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

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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

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Approach

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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.

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Life sciences

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(Bio) medical

sciences

Cognitive

sciences

Social

sciencesComputer

sciences &

Maths

Physical

sciences

Earth/

Environment

al sciences

Life sciences

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(Bio) medical

sciences

Cognitive

sciences

Earth/

Environment

al sciences

Countries selected for this study

• Belgium

• Brazil

• China

• Denmark

• Finland

• Germany

• Netherlands

• Poland

• Sweden

• Switzerland

• UK

• US

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Issues regarding individuals

• Name disambiguation;

• To which countries does an individual belong?

• Phase of a career vs. development of a country.

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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.

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Country analyses

• Measure performance using addresses (author

affiliation)

• Measure performance using performance of individuals

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Methodology – performance typologies used

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P

Highest

Lowest

PPtop10% MNJS

‘Top toppers’‘High impact’‘Top

producers’

Results

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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

USA 2,705,006 1.42 14

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

0 500 1,000 1,500 2,000 2,500 3,000

MN

CS

P * 1000

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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%

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Results – performance typology –

‘Top producers’

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Results – performance typology –

‘Top toppers’

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Results – trend of ‘new scholars’

Proportion top-toppers (all vs. ‘young’)

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0%

2%

4%

6%

8%

10%

12%

14%

all

Young

Conclusions and

perspectives

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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;

• …

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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;

• …

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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?

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Thank you

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