Characterizing Research and Technology Organizations (RTOs) using bibliometrics - The case of the Netherlands
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1 Characterizing Research and Technology Organizations (RTOs) using bibliometrics - The case of the Netherlands EuSPRI 2018, Paris 6-8 June Ed Noyons and Márcia Ferreira CWTS, Leiden University, the Netherlands noyons@cwts.leidenuniv.nl; m.r.ferreira.goncalves@cwts.leidenuniv.nl
2 Outline Background Evaluating RTOs and bibliometrics Research evaluation and science-society connections Case study: the Netherlands Wrap up
3 Background RTOs are valuable and relevant actors in the R&D landscape RTOs are not universities or academic research institutes RTOs often wish to be (and actually are) assessed as academic actors Leiden manifesto on use of evaluation metrics
4 Leiden manifesto for research metrics 10 principles to guide research evaluation Principle 2: Measure performance against the research missions of the institution, group or researcher This principle implicitly refers to evaluation of RTOs and other non (primarily) academic actors
5 Mission RTOs The European Association of Research and Technology Organizations (EARTO), defines RTOs mission as follows: The core mission of Research and Technology Organizations is to harness science and technology in the service of innovation, to improve quality of life and build economic competitiveness (EARTO, 2015).
6 Why is it unsuitable to assess RTOs as if they were universities? Citation based impact is often biased towards the partners they collaborate with; Collaboration of PROs often involves dual affiliations.
7 Scientific performance TNO Period P 5,249 TCS 13,973 MNCS 1.16 PP (top10%) 0.12 PP (collab) 0.90 PP (Intl collab) 0.42
8 Dual affiliations (share of publications) 70% 60% 50% 40% 30% 20% UNIV AMSTERDAM VRIJE UNIV AMSTERDAM DELFT UNIV TECHNOL EINDHOVEN UNIV TECHNOL UNIV TWENTE UNIV GRONINGEN LEIDEN UNIV UNIV MAASTRICHT RADBOUD UNIV NIJMEGEN ERASMUS UNIV ROTTERDAM UNIV TILBURG UNIV UTRECHT WAGENINGEN UNIV NETHERLANDS CANC INST NWO KNAW NL TNO NL NATL INST PUBL HLTH & ENVIRONM NL 10% 0%
9 How to account for a non-academic mission when using bibliometrics?
10 Publication data RTOs Information within References Citations Co-authorships Content Context Addition information Mentions in policy documents Mentions in news Mentions in blogs Mention in social media Citations in Patents
11 Impact assessment of RTOs using bibliometrics and related data Case study of the Netherlands Map of all sciences Distribution of science-society communication signals Overlay by actor-type (university, PRO, RTO) Characterizing actors by dimension
12 Signals between science & society Information within Co-authorship with non-academic authors Sources Additional information on publications (i.e., mentions in) Social media Policy documents News items Patents
13 Signals appear field specific Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
14 Signals appear field specific Industry co-authorship Social Sci & Hum. Color coding indicates the Proportion of papers involving Industry Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
15 Signals appear field specific Cited by patents Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
16 Signals appear field specific Mentions in policy documents Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
17 TNO research profile Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
18 TNO research profile characterized by mentions in policy documents This does NOT reflect the Social Sci & Hum. proportion of TNO publications Maths & CompSci being mentioned Life & Earth Biomedical & Health But rather the policy relatedness of areas in which TNO publishes Physical Sci & Engin.
19 TNO research profile characterized by industry involvement Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
20 RIVM research profile characterized by industry involvement Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
21 RIVM research profile characterized by mentions in policy docs Social Sci & Hum. Maths & CompSci Life & Earth Biomedical & Health Physical Sci & Engin.
22 Dutch R&D organizations characterized by signals (a science-society connectedness profile) wos_name avgppind avgpppatcit avgppnews avgpppol NATL INST PUBL HLTH & ENVIRONM NL NETHERLANDS CANC INST TNO NL WAGENINGEN UNIV UNIV TWENTE EINDHOVEN UNIV TECHNOL DELFT UNIV TECHNOL ERASMUS UNIV ROTTERDAM UNIV MAASTRICHT LEIDEN UNIV UNIV UTRECHT VRIJE UNIV AMSTERDAM UNIV GRONINGEN RADBOUD UNIV NIJMEGEN UNIV AMSTERDAM UNIV TILBURG KNAW NL NWO
23 Conclusions (primarily based on the Dutch case) RTOs can be assessed by bibliometric data, but Scientific performance (based on citations) may be misleading Alternative metrics provides an addition to monitor socio-economic impact Publication-based classification together with signal data provide framework for assessing society connectiveness of research
24 Discussion point Science-society connectedness should not be measured or monitored at the level of actors but on the level of the research area, the community to which an actor belongs
25 Thank you
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