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Deutsche Forschungsgemeinschaft
www.dfg.de DFG
The Use of Research Funding Databases for Research Assessment Information Systems
Presented at the 8th international Conference onCurrent Research Information Systems
May 11-13th, 2006 in Bergen, Norway
Daniel Bovelet, German Research Foundation (DFG)
Department of Information Management
1 Agenda Page 2 of 9
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
Agenda
Short Introduction into research assessment systems and the DFG Funding Ranking
Development of Research Assessment Information Systems based on research funding databases
2 Research Assessment Systems and the DFG Funding Ranking Page 3 of 9
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
Idea of Research Assessment Systems
History of the DFG Funding Ranking
First Ranking in 1997 DFG funding instruments and programmes
Second Ranking 2000 new: regional aggregation of data
Third Ranking 2003 new: networks in science
new: several other indicators based on heterogeneous research funding databases
Fourth Ranking 2006 => Extended Version: new indicators, detailed analysis of 14 research areas
Systems of research assessment, such as ranking exercises, are internationally discussed as important strategic management tools for publicly funded research institutions and, more than ever, are becoming determinants for research policy decision-making processes. Idea:
To give information on research activity and quality of research institutions
To inform about the disciplinary research profile of these institutions
To inform about regional research clusters and networks in science
The research indicators are primarily derived from process produced databases covering funding processes of research funding agencies
No surveys, no biliometric data – „only“ funding!
New approach of the DFG Funding Ranking
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
3 Developement of a CRIS based on the DFG Funding Ranking Page 4 of 9
Research Funding Databases (DFG funding & reviewers, AvH, DAAD, Bund, EU, StatBund)
The different properties of funding databases can be used for the derivation of research indicators suitable for the representation of the research activities and achievements of
research institutions differentiated by several units of analysis (e.g. scientific disciplines)
Research Assessment Information System covering 14 research areas
research indicators
Institutional Reports - Geographical Information Systems - Network Analytical Representations
integration
consolidation of heterogeneous databases
unique framework for the subject classification concordance/classifications for institutional codes
standardization process
derivation of indicators
STANDARDIZATION
HETEROGENEOUS
RESEARCH FUNDING DATABASES
OtherResearch Councils
Government FoundationsFederal
StatisticalOffice
researchfunding and
infrastructuraldata
Businessand
Industry
research areaclassifications
institutionalclassifications
InternationalOrganisations
researcharea
researchinstitution
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
3.1 Data sources and the need of standardization processes Page 5 of 9
DFG
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
3.2 Institutional reports Page 6 of 9
Characteristics
Enable comprehensive information on the parameter values of the research indicators
Several indicators can be examined in an overall context for each research institution
For the representation and interpretation of the respective values, the relation to a specific benchmark (e.g. by using ranking groups) should be taken into consideration
The information system is additionally able to provide qualitative information on the institution and its infrastructure (e.g. titles of funded research programmes)
Example for institutional reports
Figure on the University of Munich
The report offers information on three goups of research indicators: financial capital structure, the human resources and indicators suituable for the representation of the internationality
The research indicators can be differentiated according to scientific discipline or research funding programmes...
University of Munich
Regular Expenditure (= total)
Administrative income
Third party funding income Regular core funds
Financial resources (in mio. €)
1947.5
(100%)
919.7
(47.2%)
212.7
(10.9%)
815.1
(41.9%)
PrizesTotalIndividual Grants Programme
Coordinated Programme
Direct Promotion of Young Researchers
TotalHumanities and Social Sciences Life Sciences Natural Sciences Engineering Sciences
116.9
(100%)40.0(34.2%)
67.6
(57.8)
5.7
(4.9%)
3.6
(3.1%)
DFG approvals
(in mio. €)
Financial Data
Total Humanities and Social Sciences
Life Sciences Natural Sciences Engineering Sciences
Scientists (Total)
5129 (100%)
1270
(24.8%)
3006
(58.6%)
790
(15.4%)
48
(0.9%)
Professors710
(100%)306(43.1%)
274
(38.6%)
122
(17.2%)7(1%)
DFG
reviewers
309
(100%)
110
(35.6%)
148
(47.9%)
47
(15.2%)
4
(1.3%)
Personnel Data
Total Humanities and Social Sciences
Life Sciences Natural Sciences
Internationality
Engineering Sciences
DAAD scientists& academics
103
(100%)
70
(68.0%)
22
(21.4%)
11
(10.7%)
-
(0%)
AvH research fellows & award winners
115
(100%)
44
(38.3%)
24
(20.9%)
45
(39.1%)
2
(1.7%)
DFG approvals
(in mio. €)
116.9
(100%)
22.9
(19.6%)
70.0
(59.9%)
21.7
(18.6%)
2.3
(2.0%)
University of Munich
Regular Expenditure (= total)
Administrative income
Third party funding income Regular core funds
Financial resources (in mio. €)
1947.5
(100%)
919.7
(47.2%)
212.7
(10.9%)
815.1
(41.9%)
PrizesTotalIndividual Grants Programme
Coordinated Programme
Direct Promotion of Young Researchers
TotalHumanities and Social Sciences Life Sciences Natural Sciences Engineering Sciences
116.9
(100%)40.0(34.2%)
67.6
(57.8)
5.7
(4.9%)
3.6
(3.1%)
DFG approvals
(in mio. €)
Financial Data
Total Humanities and Social Sciences
Life Sciences Natural Sciences Engineering Sciences
Scientists (Total)
5129 (100%)
1270
(24.8%)
3006
(58.6%)
790
(15.4%)
48
(0.9%)
Professors710
(100%)306(43.1%)
274
(38.6%)
122
(17.2%)7(1%)
DFG
reviewers
309
(100%)
110
(35.6%)
148
(47.9%)
47
(15.2%)
4
(1.3%)
Personnel Data
Total Humanities and Social Sciences
Life Sciences Natural Sciences
Internationality
Engineering Sciences
DAAD scientists& academics
103
(100%)
70
(68.0%)
22
(21.4%)
11
(10.7%)
-
(0%)
AvH research fellows & award winners
115
(100%)
44
(38.3%)
24
(20.9%)
45
(39.1%)
2
(1.7%)
DFG approvals
(in mio. €)
116.9
(100%)
22.9
(19.6%)
70.0
(59.9%)
21.7
(18.6%)
2.3
(2.0%)
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
3.3 Geographic Information Systems Page 7 of 9
Characteristics
Using a GIS in the context of several types of research indicators provides perspectives on the various research institutions and surrounding regions with their scientific infrastructure
The figures provide insight into the research regions and enable regional focal points to be identified
Several levels of analysis can be displayed for different indicators, such as an overall view for Germany, distributions for the federal states, or allocation by administrative districts
Example for cartographical representations
Figure on allocations of DFG approvals
The data is processed in such a way that conclusions are drawn according to administrative rural and urban districts
A district code is assigned to each institution implemented in the research institution directory and standardized (address) database
For institutions located at multiple locations, each site is allocated ist own code
Humanities and Social SciencesLife SciencesNatural SciencesEngineering Sciences
Scientific DisciplineHumanities and Social SciencesLife SciencesNatural SciencesEngineering Sciences
Scientific Discipline
8th international Conference on Current Research Information Systems (2006 in Bergen, Norway) DFG
3.4 Network Analytical Representations Page 8 of 9
UniversityHelmholtz Association (HGF)Leibniz Association (WGL)Max Planck Society (MPG)Fraunhofer Society (FhG)Others
threshold value: joint participation in at least three research network programmes
UniversityHelmholtz Association (HGF)Leibniz Association (WGL)Max Planck Society (MPG)Fraunhofer Society (FhG)Others
threshold value: joint participation in at least three research network programmes
Characteristics
The network or relationship structures between research institutions can be visualized in the form of network analytical representations
The graphs can be analysed in the following way
institutions that are central to the structure are positioned centrally
institutions that interact frequently are positioned close to each other
the line thickness indicates the frequency of interaction between two institutions
the diameter of circles represents the total number of interactions
Example for Network Analytical Representations
Figure on DFG coordinated programmes
The relationship structure results from joint participation of institutions in DFG coordinated programmes
The figure shows the core network in biology
Thank you for your attention!
More Infos at www.dfg.de/
Daniel Bovelet, Department of Information [email protected]
Deutsche Forschungsgemeinschaft
www.dfg.de DFG