RESEARCH ARTICLE

Comprehensive mapping of local and diaspora
科学家: A database and analysis of
63,951 Greek scientists

约翰·P. A. Ioannidis1

, Chara Koutsioumpa2

, Angeliki Vakka3

, Georgios Agoranos4

Chrysanthi Mantsiou5
Despina G. Contopoulos-Ioannidis8

, Maria Kyriaki Drekolia6

, Nikos Avramidis7

, Konstantinos Drosatos9,10

, and Jeroen Baas11

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1Stanford Prevention Research Center, Department of Medicine, and Department of Epidemiology and Population Health,
Stanford University School of Medicine and Meta-Research Innovation Center at Stanford (METRICS), 斯坦福大学, 加利福尼亚州, 美国
2Department of Neurobiology, 哈佛医学院, 波士顿, 美国
3School of Medicine, University of Patras, 希腊
4Hellenic Center of Mental Health and Research (EKEPSYE), 雅典, 希腊
5Clinical Research and Evidence-Based Medicine Unit, Second Medical Department,
Aristotle University of Thessaloniki, Thessaloniki, 希腊
6Institute for Vascular Signalling, Centre for Molecular Medicine, Goethe University, Frankfurt am Main, 德国
7Roslin Institute, 爱丁堡大学
8Department of Pediatrics, Stanford University School of Medicine, 斯坦福大学, 加利福尼亚州, 美国
9Department of Pharmacology, Center for Translational Medicine, Lewis Katz School of Medicine,
Temple University, 费城, PA, 美国
10ARISTEiA-Institute for the Advancement of Research & Education in Arts, 科学 & 技术, McLean, VA, 美国
11爱思唯尔, 阿姆斯特丹, 荷兰

关键词: brain drain, diaspora, 希腊, science mapping, scientific workforce

抽象的

Research policy and planning for a given country may benefit from reliable data on both its
scientific workforce as well as the diaspora of scientists for countries with a substantial brain
drain. Here we use a systematic approach using Scopus to generate a comprehensive country-
level database of all scientists in Greece. 而且, we expand that database to include also
Greek diaspora scientists. The database that we have compiled includes 63,951 scientists who
have published at least five papers indexed in Scopus. Of those, 35,116 have an affiliation in
希腊. We validate the sensitivity and specificity of the database against different control sets of
科学家. We also analyze the scientific disciplines of these scientists according to the Science
Metrix classification (174 subfield disciplines) and provide detailed data on each of the 63,951
scientists using multiple citation indicators and a composite thereof. These analyses demonstrate
differential concentrations in specific subfields for the local versus the diaspora cohorts, 作为
well as an advantage of the diaspora cohort in terms of citation indicators, especially among
top-impact researchers. The approach that we have taken can also be applied to map the
scientific workforce of other countries and nations for evaluation, 规划, and policy purposes.

介绍

The construction of scientist databases can be a useful tool for evaluation, 规划, and policy-
making related to science. Efforts to compile national databases of scientists with performance
指标, in particular citation indices, are sometimes undertaken by research assessment author-
实体 (Moed, 2008; Rijke, Wouters et al., 2016). Often these efforts may not be sufficiently

开放访问

杂志

引文: Ioannidis, J. 磷. A。,
Koutsioumpa, C。, Vakka, A。, Agoranos,
G。, Mantsiou, C。, Drekolia, 中号. K.,
Avramidis, N。, Contopoulos-Ioannidis,
D. G。, Drosatos, K., & Baas, J. (2021).
Comprehensive mapping of local and
diaspora scientists: A database and
analysis of 63,951 Greek scientists.
Quantitative Science Studies, 2(2),
733–752. https://doi.org/10.1162/qss_a
_00136

DOI:
https://doi.org/10.1162/qss_a_00136

Peer Review:
https://publons.com/publon/10.1162
/qss_a_00136

已收到: 21 一月 2021
公认: 24 行进 2021

通讯作者:
约翰·P. A. Ioannidis
jioannid@stanford.edu

处理编辑器:
Ludo Waltman

版权: © 2021 约翰·P. A. Ioannidis,
Chara Koutsioumpa, Angeliki Vakka,
Georgios Agoranos, Chrysanthi
Mantsiou, Maria Kyriaki Drekolia,
Nikos Avramidis, Despina G.
Contopoulos-Ioannidis, Konstantinos
Drosatos, and Jeroen Baas. 已发表
under a Creative Commons
归因 4.0 国际的
(抄送 4.0) 执照.

麻省理工学院出版社

Comprehensive mapping of local and diaspora scientists

包括的. 例如, they may depend on nonsystematic efforts where scientists voluntarily
contribute information themselves to be included. 而且, citation metrics are difficult to
standardize, especially when they are not calculated according to the same processes for all
科学家, and when differences between scientific fields are insufficiently accounted for.
重要的, for many countries, brain drain is a major challenge for their scientific workforce
(Doria Arrieta, Pammolli, & 彼得森, 2017; Ioannidis, 2004; Veugelers, 2017). In these coun-
尝试, planning and policy decisions would greatly benefit from mapping not only the disciplines
and impact of scientists who still work in the country but also of those who have emigrated else-
在哪里. First-generation emigrating scientists and often even second and higher generation em-
igrants may often still be interested in engaging with the scientific workforce of their country of
origin, thus contributing valuable expertise. Countries with strong diaspora may benefit from the
skills of diaspora scientists. Scientific diaspora can be useful for both the mobile scientists
(Halevi, Moed, & Bar-Ilan, 2016; 彼得森, 2018; Robinson-Garcia, Sugimoto, 等人。, 2019)
and the countries involved at both ends, as it can constitute a modern tool of scientific diplomacy
and cooperation between the two countries (Stark, Helmenstein & Prskawetz, 1997; 瓦格纳 &
Jonkers, 2017).

Here we demonstrate how a large-scale standardized approach can be used to create an
包括的, comprehensive database of scientists in a specific nation. 而且, we show how
one can expand that database to include also scientists who have migrated to other countries.
We focus our efforts on Greece and its national workforce and scientific diaspora. Greece is a
country that has sustained a very strong current of brain drain over the years (Ifanti, Argyriou
等人。, 2014; Moris, Karachaliou, & Kontos, 2017; Theodoropoulos, Kyridis et al., 2014;
Trachana, 2013). 而且, the country has been hit by a major economic crisis that has se-
verely limited funding for research and development. Despite some improvements in recent
年, funding remains highly suboptimal. 此外, scientists of Greek origin include
many extremely influential scientists worldwide and past analyses suggest that there are many
high-impact Greek scientists, both in Greece and abroad, who are leaders in their fields (Yurte,
2017). 而且, such previous work has suggested that the number of Greek scientists with
substantial impact is much higher proportionately than the share of Greeks in the global pop-
计算 (10 million in Greece and perhaps another 3 million in the diaspora) (Yurte, 2017).
Mapping Greek scientists in Greece and worldwide would be a valuable resource. The avail-
ability of comprehensive science publications databases such as Scopus and the fact that
many Greek first names and a large majority of Greek last names tend to be highly specific
for Greek descent allow the creation of a database of scientists of Greek origin. 在本文中,
we describe how we have constructed such a database and how we have examined its sen-
sitivity and specificity in validation samples. We also present descriptive data for the entire
database and for comparative evaluations of Greek origin scientists who have an affiliation
in Greece and for those who have an affiliation in other countries. Our work may offer a tem-
plate for similar scientist-mapping efforts on other countries.

2. 方法

2.1. Eligibility Criteria

We aimed to capture all scientists of Greek origin who have at least five published papers (文章,
reviews, and conference proceedings). Eligible scientists were both those born in Greece and
those born elsewhere (second or higher generation), but whose family had a Greek origin.
Scientists were eligible regardless of whether they had their current main affiliation in Greece
or elsewhere. We excluded scientists who had fewer than two papers published after 1950.

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Comprehensive mapping of local and diaspora scientists

The overall strategy aimed at finding typical Greek names first and then retrieving all author
profiles with these names. To capture eligible scientists with an affiliation in Greece, we queried
Scopus (Baas, Schotten et al., 2020) as of January 15, 2020 and identified all the last names that
had at least one author ID (with any number of papers assigned) that included an affiliation in
希腊. 我们发现 70,967 names where at least one author ID has an affiliation address in
希腊. One researcher manually screened all of these names to identify those that seemed
to be of Greek origin, allowing for inclusion of those who might be probable, to avoid losing
potentially eligible names. A second researcher then examined the manual extraction and made
amendments. 最终, 57,732 last names were retained.

We also screened manually the files of the top 100,000 most cited scientists based on a
composite indicator that had been published previously (Ioannidis, Baas et al., 2019). We used
three different files of the top-cited scientists, each of which captured the top 100,000 包括-
ing self-citations as well as the top 100,000 excluding self-citations based on career-long data
in Scopus until the end of 2017 (https://dx.doi.org/10.17632/btchxktzyw.1#file-ad4249ac-f76f
-4653-9e42-2dfebe5d9b01); based on citations received during a single calendar year (2017)
(https://dx.doi.org/10.17632/btchxktzyw.1#file-b9b8c85e-6914-4b1d-815e-55daefb64f5e);
and based on career-long data until the end of 2018 (https://dx.doi.org/10.17632/btchxktzyw
.1#file-bade950e-3343-43e7-896b-fb2069ba3481). These three files manually yielded 1,044,
990, 和 1,013 eligible authors of Greek origin, with large overlap between the three lists.

此外, two online sources of common Greek first names (forebears.io and www
.studentsoftheworld.info/penpals/stats.php?Pays=GRE) were screened manually starting from
the most common ones until 86 first names were selected that were thought to be relatively
specific for Greek origin people. 例如, George is a common name in Greece, 但它是
not Greek specific (IE。, the vast majority of people with first name George are not of Greek
origin). 反过来, Georgios is highly Greek specific.

At the next step, we retrieved from Scopus all author ID files with at least five papers (文章,
reviews, or conference papers) where scientists had either a seemingly Greek-specific last name
(any of the 57,332 last names mentioned above, or any of the last names of highly cited Greek sci-
entists according to any of the three previously published lists) or a seemingly Greek-specific first
姓名 (any of the 86 上文提到的). 最终, 124,656 author ID files were retrieved.

这些 124,656 files were manually screened, perusing the information for each scientist,
including the first name, last name, country of listed affiliation, and institution of listed affiliation
that could help identify if the scientist was of Greek origin or not. The availability of all scientists
who shared one of the seemingly Greek-specific names along with country information allowed
us to identify whether any of these names were in fact not Greek-specific. Some last names occur
identically both in Greeks and in some other nationality (例如, Adam or Spinelli). In these cases,
information on first name could help classify that individual if the first name was characteristi-
cally Greek. If the first name did not help to differentiate in this regard, the country information
was used to arbitrate. The site https://forebears.io/ was consulted also in ambiguous cases,
because it shows the relative frequency of surnames and names across different countries. If a
scientist in a given country had a surname that appeared more frequently in Greece than in other
国家, she or he was considered of Greek origin.

的 124,656 author files, it was concluded that 62,837 were very likely Greek. We listed
alphabetically by last names the 62,837 authors and recorded additional first names that
seemed to be Greek specific. By screening 2,000 names at a time, it was found that relatively
few new Greek-specific names were added after screening 8,000 authors and the incremental
addition of eligible Greek origin authors would be limited by adding more first names. 这

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Comprehensive mapping of local and diaspora scientists

process yielded 370 seemingly Greek-specific first names and we then searched Scopus for all
additional author IDs with these first names that had not been already captured in the 62,837.
These additional authors were then manually screened, 和 1,012 were deemed (基于
their name and country information) to be eligible. The resulting database, comprising
63,849 author IDs, was subjected to validation checks as described below. Additions and de-
letions emerging during these validation checks and a final contribution by the authors of the
present study of Greek scientists they knew of but who had not been captured increased the
final count by 102 to a final count of 63,951 author IDs.

The process is summarized in Figure 1.

2.2. 验证: Sensitivity for Capturing Scientists of Greek Origin Who Are in Greece

To evaluate the sensitivity of the compiled database in capturing scientists who work in
希腊, we searched whether it had included scientists working at a university in Greece,
the University of Thessaly. Scientists working in different universities and research institutions
in Greece are not likely to have systematically different names, so one university is likely to
provide a reasonably representative sample. We searched Google Scholar as the reference

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数字 1. Flow diagram for identification of Greek scientists.

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Comprehensive mapping of local and diaspora scientists

数据库, as scientists need to enter their names and affiliations by themselves in creating a
profile in Google Scholar. 这 130 most cited scientists with profiles and University of
Thessaly affiliation in Google Scholar were screened and it was found that all of them (130/130)
had been included in our compiled database. 所以, the sensitivity was 100%, with binomial
95% confidence interval of 97.2% 到 100%.

2.3. 验证: Sensitivity for Capturing Scientists of Greek Origin Who Are not in Greece

To evaluate the sensitivity of the compiled database in capturing scientists of Greek origin who
do not work in Greece, we used two approaches.

第一的, we used a sample of scientists who had entered their names in a LinkedIn database of
Greek biomedical scientists created by one of us (K. D .) for the World Hellenic Biomedical
协会. We only considered names that had been entered by the scientists themselves,
proving that they identified themselves as Greek; and we further limited the search to scientists
who gave an address outside of Greece and who had a work title suggesting that they are
faculty or other people in senior positions, as opposed to students. 的 42 such individuals,
34 were found to have at least five papers in Scopus. Of those 34, 26 were captured in the
compiled database, for a sensitivity of 76.5% (95% confidence interval, 58.8% 到 89.3%).

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第二, we used the names of people listed in the Wikipedia entry on Greek Diaspora. 这些
names are not necessarily of scientists; therefore we examined whether each of the names would
have been captured either through one of the Greek-specific last names or through one of the first
Greek-specific names that we had put together to compile our database of Greek scientists. 为了
artists and other people who had acquired an artistic/stage name, we used their original name, 作为
changing to artistic/stage names would not apply for scientists. We excluded from the screening
people born before 1900, as Greek names in the remote past may have been different.
最终, 28 first-generation and 88 第二- or later-generation Greeks were eligible for
screening. Of these 14/28 和 35/88 would have been captured by our last or first name
searches, corresponding to sensitivities of 50% (95% confidence interval, 30.6% 到 69.4%)
和 39.8% (95% confidence interval, 29.4% 到 50.8%), 分别.

The sensitivity estimates should be interpreted cautiously given the relatively small numbers

and they leave some uncertainty about the total number of diaspora scientists.

2.4. 验证: Specificity for Capturing Scientists of Greek Origin

To evaluate whether the compiled database might have captured any scientists who were not
actually Greek, we randomly selected 100 的 63,849 author IDs. For each of them, we tried to
find whether we could find their name written in Greek in the web. 的 100, their Scopus
affiliation was in Greece for 62, in Cyprus for four, and in other countries for 32; for two authors
we had no listed affiliation in Scopus. We could find their name written in Greek for all 100
authors. 所以, the specificity was 100% (95% confidence interval 96.4% 到 100%).

2.5. Evaluation of Split Author Files

Some scientists in Scopus may have their published work split in two or more author ID files,
and Scopus encourages authors to communicate directly with them to merge such split files. 到
assess how common this pattern might be in the compiled database of Greek authors, after list-
ing the names alphabetically, every 600th name was selected and assessed whether more than
one author ID files may exist for that person in the database. 的 106 screened names, 九
(8.5%, 95% CI, 4.0 到 15.5%) had their work split into two files (n = 8) or three files (n = 1).

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Comprehensive mapping of local and diaspora scientists

2.6. Data Included for Each Scientist in the Database

From each author ID file included in the database, the following information is included based
on data directly imported from Scopus on October 1, 2020 (什么时候 7,983,030 author ID files
with at least five papers (文章, reviews, or conference papers) were available in Scopus) 和
calculations that are the same as those performed for a recently published list of top-cited
科学家 (Ioannidis, Boyack, & Baas, 2020): affiliation and country; publication year of earlier
and latest Scopus-indexed publication; number of publications; number of publications in
1960–2020; six citation indicators (total citations, h-index, hm-index, citations to single-
authored publications, citations to first- or single-authored publications, citations to first-,
single-, or last-authored publications) and their composite (all indicators being presented both
with and without self-citations); proportion of self-citations; ratio of citations to citing papers;
ranking according to the composite indicator among all scientists worldwide with at least five
文件; most common field of publications according to the 22-field Science Metrix classifi-
阳离子; two most common subfields of publications according to the 174-subfield Science
Metrix classification; and ranking according to the composite indicator among all the scientists
in the same main (most common) Science Metrix subfield. For details on the Science Metrix
classification see Archambault, Beauchesne, and Caruso (2011) and Zhang, 赵, and LeCun
(2015). For authors where Scopus listed an affiliation but not a country, we tried to identify the
country whenever it would be unambiguous based on the provided affiliation.

3. 结果

3.1. Main Descriptive Characteristics

的 63,951 author ID files included in the final database, country of affiliation was available
为了 63,174, 和 35,116 (55.6%) of them had their affiliation in Greece. Large shares of this cohort

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数字 2. Worldwide distribution of scientists.

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of scientists were also located in the United States (n = 9,339, 14.8%), 英国 (n =
6,165, 9.8%), 德国 (n = 2,083, 3.3%), 塞浦路斯 (n = 1,688, 2.7%), 澳大利亚 (n = 1,155,
1.8%), 法国 (n = 1,141, 1.8%), 加拿大 (n = 1,110, 1.8%), and Switzerland (n = 994,
1.6%), but the diaspora was worldwide (数字 2).

A total of 12,299 (19.2%) scientists had published their first Scopus-indexed paper after
2010 和 38,248 (59.8%) had been recently active, publishing their last paper in 2018 or later.
The median number of published papers was 13 (interquartile range 8 到 31) and the median
number of citations was 153 (interquartile range 52 到 478).

如表所示 1, scientists with affiliation in Greece had a similar number of papers to
scientists with affiliation outside of Greece, but they had substantially fewer citations and
fewer papers that cited their work, and were placed on average in lower ranks compared with
scientists with affiliation outside of Greece. The results were qualitatively similar regardless of
whether self-citations were counted or excluded (桌子 1). Scientists with affiliation outside of
Greece tended to have younger publication ages (median for year of first publication 2004
相对 2002).

A total of 33,956 scientists with affiliation in Greece and 26,150 scientists with affiliation in
other countries could be assigned to a main scientific subfield. Among scientists who were in
the top 0.1% of their subfield, the vast majority (86%) of them had an affiliation outside of
Greece rather than in Greece (96 相对 15). For the top 0.5%, the respective numbers were
348 相对 89, for the top 1% the respective numbers were 648 相对 250, and for the top 5%
the respective numbers were 2,438 相对 1,724, always with a strong preponderance of

桌子 1.

Characteristics of scientists according to their country of current affiliation

Characteristic, median (IQR)
Number of papers

Year of first paper

Year of most recent paper

Ranking across all science,

数千 (excluding self-citations)

Citations (excluding self-citations)

Citing papers (excluding self-citations)

Citations to citing papers ratio (excluding self-citations)

Percentage of self-citations

Affiliation in Greece
n = 35,116

13 (7–30)

2002 (1993–2008)

2019 (2013–2020)

3,505 (1,691–5,463)

139 (50–408)

131 (48–375)

1.04 (1.00–1.11)

14 (7–25)

Affiliation in other
country n = 28,058

14 (8–32)

2004 (1994–2010)

2019 (2014–2020)

2,812 (1,265–4,730)

184 (59–609)

169 (55–541)

1.07 (1.02–1.16)

15 (8–25)

Ranking across all science, 数千 (with self-citations)

3,508 (1,681–5,458)

2,801 (1,259–4,697)

Citations (with self-citations)

Ranking in main subfield (with self-citations)

Ranking in main subfield (without self-citations)

Percentile in main subfield (with self-citations)

Percentile in main subfield (without self-citations)

169 (63–486)

28,711 (11,338–61,183)

28,693 (11,312–61,180)

46 (22–71)

226 (76–730)

21,378 (7,500–48,629)

21,324 (7,535–48,751)

37 (16–61)

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2
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Comprehensive mapping of local and diaspora scientists

桌子 2. Number of scientists in each scientific subfield

希腊
20

其他
32

Unknown
0

全部的
52

国家

Scientific subfield
Accounting

Acoustics

Aerospace & Aeronautics

Agricultural Economics & 政策

Agronomy & 农业

Allergy

Analytical Chemistry

Anatomy & Morphology

Anesthesiology

Anthropology

Applied Ethics

应用数学

Applied Physics

Archaeology

Architecture

Art Practice, 历史 & 理论

Arthritis & Rheumatology

人工智能 & Image Processing

Astronomy & Astrophysics

Automobile Design & Engineering

Behavioral Science & Comparative Psychology

Biochemistry & Molecular Biology

Bioinformatics

Biomedical Engineering

Biophysics

生物技术

建筑 & Construction

商业 & 管理

Cardiovascular System & Hematology

Chemical Engineering

Chemical Physics

Quantitative Science Studies

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3

112

211

368

130

160

632

107

194

1,685

166

286

262

181

168

200

1,671

220

200

154

159

194

100

586

126

1,293

246

474

105

248

128

148

203

768

236

234

266

219

265

142

564

211

261

1,218

168

320

2,985

413

760

177

511

135

309

316

403

2,449

456

435

740

Comprehensive mapping of local and diaspora scientists

桌子 2.

(continued )

Scientific subfield
Civil Engineering

Classics

Clinical Psychology

沟通 & Media Studies

Complementary & Alternative Medicine

Computation Theory & Mathematics

Computer Hardware & Architecture

Criminology

Cultural Studies

Dairy & Animal Science

Demography

Dentistry

Dermatology & Venereal Diseases

Design Practice & 管理

Development Studies

Developmental & Child Psychology

Developmental Biology

Distributed Computing

Drama & Theater

Ecology

Econometrics

Economic Theory

经济学

教育

Electrical & Electronic Engineering

Emergency & Critical Care Medicine

Endocrinology & Metabolism

Energy

Entomology

Environmental & Occupational Health

Environmental Engineering

Quantitative Science Studies

希腊
249

其他
251

Unknown
2

全部的
502

国家

123

173

214

421

209

172

119

310

456

293

183

577

869

195

246

119

164

287

150

712

286

329

267

342

591

119

243

337

268

713

360

129

884

158

192

596

785

560

276

928

1,467

243

366

741

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Comprehensive mapping of local and diaspora scientists

桌子 2.

(continued )

Scientific subfield
Environmental Sciences

流行病学

Evolutionary Biology

实验心理学

Family Studies

Finance

Fisheries

Fluids & Plasmas

Folklore

Food Science

Forestry

Gastroenterology & Hepatology

Gender Studies

General & Internal Medicine

General Chemistry

General Clinical Medicine

General Mathematics

General Physics

General Psychology & 认知科学

遗传学 & Heredity

Geochemistry & Geophysics

Geography

Geological & Geomatics Engineering

Geology

Geriatrics

Gerontology

Health Policy & Services

历史

History of Science, 技术 & 药品

History of Social Sciences

Horticulture

Quantitative Science Studies

希腊
534

其他
163

Unknown
0

全部的
697

国家

146

159

377

661

375

102

237

131

270

272

138

159

195

132

252

231

162

151

174

167

187

121

178

254

193

354

513

124

915

611

140

399

282

270

445

460

124

742

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Comprehensive mapping of local and diaspora scientists

桌子 2.

(continued )

Scientific subfield
Human Factors

Immunology

Industrial Engineering & 自动化

Industrial Relations

信息 & Library Sciences

Information Systems

Inorganic & Nuclear Chemistry

International Relations

Languages & 语言学

Law

Legal & Forensic Medicine

Literary Studies

Logistics & Transportation

Marine Biology & Hydrobiology

Marketing

Materials

Mathematical Physics

Mechanical Engineering & Transports

Medical Informatics

Medicinal & Biomolecular Chemistry

Meteorology & Atmospheric Sciences

Microbiology

Microscopy

Mining & Metallurgy

音乐

Mycology & Parasitology

Nanoscience & Nanotechnology

Networking & Telecommunications

Neurology & Neurosurgery

核 & Particle Physics

Nuclear Medicine & Medical Imaging

Quantitative Science Studies

希腊
28

其他
77

Unknown
0

国家

706

332

143

250

173

247

390

253

184

236

306

896

1,100

742

509

575

487

390

204

128

155

280

218

149

223

367

134

953

962

623

377

全部的
105

1,194

722

351

379

114

329

331

131

671

472

262

385

529

1,267

209

2,063

1,707

1,132

953

743

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Comprehensive mapping of local and diaspora scientists

桌子 2.

(continued )

Scientific subfield
Numerical & Computational Mathematics

Nursing

Nutrition & Dietetics

Obstetrics & Reproductive Medicine

Oceanography

Oncology & Carcinogenesis

Operations Research

Ophthalmology & Optometry

Optics

Optoelectronics & Photonics

Organic Chemistry

Ornithology

Orthopedics

Otorhinolaryngology

Paleontology

Pathology

Pediatrics

Pharmacology & Pharmacy

Philosophy

Physical Chemistry

Physiology

Plant Biology & Botany

政治学 & Public Administration

Polymers

Psychiatry

Psychoanalysis

公共卫生

Rehabilitation

Religions & Theology

Respiratory System

Science Studies

Quantitative Science Studies

希腊
92

147

230

636

102

1,718

138

301

258

232

461

206

123

226

396

172

498

282

277

534

国家

其他
51

Unknown
0

126

303

868

118

308

155

319

212

348

128

113

208

161

107

222

265

139

255

全部的
143

237

356

940

145

2,589

256

609

229

578

444

810

334

194

341

604

262

659

162

505

544

226

104

790

744

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Comprehensive mapping of local and diaspora scientists

希腊
30

其他
74

Unknown
1

国家

桌子 2.

(continued )

Scientific subfield
Social Psychology

Social Sciences Methods

Social Work

Sociology

Software Engineering

Speech-Language Pathology & Audiology

Sport Sciences

Sport, Leisure & Tourism

统计数据 & 可能性

Strategic, Defence & 安全研究

Substance Abuse

Surgery

Toxicology

Tropical Medicine

Urban & Regional Planning

Urology & Nephrology

Veterinary Sciences

Virology

Zoology

331

144

160

760

114

549

164

126

104

132

493

223

154

1,269

196

117

773

237

240

全部的
105

192

103

435

119

276

259

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scientists who were not in Greece (79%, 72%, 和 59%, 分别, for these three thresh-
olds). Below the top 5%, there was more equilibrium between scientists with affiliation outside
of Greece versus in Greece, with the respective numbers being 7,842 相对 7,807 为了
顶部 20%.

3.2. Scientific Fields

如表所示 2, Greek scientists had different representation across the 174 main scien-
tific subfields of the Science Metrix classification. A number of fields of clinical medicine, 双-
ology, and agriculture/fisheries/forestry are more heavily represented for scientists who are in
希腊, while the diaspora is more prominently represented in several social and economic
sciences and some cutting-edge biomedical fields. 为了 25 subfields, scientists in Greece ex-
ceeded by more than 2:1 scientists with affiliation outside of Greece (Anatomy & Morphology,
Environmental Engineering, Respiratory System, Obstetrics & Reproductive Medicine,
Cardiovascular System & Hematology, Veterinary Sciences, Medical Informatics,
Oceanography, Microbiology, Urology & Nephrology, Gastroenterology & Hepatology,
General Clinical Medicine, Food Science, Marine Biology & Hydrobiology, Plant Biology &

Quantitative Science Studies

745

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桌子 3.

Scientists who are among the top 15 of their scientific subfield according to a composite citation indicator, excluding self-citations

国家
aus

Subfield

建筑 & Construction

Rank*
1

n in subfield**
27299

First degree

U Patras

Name of scientist
Santamouris, Mattheos

Affiliation

University of New South Wales

(新南威尔士大学) 澳大利亚

Peppas, Nicholas A.

The University of Texas at Austin

Terzopoulos, Demetri

加州大学, 天使们

Nicolaides, Kypros H.

King’s College Hospital

usa

gbr

Pharmacology & Pharmacy

Software Engineering

Obstetrics & Reproductive

药品

Papadimitriou, Christos H. Columbia University in the City of

usa

Computation Theory &

纽约

Mathematics

Ioannidis, 约翰·P. A.

Stanford University School of Medicine

Stamatakis, Alexandros

Karlsruhe Institute of Technology

Joannopoulos, 约翰

麻省理工学院

Alivisatos, A. 保罗

加州大学, 伯克利

Ntziachristos, Vasilis

Helmholtz Center Munich

German Research Center for
Environmental Health

Guibas, Leonidas J.

斯坦福大学

Buhalis, Dimitrios

Bournemouth University

Giannelis, Emmanuel

康奈尔大学

Kanatzidis, Mercouri G.

Northwestern University

Simopoulos, Artemis P.

Center for Nutrition, 遗传学

& 健康

Bertsekas, Dimitri

Arizona State University

Pavlou, 保罗

C. 时间. Bauer College of Business

Stephanopoulos, Gregory Massachusetts Institute of Technology

Nicolaou, K. C.

Rice University

Diamantopoulos,
Adamantios

Universitat Wien

Gazetas, G.

National Technical University

of Athens

usa

deu

usa

deu

usa

gbr

usa

aut

grc

General & Internal Medicine

Bioinformatics

Optoelectronics & Photonics

Nanoscience &

Nanotechnology

Nuclear Medicine &
Medical Imaging

Software Engineering

Sport, Leisure & Tourism

Polymers

Materials

Nutrition & Dietetics

Operations Research

Information Systems

生物技术

Organic Chemistry

Marketing

Strategic, Defence &
安全研究

7
4
6

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95625

21515

66792

NTUA

McGill

King’s College

16762

NTUA

107698

U Athens

18635

TU Munich

102335

UC Berkeley

75646

U Chicago

84992

Aristotle U

21515

CalTech

6295

U Aegean

81179

U Athens

180221

Aristotle U

35890

23674

16831

50679

Barnard

大学

NTUA

Rice U

NTUA

112004

U London

10516

Heriot-Watt U

17396

NTUA

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Antonarakis, Stylianos E.

Université de Genève Faculté de

che

遗传学 & Heredity

Pratsinis, Sotiris E.

苏黎世联邦理工学院

Médecine

Chrousos, George P.

National and Kapodistrian University

of Athens

che

grc

Chemical Engineering

Endocrinology &
Metabolism

Kalogirou, Soteris A.

Cyprus University of Technology

cyp

Energy

Yannakakis, Mihalis

Columbia University in the City of

usa

Computation Theory &

纽约

Avouris, Phaedon

IBM Thomas J. Watson Research Center

Lyketsos, Constantine G.

Johns Hopkins Bayview Medical Center

Argyropoulos, Dimitris S.

NC State University

Giannakis, Georgios B.

University of Minnesota Twin Cities

Davatzikos, Christos

宾夕法尼亚大学

usa

Mathematics

Applied Physics

Geriatrics

Forestry

Networking &

Telecommunications

Nuclear Medicine &
Medical Imaging

Karniadakis, George Em

Brown University

usa

应用数学

32809

U Athens

56292

69452

Aristotle U

U Athens

188556

Higher

Tech Inst

16762

NTUA

226884

Aristotle U

9246

Northwestern

24339

U London

162693

NTUA

84992

NTUA

16040

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* Rank among all scientists in the same subfield, regardless of whether they are alive or deceased. 例如, in General & Internal Medicine the top ranked scientist is Douglas Altman,
who is deceased. Also of note, the top 32 scientists who are highly ranked based on the percentile in their subfield (not shown here) 包括 23 的 32 who are top-ranked based on the
absolute threshold (顶部 15 in the subfield).

** Number of scientists in the same subfield, including both those who are alive and those who are deceased; it is not straightforward to identify how many are deceased. The count includes
those who have at least five papers (文章, reviews, or conference proceedings) indexed in Scopus and who have some papers classified in one of the 174 Science Metrix subfields.

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7
4
7

Comprehensive mapping of local and diaspora scientists

Botany, Fisheries, Sport Sciences, Environmental Sciences, Agronomy & 农业, Dairy &
Animal Science, Entomology, Ornithology, History of Science, 技术 & 药品,
Horticulture, Folklore). 反过来, 在 32 subfields, scientists outside of Greece exceeded by more
比 2: 1 scientists with affiliation in Greece (Cultural Studies, Law, Criminology, 沟通
& Media Studies, Art Practice, 历史 & 理论, Economic Theory, Automobile Design &
Engineering, Development Studies, General Chemistry, Social Work, Developmental Biology,
Philosophy, 实验心理学, History of Social Sciences, Behavioral, 科学 &
Comparative Psychology, International Relations, Psychoanalysis, Social Sciences Methods,
Aerospace & Aeronautics, Human Factors, Developmental & Child Psychology, Applied Ethics,
Anthropology, General Psychology & 认知科学, Social Psychology, Religions &
Theology, Physiology, Literary Studies, 音乐, Clinical Psychology, Optics, 历史).

3.3. Top-Cited Greek Scientists Across Different Fields

Thirty-two Greek scientists were among the top 15 of their scientific subfield based on a cita-
tion indicator excluding self-citations (桌子 3). Almost all of them (30/32, 94%) were listed by
Scopus with an affiliation outside of Greece. 的 32 科学家, information on place of birth
could be found on 28 (except for Terzopoulos, Stamatakis, Pavlou, and Argyropoulos); 三
were born in Cyprus (Nicolaides, Nicolaou, Kalogirou), three were born in the United States
(Ioannidis, Joannopoulos, Alivisatos), one was born in the United Kingdom (Lyketsos), 和
其余的 21 had been born in Greece. 的 32, 18 had received their first degree from an
institution in Greece.

4. 讨论

We have created and validated a database of scientists of Greek origin that may be helpful for
评估, 规划, and research policy purposes. It may also serve as a template for similar
efforts to be undertaken for other countries to map their scientific workforce. The iterative ap-
proach that we followed may also have special added value for countries that have sustained
heavy brain drain and/or that have a substantial scientific diaspora. The sensitivity and spec-
ificity achieved from such an approach in constructing scientist databases from different coun-
tries may vary depending on how unique first and last names are to geographic origin.

Our approach has tried to identify scientists originating from Greece regardless of their pres-
ent or past affiliations. We have also probed the sensitivity and specificity of the database
membership. The database is dependent on Scopus coverage, so scientists in fields not well
covered by Scopus may be particularly underrepresented. The database includes close to
64,000 author ID files representing scientists who have published at least five papers. 给定
that some scientists have their publications split in more than one file, the database probably
includes close to 60,000 unique scientists. Validation exercises suggest that it probably misses
very few scientists who meet the productivity eligibility criteria and who have an affiliation in a
Greek institution. 反过来, a more substantial proportion has been missed among those
who have an affiliation in an institution outside of Greece. The estimate of the missingness
in this regard varies according to different validation sets that we used. Based on scientists
working abroad who on their own initiative offered to be included in a database of Greek
科学家, about one in four scientists were missed with our approach. The percentage of miss-
ingness was higher based on a Wikipedia list of diasporeans, and even more when extending
beyond first-generation emigrants. It is unavoidable that our approach would miss Greeks who
acquire non-Greek names (upon second and subsequent generations) and for people who
change their names (例如, through marriage, by making the name less foreign-sounding in their

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new country, or other reasons) and those who have a Greek last name that was not among the
ones we searched for. Some of these individuals may still be captured if they possess a highly
Greek-specific first name among the list of first names that we screened for. 所以, 甚至
though scientists with an affiliation in Greece were a slight majority in the compiled database,
Greek origin scientists with an affiliation outside of Greece would probably be the majority if all
Greek origin scientists could have been retrieved. The total of Greek origin scientists meeting the
productivity eligibility criteria may be in the range of 80,000–100,000 (~1.00–1.25% of the
global total). 反过来, a few scientists are included in the database by failed disambiguation.
The validation process suggests that this situation is probably very uncommon.

The database reflects the large extent of general emigration from Greece as well as the massive
brain drain that the country has sustained over the years, with accelerated rates in the last decade in
conjunction with the economic crisis that hit Greece worse than almost any other highly developed
国家. We noted that the cohort of scientists with affiliation outside of Greece had on average
younger publication ages, as revealed by the year of their first paper; half of them published
their first paper in 2004 or more recently.

While citation indicators are quite high for the entire database averages, scientists with an
affiliation outside of Greece have substantially stronger citation indicators and higher rankings
in their fields compared with scientists with affiliation in Greece. The difference is more prom-
inent among top-cited scientists, 在哪里 86% of the Greek origin scientists who are in the top
0.1% of their subfield are not in Greece. 相似地, 几乎全部 (94%) of the Greek origin scien-
tists who are among the top 15 of their subfield are not in Greece. Of interest, is that the large
majority of these extremely highly cited scientists were born in Greece, and the majority also
received their first degree in Greece. This further demonstrates the power of the brain drain
过程. 同时, scientists who have remained in Greece still include large numbers
placed in the top 20% of their subfield. 因此, the local scientific workforce still has consider-
able capacity for excellence. Of note, given our search strategy, is that our database has prac-
抽搐地 100% sensitivity for Greek scientists abroad who are in the top 2% of citation impact,
while several scientists with lesser impact may have been missed.

The database includes scientists scattered across almost every scientific subfield. Scientists
with an affiliation in Greece have stronger concentrations than those with affiliations outside
of Greece in many fields of clinical medicine, several fields of biology, and agriculture/
fisheries/forestry. Greece has one of the highest rates of physicians per population in the
世界, if not the highest (country-level data on medical doctors per 10,000 population are
available at https://www.who.int/data/gho/data/indicators/indicator-details/GHO/medical
-doctors-per-10-000-population). Many of them are engaged in research, authoring or
coauthoring papers, as scientific publications are requested and appraised not only for
academic track positions, but even for regular clinical positions in the national health system.
The advantage is that these incentives create a large pool of physicians with exposure to
研究. The disadvantage is that much of this research may not be of high quality and these
authors have no lasting commitment to research. The concentration in subfields of agriculture,
fisheries, and biology is probably explained by the nature of the economy, although agricul-
ture and related fields have shrunk in latest years. 反过来, there are several other fields
where most scientists of Greek origin do not work in Greece. This pattern is particularly strong
in the social and economic sciences and some cutting-edge biomedical sciences, 例如
developmental biology.

Some limitations need to be discussed. 第一的, as we have already acknowledged, 数据-
base is still missing several Greek origin scientists, in particular among those living and

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working abroad. We encourage people to provide relevant information at www.drosatos.com
/greekscientists to bring such cases to our attention. While it is impossible to update the da-
tabase by adding one more scientist at a time, collecting information on missing individuals
may allow us to consider further optimized automated processes in the future. While this pa-
per was in peer review, and as of March 20, 2021, 13 additional names of Greek scientists
were provided to us, but seven of those were already included in the database, two had fewer
than five papers by early 2020, and only four had been missed (Anna-Bettina Haidich
[Aristotle U Thessaloniki, h = 29], Elias Franses [Purdue, h = 36], Iosif Koutagiar [Hygheia
Hospital, h = 9], and Christos Chinopoulos [Semmelweis Egyetem, h = 31]).

第二, the constructed database was restricted to scientists with at least five full papers. 在
the entire Scopus database, roughly four-fifths of author ID files have fewer than five papers.
Some of the author ID files with sparse papers may be split-off fragments of the publication
corpus of authors represented by some larger file. 尽管如此, by extrapolation, the total
number of Greek authors who have published at least one paper may be in the range of
250,000–500,000. The overwhelming majority of authors of 1–4 papers are not major contrib-
utors or leaders in the scientific enterprise. 然而, many young scientists in this group may
become major contributors or leaders in the future. 所以, follow-up updates would be
useful to perform.

第三, 错误 (either splitting the same author into two or more author ID files or including
some papers by two or more authors in the same file) and inaccuracies in affiliations are possible.
Authors who recognize errors should contact Scopus directly to make these corrections in
Scopus itself, so that they may be carried over in our database with any potential future updates.
The entire Scopus database currently has overall 98.1% precision (proportion of papers in an
author ID file that belong to the author) 和 94.4% 记起 (proportion of papers of an author
included in the largest profile) (Baas et al., 2020). Precision and recall may be even better for
Greek-name authors, because Greek names are more rare and thus more specific than those of
most other origins (例如, the disambiguation challenges for “Liu Wang” are greater than for
“Yiannis Triantafyllou”). 我们发现 8.5% of the authors in the database to have a split profile
和, given that even when one profile carries the large majority of the author’s papers, 记起
probably substantially exceeds 94.4% for our database.

第四, allocation of fields and subfields follows a well-established classification, but some
scientists may have an almost equal number of papers in two or more fields, and the most
common one may not fully capture their expertise. Their ranking would have been different
had they been classified in a different subfield. 而且, even within the same subfield, 那里
are granular subsections with different citation densities.

第五, allocation of affiliation and country is performed automatically by Scopus picking just
one affiliation from the most recent papers of each author. Some authors have multiple current
affiliations, and some may have changed their affiliation recently. 再次, we encourage au-
thors who want to change their listed affiliation to communicate directly with Scopus.
Misclassification may affect some authors in their classification as being in Greece versus out-
side of Greece. 然而, it would have been extremely difficult to curate affiliations manually
and it is impossible for an outsider to know which of many affiliations an author may prefer.

Sixth, our database does not automatically distinguish between first, 第二, 及更高
generation emigrants. If deemed desirable, this would have to be done manually, and it
may have implications for policy (not losing scientists versus attracting scientists). 第二
and higher generation emigrants are not necessarily a sign of brain drain, as they did not
emigrate themselves.

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最后, all citation metrics have limitations and they should be used with caution and not
as absolute indicators (希克斯, Wouters et al., 2015; Waltman, 2016; 王, Veugelers, &
Stephan, 2017). We made no effort to assess the quality of the published works. Some authors
may rank high, but may have other reasons for concern (例如, retracted papers, or implausibly
high self-citation metrics or evidence for citation farms). These need to be carefully scrutinized
on a case-by-case basis.

Acknowledging these caveats, the compiled database offers a tool that may be useful for both
research and policy purposes. For a country that is trying to recover from a lengthy economic crisis
and a superimposed crisis from the recent COVID-19 pandemic, realization of its scientific poten-
提尔, deceleration and reversal of the brain drain and informed decision-making in the interface of
science and society may offer substantial added value. The brain drain and diaspora do not need to
have negative consequences for the home country; mapping of the scientific workforce and dias-
pora may help to maximize positive impact (Davenport, 2004; 瓦格纳 & Jonkers, 2017).

We also hope that the iterative approach used here may be applied also to map the scientific
workforce and scientific diaspora of other countries/nations as well. Scopus data can readily
identify scientists with affiliation in a given country. In the case of Greece, where few scientists
immigrate to from other countries, almost all scientists with affiliation in Greece have Greek
名字. This would not be true for countries that attract many scientists from other countries,
but usually it is more important to map the entire scientific workforce rather than just native sci-
entists. The ability to map the diaspora of different countries depends on whether there are many
first and last names that are country-specific. Specificity may vary substantially across countries
and careful validation and cross-checking procedures should be applied accordingly.

作者贡献

约翰·P. A. Ioannidis: 概念化, 形式分析, 调查, 方法, 项目
行政, 监督, 验证, 可视化, Writing—Original draft, Writing—
审查 & 编辑. Chara Koutsioumpa: 数据管理, 调查, 验证, Writing—
审查 & 编辑. Angeliki Vakka: 数据管理, 调查, 验证, Writing—Review
& 编辑. Georgios Agoranos: 数据管理, 调查, 验证, Writing—Review &
编辑. Chrysanthi Mantsiou: 数据管理, 调查, 验证, Writing—Review &
编辑. Maria Kyriaki Drekolia: 数据管理, 调查, 验证, Writing—Review
& 编辑. Nikos Avramidis: 数据管理, 调查, 验证, Writing—Review & 编辑.
Despina G. Contopoulos-Ioannidis: 数据管理, 形式分析, 调查, 验证,
可视化, Writing—Review & 编辑. Konstantinos Drosatos: 概念化, Data cura-
的, 调查, 项目管理, 监督, 验证, Writing—Review & 编辑.
Jeroen Baas: 概念化, 数据管理, 形式分析, 调查, 方法,
资源, 软件, 验证, Writing—Review & 编辑.

COMPETING INTERESTS

Jeroen Baas is an employee of Elsevier, which runs Scopus.

资金信息

No funding has been received for this research.

DATA AVAILABILITY

All the data on the 63,951 scientists are available in Mendeley at https://doi.org/10.17632
/zbyctscmbn.1.

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