Data Integration for Research and Innovation Policy: An Ontology-based Data Management Approach

Cinzia Daraio (), Maurizio Lenzerini (), Claudio Leporelli (), Henk F. Moed (), Paolo Naggar (), Andrea Bonaccorsi () and Alessandro Bartolucci ()
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Cinzia Daraio: Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG), University of Rome La Sapienza, Rome, Italy
Maurizio Lenzerini: Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG), University of Rome La Sapienza, Rome, Italy
Claudio Leporelli: Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG), University of Rome La Sapienza, Rome, Italy
Henk F. Moed: Department of Computer, Control and Management Engineering Antonio Ruberti (DIAG), University of Rome La Sapienza, Rome, Italy
Paolo Naggar: Studiare Ltd., Rome, Italy
Andrea Bonaccorsi: DISTEC, University of Pisa, Italy
Alessandro Bartolucci: Studiare Ltd., Rome, Italy

No 2015-10, DIAG Technical Reports from Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"

Abstract: The main objective of this paper is to propose 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 we propose 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. Our approach, implemented in the Sapientia ontology (Sapientia: the Ontology of Multi- Dimensional Research Assessment) offers a transparent platform on which to base the evaluation process; permits to define and specify in an unambiguous way the indicators on which the evaluation is based on; allows us to track their evolution over time; makes it possible the analysis of the feedbacks of the indicators on the behavior of scholars and allows us to find out opportunistic behaviors; provides a monitoring system to track over time the changes in the established evaluation criteria and their consequences on the research system. We claim that an higher availability and a more transparent view on the scholarly outcomes may improve the understanding of basic science from the broad society and can improve the communication of the research outcome to the public opinion, which, in the present economic phase, has an increasingly money-for-value approach about the funding of science.A lot of work on these issues has still to be carried out. Nevertheless we believe that a new line of research based on an OBDM approach could successfully contribute to solve some of the key issues in the integration of heterogeneous data for STI policies.

Keywords: research assessment; science of science policy; data integration; ontology-based data management (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-ino and nep-knm
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