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The Added Value of the European Map of Excellence and Specialization (EMES) for R&I Policy Making

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The Added Value of the European Map of Excellence and Specialization (EMES) for R&I Policy Making Cinzia Daraio July – 2015 EUR 27389 EN EUROPEAN COMMISSION Directorate-General for Research and Innovation Directorate A – Policy Development and coordination Unit A6 – Science Policy, foresight and data Contact: Emanuele Barbarossa, Katarzyna Bitka E-mail: [email protected] [email protected] [email protected] [email protected] European Commission B-1049 Brussels EUROPEAN COMMISSION The Added Value of the European Map of Excellence and Specialization (EMES) for R&I Policy Making Cinzia Daraio The document is based on projects carried out by the ONTORES research group at Sapienza University of Rome and on the Smart.CI.EU (Sapienza microdata architecture for education, research and technology studies. A Competence-based data Infrastructure on European Universities). The contributions of Marco Angelini, Alessandro Daraio, Flavia di Costa, Maurizio Lenzerini, Claudio Leporelli, Henk F. Moed, Gabriele Petrotta, and Giuseppe Santucci are gratefully acknowledged. Directorate-General for Research and Innovation 2015 Research, Innovation, and Science Policy Experts High Level Group EUR 27389 EN EUROPE DIRECT is a service to help you find answers to your questions about the European Union Freephone number (*): 00 800 6 7 8 9 10 11 (*) The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you) LEGAL NOTICE This document has been prepared for the European Commission however it reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. More information on the European Union is available on the internet (http://europa.eu). Luxembourg: Publications Office of the European Union, 2015. ISBN 978-92-79-50354-2 doi 10.2777/553985 ISSN 1831-9424 © European Union, 2015. Reproduction is authorised provided the source is acknowledged. Table of contents EXECUTIVE SUMMARY .................................................................................................... 5 RÉSUMÉ ....................................................................................................................... 9 TABLE OF CONTENTS ..................................................................................................... 3 1. INTRODUCTION AND CONTENT OF THE STUDY ........................................................... 12 Introduction ........................................................................................................ 12 Content of the study ............................................................................................ 12 2. POLICY RELEVANCE OF AN EMES FOR R&I POLICY MAKING .......................................... 14 3. DEFINING CRITERIA FOR EMES ................................................................................. 17 4. GEO-REFERENCING INFORMATION ON EUROPEAN UNIVERSITIES ................................. 17 Drawbacks and limitations: multi-site institutions .................................................... 19 5. INTEGRATING BIBLIOMETRIC DATA AT THE LEVEL OF INDIVIDUAL UNIVERSITIES .......... 19 State of the art .................................................................................................... 19 Scimago Institutions Rankings ...................................................................... 20 Global Research Benchmarking System ......................................................... 20 Leiden Ranking ........................................................................................... 21 Altmetrics, webometrics and other complementary information ........................ 22 Coverage of the European university landscape .............................................. 24 6. LOCATING PUBLICATIONS OF UNIVERSITIES AND PROS ON A GEOGRAPHIC MAP ........... 25 Towards an authority file for PROs ......................................................................... 26 Breakdown by discipline........................................................................................ 26 7. TOWARDS A EUROPEAN MAP OF EXCELLENCE AND SPECIALIZATION............................. 28 Geo-referencing data on publications...................................................................... 28 Integrating information from other projects: the case of U-Multirank .......................... 31 Integrating other socio-economic indicators ............................................................ 32 Feasibility of selected indicators ............................................................................. 34 8. CONCORDANCE TABLES OF DIFFERENT SUBJECT CLASSIFICATION SYSTEMS ................. 40 Introduction ........................................................................................................ 40 Results from a survey ........................................................................................... 41 Approaches and systems developed in the past. Correspondence tables between Intellectual Patent Classification (IPC) and Fields of Science (FoS); and between IPC and industrial classification..................................................................... 43 Correspondence tables between Fields of Education (FoE) and Fields of Science (FoS) .. 43 Correspondence tables from the Eumida project ............................................. 43 Correspondence tables from the ETER Project ................................................ 45 Conclusions and recommendations ......................................................................... 47 9. VISUAL ANALYTICS FOR A PILOT EMES ...................................................................... 47 General Design .................................................................................................... 48 Proof-of-concept prototypal application ................................................................... 51 10. ASSESSMENT ........................................................................................................ 55 11. EXPLORATION OF POSSIBLE BUSINESS MODELS AND BUDGET ................................... 56 1. Model Supported by the European Commission .................................................... 56 2. Public-private sponsorship Model........................................................................ 57 3. Science 2.0 Model ............................................................................................ 57 Linking data in an open platform ............................................................................ 57 Automation and maintenance of the infrastructural data system ................................ 58 A real options approach to estimate the investment in an OBDM approach .................. 60 An estimate of the needed budget.......................................................................... 61 3 12. RECOMMENDATIONS .............................................................................................. 62 REFERENCES .............................................................................................................. 65 APPENDICES ............................................................................................................... 68 Appendix 1: Authority file of European universities ................................................... 68 Appendix 2: Concordance tables .......................................................................... 101 Appendix 3: Possible User Groups ........................................................................ 107 4 EXECUTIVE SUMMARY This study examines the feasibility of constructing a European Map of Excellence and Specialization (EMES) by offering a proof of the concept and illustrating the potential for policy making. The term 'Map of Excellence and Specialization' refers to a geographical information system (GIS) that combines and georeferences information from various sources at different geographic scales (Nomenclature of Units for Territorial Statistics (NUTS) levels 2 and possibly 3) and provides indicators intended for policy use. Drawing a Map of Excellence and Specialization entails many challenges: Actors in the European Science and Technology (S&T) field are heterogeneous (for example, universities and Public Research Organisations (PROs)), their output is composite (for example, education, publications, and patents), the location of their activities is not fully disclosed, etc. A number of S&T policy decisions depend on assumptions about the impact of public expenditure on national, regional or local variables such as employment, productivity, and growth. These assumptions are rarely based on sound empirical evidence, however. Furthermore, they tend to ignore the magnitude of knowledge spillovers and tend to assume a simplistic view of agglomeration. What is needed is a robust empirical base at geographic level in which data on knowledge production are firmly established. Such a base would then offer the opportunity to integrate other data using the same unit of reference at geographic level. The current study explores also the policy implications of using such a Map of Excellence and Specialization. The main criteria to assess the successful implementation of the EMES have been identified in: Availability of data on publications (adequate economic and legal framework for the use of commercial data on publications including sources, commercial conditions and update for
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