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“Why do we need to model
the science system?”
Talk at the seminar of the Eindhoven Centre for Innovation
Sciences, June 2, 2016
Andrea Scharnhorst, Royal Netherlands Academy of Arts and Sciences, DANS
Story line
• How got I roped into this?
• What kind of models do we hunt for?
• There is no one model of science – but there is also not really an overview
about them or a tool box
• Why do we need them?
• Do we have enough good data for predictive models of science dynamic?
• Modeling and measuring of science – living apart together
• Barriers and actions
• If only I had ….
A Map of Science and a journey
System-Umwelt-Grenze
Teilsystem 1 Teilsystem i
Teilsystem j
0
Di
0
Di
1
Ai
0
Aij
0, Mij
Aij
1
x1 xi
xj
Ai
1
CijBij
Physics
Economics
DataScience
Education
Scientific
schools
Retirement
Fieldmobility
Ebeling, W., Scharnhorst, A. (1986) Selforganization Models for Field Mobility of Physicists. Czechoslovak Journal of Physics B36 , pp. 43-46.
Bruckner, E., Ebeling, W., Scharnhorst, A. (1990) The Application of Evolution Models in Scientometrics. Scientometrics 18 (1-2), pp. 21-41
Darwinian selection among scientific fields
One model, two models, many models …
Elementary unit: researcher, group, invisible college, papers,
journals, institutions,
Phenomenon: growth of scientific fields, the journal market,
the flows of citations, the structure of collaborative networks,
the boundary conditions for a successful individual career, ….
Proposed funding systemIllustrations of the existing (left) and the proposed (right) funding
systems, with reviewers in blue and investigators in red.
Johan Bollen et al. EMBO Rep. doi:10.1002/embr.201338068
©2014 by European Molecular Biology Organization
Reasonswhyweneedmodels
Proposalcrisis
List of full professors in the Netherlands with an expertise tag (D category) which is seldom
!
Rare expertise types among the full professors
In The Netherlands
BUT: we tag the person
expertise build a hierarchical system
…..
Reasonswhyweneedmodels
Thefunctionofsmallfields
Communication
Text Actors
words journals references authors institutions countries…
Co-word maps
Semantic maps
(Callon, Rip,
White)
Citation environments
of journals
(Leydesdorff)
Maps of science
(Boyack, Börner, Klavans;
Leydesdorff, Rafols)
Bibliographic coupling
Citation networks
Co-citation networks
(Marshokova, Small/Griffith)
Productivity
(Lotka)
Coauthorship
(…..)
Disciplinary profiles
Performance
Impact
(…..)
International
collaboration
(…..)
What is a topic?
What is a paradigm?
What are fields and
disciplines?
What are the hot areas and
research fronts?
What are the knowledge flows?
Core and periphery
of knowledge exchange in
a globalized economy
Biographies, key player,
Individual vs group dynamics
Key players, evaluation
Meaning of a citation, deeper understanding of knwoledge flows
Sentiment of citations Small, Thelwall, Boyack…
Theapplicationofamodel
isonlyasgoodas…
Measuring and modelling the sciences
Stochastic processes
& indicators
Science maps, network analytics
& epidemic processes
Hirsh index
Lucio-Arias, D., & Scharnhorst, A. (2012). Mathematical Approaches to Modeling Science from an
Algorithmic-Historiography Perspective. In A. Scharnhorst, K. Börner, & P. van den Besselaar (Eds.),
Models of Science Dynamics (pp. 23–66). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-23068-4_2
Barriers
Vision
Evidence based policy advice
Science
model
laboratory
Science
observatory
Science in
society
interface
On the way…
• Workshops to raise awareness
• Special issues, books, review articles
• Data mining and data visualisation
• Interaction with stakeholders in science policy
Informa on Professionals/
Informa on Scien sts
Social Scien sts
Computer Scien sts
Physics/Mathema cs
Digital Humani es
Information professionals
• Collections, Information retrieval
• WG 1 Phenomenology of knowledge
spaces
• WG 4 Data curation & navigation
Social scientists
• Simulating user behavior
• WG 2 Theory of knowledge
spaces
• WG 4 Data curation &
navigation
Computer scientists
• Semantic web, data models
• WG 1 Phenomenology of Knowledge Spaces
• WG 4 Data curation &navigation
Physicists, mathematicians
Digital humanities scholars
• Collections, interactive design
• WG 3 Visual analytics – knowledge maps
• WG 4 Data curation & navigation
Participating communities
• Structure & evolution of
complex knowledge
spaces, big data mining
• WG 2 Theory of
knowledge spaces
• WG 3 Visual analytics –
knowledge maps
www.knowescape.org
Digital Humanities as transient innovation
With Sally Wyatt, June 2015
dans.knaw.nl
DANS is an institute of KNAW en NWO
Thanks for your attention!
Andrea.scharnhorst@dans.knaw.nl
Twitter: @knowescape; Mendeley

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Why do we need to model the science system?

  • 1. “Why do we need to model the science system?” Talk at the seminar of the Eindhoven Centre for Innovation Sciences, June 2, 2016 Andrea Scharnhorst, Royal Netherlands Academy of Arts and Sciences, DANS
  • 2. Story line • How got I roped into this? • What kind of models do we hunt for? • There is no one model of science – but there is also not really an overview about them or a tool box • Why do we need them? • Do we have enough good data for predictive models of science dynamic? • Modeling and measuring of science – living apart together • Barriers and actions • If only I had ….
  • 3. A Map of Science and a journey
  • 4.
  • 5. System-Umwelt-Grenze Teilsystem 1 Teilsystem i Teilsystem j 0 Di 0 Di 1 Ai 0 Aij 0, Mij Aij 1 x1 xi xj Ai 1 CijBij Physics Economics DataScience Education Scientific schools Retirement Fieldmobility Ebeling, W., Scharnhorst, A. (1986) Selforganization Models for Field Mobility of Physicists. Czechoslovak Journal of Physics B36 , pp. 43-46. Bruckner, E., Ebeling, W., Scharnhorst, A. (1990) The Application of Evolution Models in Scientometrics. Scientometrics 18 (1-2), pp. 21-41 Darwinian selection among scientific fields
  • 6. One model, two models, many models … Elementary unit: researcher, group, invisible college, papers, journals, institutions, Phenomenon: growth of scientific fields, the journal market, the flows of citations, the structure of collaborative networks, the boundary conditions for a successful individual career, ….
  • 7. Proposed funding systemIllustrations of the existing (left) and the proposed (right) funding systems, with reviewers in blue and investigators in red. Johan Bollen et al. EMBO Rep. doi:10.1002/embr.201338068 ©2014 by European Molecular Biology Organization Reasonswhyweneedmodels Proposalcrisis
  • 8. List of full professors in the Netherlands with an expertise tag (D category) which is seldom ! Rare expertise types among the full professors In The Netherlands BUT: we tag the person expertise build a hierarchical system ….. Reasonswhyweneedmodels Thefunctionofsmallfields
  • 9. Communication Text Actors words journals references authors institutions countries… Co-word maps Semantic maps (Callon, Rip, White) Citation environments of journals (Leydesdorff) Maps of science (Boyack, Börner, Klavans; Leydesdorff, Rafols) Bibliographic coupling Citation networks Co-citation networks (Marshokova, Small/Griffith) Productivity (Lotka) Coauthorship (…..) Disciplinary profiles Performance Impact (…..) International collaboration (…..) What is a topic? What is a paradigm? What are fields and disciplines? What are the hot areas and research fronts? What are the knowledge flows? Core and periphery of knowledge exchange in a globalized economy Biographies, key player, Individual vs group dynamics Key players, evaluation Meaning of a citation, deeper understanding of knwoledge flows Sentiment of citations Small, Thelwall, Boyack… Theapplicationofamodel isonlyasgoodas…
  • 10. Measuring and modelling the sciences Stochastic processes & indicators Science maps, network analytics & epidemic processes Hirsh index Lucio-Arias, D., & Scharnhorst, A. (2012). Mathematical Approaches to Modeling Science from an Algorithmic-Historiography Perspective. In A. Scharnhorst, K. Börner, & P. van den Besselaar (Eds.), Models of Science Dynamics (pp. 23–66). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-23068-4_2
  • 12. Vision Evidence based policy advice Science model laboratory Science observatory Science in society interface
  • 13. On the way… • Workshops to raise awareness • Special issues, books, review articles • Data mining and data visualisation • Interaction with stakeholders in science policy
  • 14. Informa on Professionals/ Informa on Scien sts Social Scien sts Computer Scien sts Physics/Mathema cs Digital Humani es Information professionals • Collections, Information retrieval • WG 1 Phenomenology of knowledge spaces • WG 4 Data curation & navigation Social scientists • Simulating user behavior • WG 2 Theory of knowledge spaces • WG 4 Data curation & navigation Computer scientists • Semantic web, data models • WG 1 Phenomenology of Knowledge Spaces • WG 4 Data curation &navigation Physicists, mathematicians Digital humanities scholars • Collections, interactive design • WG 3 Visual analytics – knowledge maps • WG 4 Data curation & navigation Participating communities • Structure & evolution of complex knowledge spaces, big data mining • WG 2 Theory of knowledge spaces • WG 3 Visual analytics – knowledge maps www.knowescape.org
  • 15. Digital Humanities as transient innovation With Sally Wyatt, June 2015
  • 16. dans.knaw.nl DANS is an institute of KNAW en NWO Thanks for your attention! Andrea.scharnhorst@dans.knaw.nl Twitter: @knowescape; Mendeley