim Schöpfel. Quality Issues of CRIS Data: An Exploratory Investigation with Universities from Twelve Countries. Publications, 2019, 7 (1), pp.14. ⟨10.3390/publications7010014⟩. ⟨hal-02045885⟩