Upload
knowescape2013
View
140
Download
0
Embed Size (px)
Citation preview
Science mapsas ways to indicate knowledge transfer
SSSSáááándor Sondor Sondor Sondor SoóóóóssssDept. Science Policy and Scientometrics
Library and Information Centre of the Hungarian Acad. Sci.
George KampisGeorge KampisGeorge KampisGeorge KampisLorand Eötvös University, Budapest, Hungary
Overview
� Preliminaries: A global map of science
� Preliminaries: Research profiles
� Preliminaries: Structural measures
� Problems of measuring Knowledge dynamics
� A flexible proposal
� Application1: Development of science
� Application2: Research evaluation
� Application3: Career and mobility studies
A global map of science
A global science map from (Rafols, Porter & Leydesdorff, 2009), based on WoS databases
� Unit of analysis: ISI Subject Category (SC)
� The map: the proximity network of SCs
� Method: „bibliometric coupling” of SCs
� Disciplines: clusters (factors) in the proximity network
Rafols, Porter and Leydesdorff (2009)
Cognitive Sci.
Agri Sci
Biomed Sci
Chemistry
Physics
Engineering
Env Sci & Tech
Matls Sci
Infectious
Diseases
Psychology
Social Studies
Clinical Med
Computer Sci.
Business & MGT
Geosciences
Ecol Sci
Econ. Polit. & Geography
Health & Social Issues
Global Map of Science, 2007221 SCI-SSCI Subject Categories
Modelling research profilesThe science overlay technique
� Position of an actor within the scientific landscape=
� Structure of its research profile
� Method: Mapping a set of publications onto the global map (basemap)
� SCs related to the publication record are highlighted, indicating their respective weights
Structural measures
� Measuring multi- and interdisciplinarity (IDR) upon this model: the Stirling index
� Novelty: Three structural features accounted for:� Number of SCs („variety”)� Distribution of pubs over SCs („balance”)� Proximity/distanceProximity/distanceProximity/distanceProximity/distance of constituent SCs („disparity”)
Potential: knowledge dynamics
?
A flexible proposal
Mean Overlay Distance (MOD)Mean Overlay Distance (MOD)Mean Overlay Distance (MOD)Mean Overlay Distance (MOD) = ∑==
mn
ji
ijji dppmn
,
1,1*
1
The (average) distance between two overlay mapsbased on pairwise (weighted) cognitive distances between constituent SCs
App1: development of science
citing
cited
∑==
mn
ji
ijji dppmn
,
1,1*
1
App1: development of science
� MOD: measuring knowledge diffusion/integrationmeasuring knowledge diffusion/integrationmeasuring knowledge diffusion/integrationmeasuring knowledge diffusion/integration through citation networks (evolution of a scholarly discourse)
� A detailed, large-scale case study: the species problem
App1: development of science
App1: development of science
App1: development of science
App1: development of science
App1: development of science
App2: Research evaluation
� MOD as an evaluative/impact measure
� Usual impact measures: based on quantity
� Absolute (number of cits)
� Normalized (field-normalized relative impact)
� Weighted (eigenfactor)
MOD in this context: scope of citation impactscope of citation impactscope of citation impactscope of citation impact
App2: Research evaluation
� MOD as an impact measure:
� How far (distance) a publication gets from its own research field, i.e. what effect it bears on the scientific landscape
Carley, S., & Porter, A. L. (2012). A forward diversity index. Scientometrics, 90(2), 407-427.
App3: career and mobility studies
� Seldom addressed dimension of scientific careers and mobility: development of a research profile
� Important variable of econometric models on mobility:
� Effect of profile dynamics on productivity or vice versa (generalist or specialist strategies)
� Effect of various mobility dimensions on a research profile and vice versa
� SISOB (Science in Society Observatorium) program, FP7, Mobility use case
App3: career and mobility studies
� The Stirling indexStirling indexStirling indexStirling index as an aggregated/staticaggregated/staticaggregated/staticaggregated/static measure of research profile development: thematic mobilitythematic mobilitythematic mobilitythematic mobility for a large sample of engineers (SISOB case study) provided by SISOB partner Fondazione Rosselli (U Turin)
Sample distribution of thematic mobility Sample distribution by average number
of coauthors
App3: career and mobility studies
� MOD in this context: thematic mobility, dynamic versionthematic mobility, dynamic versionthematic mobility, dynamic versionthematic mobility, dynamic version
Career stage (n)
∑==
mn
ji
ijji dppmn
,
1,1*
1
Career stage (n+1)
Acknowledgement
� This paper was supported by
� the European Commission under the FP7 Science in Society Grant No. 266588 (SISOB project),
� the European Union and the European Social Fund through project FuturICT.hu (grant no.: TÁMOP-4.2.2.C-11/1/KONV-2012-0013),
� the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.