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From publications to people: bibliometric 
benchmarking of a selection of countries in the 
Life Sciences based on individual-level 
bibliometrics 
Rodrigo Costas & Ed Noyons 
Centre for Science and Technology Studies (CWTS), 
Leiden University, the Netherlands 
Funded by Crucell Vaccine Institute
2 
Introduction 
• Usual objects of bibliometric studies: Countries and 
institutions (affiliations) 
• The actual producers of knowledge are scholars 
• Two approaches for bibliometric studies: 
1. Measure performance of an institution/ country 
2. Measure performance of the individuals of an institution/country 
• 2nd approach less explored due to limitations in 
individual-level bibliometric data
Main objective of this study 
• To explore the potential of a bibliometric study of 
countries based on the performance of individuals 
‘affiliated’ to them 
3
Approach 
4
Data and Methodology 
• Web of Science (WoS), 1980-2011/12 
• Publication classification 
– Meso level (~800 clusters, fields); 
• Life Sciences (LS) [selection of publications by experts]; 
• Identified authors with algorithm (Caron & v.Eck); 
• Authors with 50% or more production in LS. 
5
Life sciences 
6 
Cognitive 
sciences 
(Bio) medical 
sciences 
Social 
sciences 
Computer 
sciences & 
Maths 
Physical 
sciences 
Earth/ 
Environment 
al sciences
Life sciences 
7 
Cognitive 
sciences 
(Bio) medical 
sciences 
Earth/ 
Environment 
al sciences
Countries selected for this study 
• Belgium 
• Brazil 
• China 
• Denmark 
• Finland 
• Germany 
• Netherlands 
• Poland 
• Sweden 
• Switzerland 
• UK 
• US 
8
Issues regarding individuals 
• Name disambiguation; 
• To which countries does an individual belong? 
• Phase of a career vs. development of a country. 
9
Approach regarding individuals 
• Individual authors disambiguated (Caron & van Eck, 2014) 
presented yesterday; 
• Calculation of 
– Most common certain address (MCAD) 
– Most probable recent address (MPRAD); 
• Individuals are assigned to the country by MCAD 
• ‘Certain’ linkages author-affiliations 
– Reprint addresses, direct linkages author-affiliation, e-mail data, single affiliation 
papers, etc.; 
• Information on the affiliations of individuals and their first year of 
publication (scientific age) 
– ‘Young’ researchers: first publication year in the last 10 years; 
• Threshold production: >5 publications. 
10
Country analyses 
• Measure performance using addresses (author 
affiliation) 
• Measure performance using performance of individuals 
11
Methodology – performance typologies used 
12 
P 
Highest 
Lowest 
PPtop10% MNJS 
‘Top top‘Hpeigrhs’ impact’ 
‘Top 
producers’
Results 
13
Performance in LS using addresses 
Country p MNCS 
BELGIUM 116,403 1.30 
BRAZIL 160,735 0.62 
DENMARK 92,649 1.33 
FINLAND 76,951 1.23 
GERMANY 600,804 1.12 
NETHERLANDS 224,797 1.38 
CHINA 275,071 0.75 
POLAND 79,398 0.61 
SWEDEN 167,862 1.25 
SWITZERLAND 151,463 1.48 
UK 682,433 1.36 
1.6 
1.4 
1.2 
1.0 
0.8 
0.6 
0.4 
0.2 
0.0 
0 500 1,000 1,500 2,000 2,500 3,000 
MNCS 
P * 1000 
USA 2,705,006 1.42 14
15 
Results using individuals (1) 
• Overall results about LS scholars ‘active in WoS’ 
country total 
%world 
scholars 
% P 
(addr) 
BELGIUM 12,008 0.92% 1.55% 
BRAZIL 28,798 2.20% 2.14% 
DENMARK 8,972 0.69% 1.24% 
FINLAND 9,495 0.73% 1.03% 
GERMANY 62,515 4.77% 8.01% 
NETHERLANDS 26,083 1.99% 3.00% 
PEOPLES R CHINA 46,119 3.52% 3.67% 
POLAND 10,818 0.83% 1.06% 
SWEDEN 18,180 1.39% 2.24% 
SWITZERLAND 13,953 1.07% 2.02% 
USA 289,494 22.11% 36.07% 
UK 60,900 4.65% 9.10% 
Total worldwide 1,309,458 100.00% 100%
16 
Results – performance typology – 
‘Top producers’
17 
Results – performance typology – 
‘Top toppers’
18 
Results – trend of ‘new scholars’
Proportion top-toppers (all vs. ‘young’) 
19 
14% 
12% 
10% 
8% 
6% 
4% 
2% 
0% 
all 
Young
Conclusions and 
perspectives 
20
Conclusions - results 
• Most western countries perform well in ‘top producers’ 
and production; 
• China, Poland & Brazil accelerate incorporation of ‘new’ 
scholars in the most recent years; 
• Percentage of young top-toppers relatively high in China 
and Brazil; 
• US dominates the main picture worldwide but not 
regarding young toppers; 
• … 
21
Conclusions - approach 
• New information and new perspectives 
– Productivity may be measured 
– Potential input to further characterize actors and their development 
– Insight into organization of science and national systems; 
• Complementary to overall performance analysis of 
actors 
– A combination of results will make the picture more complete; 
• … 
22
Further research 
• New pathways for research performance analysis: ‘bottom-up’ 
• ‘Ecosystems of scholars’ as opposed to single-dimension 
perspectives (e.g. h-index, Impact Factor, etc.) 
– Expansion of the ‘publish or perish’ debate 
• Data issues: 
– Name disambiguation 
– Better linkage authors-affiliations 
• Other classificatory approaches 
– Characteristic Scores and Scales approach instead of percentiles 
• Other disciplines, mobility 
• How to consider the bibliometric analysis of individuals? 
23
Thank you 
24

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20140905 sti costas_noyons

  • 1. From publications to people: bibliometric benchmarking of a selection of countries in the Life Sciences based on individual-level bibliometrics Rodrigo Costas & Ed Noyons Centre for Science and Technology Studies (CWTS), Leiden University, the Netherlands Funded by Crucell Vaccine Institute
  • 2. 2 Introduction • Usual objects of bibliometric studies: Countries and institutions (affiliations) • The actual producers of knowledge are scholars • Two approaches for bibliometric studies: 1. Measure performance of an institution/ country 2. Measure performance of the individuals of an institution/country • 2nd approach less explored due to limitations in individual-level bibliometric data
  • 3. Main objective of this study • To explore the potential of a bibliometric study of countries based on the performance of individuals ‘affiliated’ to them 3
  • 5. Data and Methodology • Web of Science (WoS), 1980-2011/12 • Publication classification – Meso level (~800 clusters, fields); • Life Sciences (LS) [selection of publications by experts]; • Identified authors with algorithm (Caron & v.Eck); • Authors with 50% or more production in LS. 5
  • 6. Life sciences 6 Cognitive sciences (Bio) medical sciences Social sciences Computer sciences & Maths Physical sciences Earth/ Environment al sciences
  • 7. Life sciences 7 Cognitive sciences (Bio) medical sciences Earth/ Environment al sciences
  • 8. Countries selected for this study • Belgium • Brazil • China • Denmark • Finland • Germany • Netherlands • Poland • Sweden • Switzerland • UK • US 8
  • 9. Issues regarding individuals • Name disambiguation; • To which countries does an individual belong? • Phase of a career vs. development of a country. 9
  • 10. Approach regarding individuals • Individual authors disambiguated (Caron & van Eck, 2014) presented yesterday; • Calculation of – Most common certain address (MCAD) – Most probable recent address (MPRAD); • Individuals are assigned to the country by MCAD • ‘Certain’ linkages author-affiliations – Reprint addresses, direct linkages author-affiliation, e-mail data, single affiliation papers, etc.; • Information on the affiliations of individuals and their first year of publication (scientific age) – ‘Young’ researchers: first publication year in the last 10 years; • Threshold production: >5 publications. 10
  • 11. Country analyses • Measure performance using addresses (author affiliation) • Measure performance using performance of individuals 11
  • 12. Methodology – performance typologies used 12 P Highest Lowest PPtop10% MNJS ‘Top top‘Hpeigrhs’ impact’ ‘Top producers’
  • 14. Performance in LS using addresses Country p MNCS BELGIUM 116,403 1.30 BRAZIL 160,735 0.62 DENMARK 92,649 1.33 FINLAND 76,951 1.23 GERMANY 600,804 1.12 NETHERLANDS 224,797 1.38 CHINA 275,071 0.75 POLAND 79,398 0.61 SWEDEN 167,862 1.25 SWITZERLAND 151,463 1.48 UK 682,433 1.36 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0 500 1,000 1,500 2,000 2,500 3,000 MNCS P * 1000 USA 2,705,006 1.42 14
  • 15. 15 Results using individuals (1) • Overall results about LS scholars ‘active in WoS’ country total %world scholars % P (addr) BELGIUM 12,008 0.92% 1.55% BRAZIL 28,798 2.20% 2.14% DENMARK 8,972 0.69% 1.24% FINLAND 9,495 0.73% 1.03% GERMANY 62,515 4.77% 8.01% NETHERLANDS 26,083 1.99% 3.00% PEOPLES R CHINA 46,119 3.52% 3.67% POLAND 10,818 0.83% 1.06% SWEDEN 18,180 1.39% 2.24% SWITZERLAND 13,953 1.07% 2.02% USA 289,494 22.11% 36.07% UK 60,900 4.65% 9.10% Total worldwide 1,309,458 100.00% 100%
  • 16. 16 Results – performance typology – ‘Top producers’
  • 17. 17 Results – performance typology – ‘Top toppers’
  • 18. 18 Results – trend of ‘new scholars’
  • 19. Proportion top-toppers (all vs. ‘young’) 19 14% 12% 10% 8% 6% 4% 2% 0% all Young
  • 21. Conclusions - results • Most western countries perform well in ‘top producers’ and production; • China, Poland & Brazil accelerate incorporation of ‘new’ scholars in the most recent years; • Percentage of young top-toppers relatively high in China and Brazil; • US dominates the main picture worldwide but not regarding young toppers; • … 21
  • 22. Conclusions - approach • New information and new perspectives – Productivity may be measured – Potential input to further characterize actors and their development – Insight into organization of science and national systems; • Complementary to overall performance analysis of actors – A combination of results will make the picture more complete; • … 22
  • 23. Further research • New pathways for research performance analysis: ‘bottom-up’ • ‘Ecosystems of scholars’ as opposed to single-dimension perspectives (e.g. h-index, Impact Factor, etc.) – Expansion of the ‘publish or perish’ debate • Data issues: – Name disambiguation – Better linkage authors-affiliations • Other classificatory approaches – Characteristic Scores and Scales approach instead of percentiles • Other disciplines, mobility • How to consider the bibliometric analysis of individuals? 23

Notas do Editor

  1. Random if not clear
  2. What question we cant answer with this?