Data and classification governance, key to semantic interoperability of CRIS systems in inter-organizational contexts

Abstract

Research information systems are often described as important tools to enhance open innovation, by directly gathering and unlocking information on scientific and technological research to stakeholders. Current Research Information Systems (CRIS) are mostly developed within a single organization with a context-specific vocabulary and generally use the Common European Research Information Format (CERIF) for data storage. Although CERIF allows for almost unlimited possibilities to model research information, it has - like any standard - limitations when it comes down to communication to end-users in terms of semantics. However, if one wants to exchange the information kept within CRIS systems, it is essential to include research information and classification governance as this is key to truly comparable and thus meaningful information. In this paper, we elaborate on research information and classification governance as a prerequisite for establishing true semantic interoperability of CRIS systems in inter-organizational contexts.