A dataset of publication records for Nobel laureates

Jichao Li, Yian Yin, Santo Fortunato, Dashun Wang

Research output: Contribution to journalArticle

Abstract

A central question in the science of science concerns how to develop a quantitative understanding of the evolution and impact of individual careers. Over the course of history, a relatively small fraction of individuals have made disproportionate, profound, and lasting impacts on science and society. Despite a long-standing interest in the careers of scientific elites across diverse disciplines, it remains difficult to collect large-scale career histories that could serve as training sets for systematic empirical and theoretical studies. Here, by combining unstructured data collected from CVs, university websites, and Wikipedia, together with the publication and citation database from Microsoft Academic Graph (MAG), we reconstructed publication histories of nearly all Nobel prize winners from the past century, through both manual curation and algorithmic disambiguation procedures. Data validation shows that the collected dataset presents among the most comprehensive collection of publication records for Nobel laureates currently available. As our quantitative understanding of science deepens, this dataset is expected to have increasing value. It will not only allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may also help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs.

Original languageEnglish (US)
Number of pages1
JournalScientific Data
Volume6
Issue number1
DOIs
StatePublished - Apr 18 2019

Fingerprint

Websites
Productivity
career
Wikipedia
science
Citations
Probe
history
creativity
website
elite
productivity
Graph in graph theory
History
university
Values
Training
Creativity
Universities
Collaboration

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

Cite this

Li, Jichao ; Yin, Yian ; Fortunato, Santo ; Wang, Dashun. / A dataset of publication records for Nobel laureates. In: Scientific Data. 2019 ; Vol. 6, No. 1.
@article{246835730d824a87abfa7ba2920da4b1,
title = "A dataset of publication records for Nobel laureates",
abstract = "A central question in the science of science concerns how to develop a quantitative understanding of the evolution and impact of individual careers. Over the course of history, a relatively small fraction of individuals have made disproportionate, profound, and lasting impacts on science and society. Despite a long-standing interest in the careers of scientific elites across diverse disciplines, it remains difficult to collect large-scale career histories that could serve as training sets for systematic empirical and theoretical studies. Here, by combining unstructured data collected from CVs, university websites, and Wikipedia, together with the publication and citation database from Microsoft Academic Graph (MAG), we reconstructed publication histories of nearly all Nobel prize winners from the past century, through both manual curation and algorithmic disambiguation procedures. Data validation shows that the collected dataset presents among the most comprehensive collection of publication records for Nobel laureates currently available. As our quantitative understanding of science deepens, this dataset is expected to have increasing value. It will not only allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may also help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs.",
author = "Jichao Li and Yian Yin and Santo Fortunato and Dashun Wang",
year = "2019",
month = "4",
day = "18",
doi = "10.1038/s41597-019-0033-6",
language = "English (US)",
volume = "6",
journal = "Scientific data",
issn = "2052-4463",
publisher = "Nature Publishing Group",
number = "1",

}

A dataset of publication records for Nobel laureates. / Li, Jichao; Yin, Yian; Fortunato, Santo; Wang, Dashun.

In: Scientific Data, Vol. 6, No. 1, 18.04.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A dataset of publication records for Nobel laureates

AU - Li, Jichao

AU - Yin, Yian

AU - Fortunato, Santo

AU - Wang, Dashun

PY - 2019/4/18

Y1 - 2019/4/18

N2 - A central question in the science of science concerns how to develop a quantitative understanding of the evolution and impact of individual careers. Over the course of history, a relatively small fraction of individuals have made disproportionate, profound, and lasting impacts on science and society. Despite a long-standing interest in the careers of scientific elites across diverse disciplines, it remains difficult to collect large-scale career histories that could serve as training sets for systematic empirical and theoretical studies. Here, by combining unstructured data collected from CVs, university websites, and Wikipedia, together with the publication and citation database from Microsoft Academic Graph (MAG), we reconstructed publication histories of nearly all Nobel prize winners from the past century, through both manual curation and algorithmic disambiguation procedures. Data validation shows that the collected dataset presents among the most comprehensive collection of publication records for Nobel laureates currently available. As our quantitative understanding of science deepens, this dataset is expected to have increasing value. It will not only allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may also help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs.

AB - A central question in the science of science concerns how to develop a quantitative understanding of the evolution and impact of individual careers. Over the course of history, a relatively small fraction of individuals have made disproportionate, profound, and lasting impacts on science and society. Despite a long-standing interest in the careers of scientific elites across diverse disciplines, it remains difficult to collect large-scale career histories that could serve as training sets for systematic empirical and theoretical studies. Here, by combining unstructured data collected from CVs, university websites, and Wikipedia, together with the publication and citation database from Microsoft Academic Graph (MAG), we reconstructed publication histories of nearly all Nobel prize winners from the past century, through both manual curation and algorithmic disambiguation procedures. Data validation shows that the collected dataset presents among the most comprehensive collection of publication records for Nobel laureates currently available. As our quantitative understanding of science deepens, this dataset is expected to have increasing value. It will not only allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may also help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs.

UR - http://www.scopus.com/inward/record.url?scp=85065021203&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85065021203&partnerID=8YFLogxK

U2 - 10.1038/s41597-019-0033-6

DO - 10.1038/s41597-019-0033-6

M3 - Article

VL - 6

JO - Scientific data

JF - Scientific data

SN - 2052-4463

IS - 1

ER -