Abstract
With the steady increase in the number of data sources to be stored and processed by higher education and research institutions, it has become necessary to develop Research Information Systems, which will store this research information in the long term and make it accessible for further use, such as reporting and evaluation processes, institutional decision making and the presentation of research performance. In order to retain control while integrating research information from heterogeneous internal and external data sources and disparate interfaces into RIS and to maximize the benefits of the research information, ensuring data quality in RIS is critical. To facilitate a common understanding of the research information collected and to harmonize data collection processes, various standardization initiatives have emerged in recent decades. These standards support the use of research information in RIS and enable compatibility and interoperability between different information systems. This paper examines the process of securing data quality in RIS and the impact of research information standards on data quality in RIS. We focus on the recently developed German Research Core Dataset standard as a case of application.
Highlights
The collection and exchange of research information are integral parts and success factors in the research information management process
Research information systems provide information about research activities and their results. This information is essential for insight knowledge of research activities, for the evaluation of research performance and for well informed decision making
The workflow presented in our paper offers institutions the opportunity to assess and improve the quality of research information prior to integration in Research InformationSystems (RIS)
Summary
The collection and exchange of research information (e.g., information about research staff, organizations, publications, project funding, patents, partners, etc.) are integral parts and success factors in the research information management process. The CERIF Data Model is an international standard for the management and exchange of research information and describes relevant object types from all areas of research and development [3]. A new standard for German research information management has a direct and immediate impact on RIS in other, international, European or foreign research institutions and networks. The two following sections three and four deal with data quality issues related to RIS implementation and provide a general concept for RIS data quality managing, together with a workflow Based on these elements, section five explores the potential usefulness of the RCD standard for the management of RIS data quality. The conclusion summarizes our findings and provides some perspectives for further investigation
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