Abstract This paper proposes an Ontology-Based Data Management (OBDM) approach to coordinate, integrate and maintain the data needed for Science, Technology and Innovation (STI) policy development. The OBDM approach is a form of integration of information in which the global schema of data is substituted by the conceptual model of the domain, formally specified through an ontology. Implemented in Sapientia, the ontology of multidimensional research assessment, it offers a transparent platform as the base for the assessment process; it enables one to define and specify in an unambiguous way the indicators on which the evaluation is based, and to track their evolution over time; also it allows to the analysis of the effects of the actual use of the indicators on the behavior of scholars, and spot opportunistic behaviors; and it provides a monitoring system to track over time the changes in This work is based on two papers accepted for presentation and published in the proceedings of the ISSI 2015 Conference (see Daraio et al. 2015b, c (2016( ) 106:857-871 DOI 10.1007( /s11192-015-1814 the established evaluation criteria and their consequences for the research system. It is argued that easier access to and a more transparent view of scientific-scholarly outcomes help to improve the understanding of basic science and the communication of research outcomes to the wider public. An OBDM approach could successfully contribute to solve some of the key issues in the integration of heterogeneous data for STI policies.
Turko et al., [15] REF proposed a method for data management which is based on ontology to identify, maintain and integrate the data required for STI policy making.
Data integration for research and innovation policy: an Ontology-Based Data Management approach
Scientometrics
Scientometrics
Engineering Computer Science