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

Otmane Azeroual and Joachim Schöpfel
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Otmane Azeroual: German Center for Higher Education Research and Science Studies (DZHW), 10117 Berlin, Germany
Joachim Schöpfel: GERiiCO Laboratory, University of Lille, 59653 Villeneuve-d’Ascq, France

Publications, 2019, vol. 7, issue 1, 1-18

Abstract: 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.

Keywords: current research information systems (CRIS); research information systems (RIS); research information management systems (RIMS); research information; data quality issues; data quality perception; quality management task; quality enhancement methods (search for similar items in EconPapers)
JEL-codes: A2 D83 L82 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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