Andrea Scharnhorst (2016) Why do we need to model the science system? Talk at the seminar of the Eindhoven Centre for Innovation Sciences, June 2, 2016
This PowerPoint helps students to consider the concept of infinity.
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 ….
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, ….
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
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