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.

Highlights

  • Scientific elites have attracted ensuing interest from a wide range of discipli nes[17,19,20,21,22,27,28,29,30,31,32,33,34,35,36,37,38], spanning across sociology, economics, psychology, and physics, most quantitative analyses have focused on the prize-winning work alone, exploring the link between age and creativity[19,20], and allocation of credits and recognition[27,30,32]

  • Such studies would deepen our understanding of the factors driving exceptional scientific careers, helping us answer the broad question of what makes great scientists great

  • We built an open-access dataset on publication records for Nobel laureates in Physics, Chemistry, and Medicine, which is available at Harvard Dataverse[43]

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Summary

OPEN A dataset of publication records for Data Descriptor Nobel laureates

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. 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 most 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 allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs

Background & Summary
Home Page
Methods
Matched Nobel lecture paper in MAG dataset
Name disambiguation procedure
Manually checkup
Format String Integer String Integer String Integer Integer String
Format Integer String Integer String Integer Integer String String String String
Physics Chemistry
Findings
Additional Information
Full Text
Published version (Free)

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