EconPapers    
Economics at your fingertips  
 

Data measurement in research information systems: metrics for the evaluation of data quality

Otmane Azeroual (), Gunter Saake () and Jürgen Wastl ()
Additional contact information
Otmane Azeroual: German Center for Higher Education Research and Science Studies (DZHW)
Gunter Saake: Otto-von-Guericke-University Magdeburg
Jürgen Wastl: University of Cambridge

Scientometrics, 2018, vol. 115, issue 3, No 8, 1290 pages

Abstract: Abstract In recent years, research information systems (RIS) have become an integral part of the university’s IT landscape. At the same time, many universities and research institutions are still working on the implementation of such information systems. Research information systems support institutions in the measurement, documentation, evaluation and communication of research activities. Implementing such integrative systems requires that institutions assure the quality of the information on research activities entered into them. Since many information and data sources are interwoven, these different data sources can have a negative impact on data quality in different research information systems. Because the topic is currently of interest to many institutions, the aim of the present paper is firstly to consider how data quality can be investigated in the context of RIS, and then to explain how various dimensions of data quality described in the literature can be measured in research information systems. Finally, a framework as a process flow according to UML activity diagram notation is developed for monitoring and improvement of the quality of these data; this framework can be implemented by technical personnel in universities and research institutions.

Keywords: Current research information systems (CRIS); Research information systems (RIS); Research information; Data quality; Data quality dimensions; Data measurement; Data monitoring; Science system; Standardization (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-018-2735-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:115:y:2018:i:3:d:10.1007_s11192-018-2735-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-018-2735-5

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:scient:v:115:y:2018:i:3:d:10.1007_s11192-018-2735-5