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.

Scientific elite revisited: patterns of productivity, collaboration, authorship and impact

“…To test this hypothesis, in this revision we have acquired a novel dataset that captures funding records across all funding agencies world-wide, linked with individual investigators and resulting publications [43][44][45][46][47] . To the best of our knowledge, it is the most comprehensive research grants database to date 48 , ideal to test this hypothesis.…”

Work honored by Nobel prizes clusters heavily in a few scientific fields

“…We preferred to use more objective bibliometric criteria of impact to select one paper for each laureate when there were several contesters, so as to avoid potential subjectivity. Regardless, the papers that we selected match substantially the corpus of papers selected by other authors [13,14]. Moreover, we also performed analyses focusing on the entire publication corpus of each laureate and this evaluation gave a similar overall picture, since most laureates (like most other scientists) largely focus their work in a particular single discipline.…”

“…A different empirical study [12] that tried to evaluate which authors are considered the ones deserving more credit in papers that led to Nobel recognitions selected papers with a different approach. Another group of scientists [13,14] used their own rules to arrive at a set of Nobel-related papers. These different selections largely pertain to the same domains as those papers that we selected.…”

“…These different selections largely pertain to the same domains as those papers that we selected. For example, 97 of the 144 papers that we selected overlap with the Li et al selection [13,14] and the others are mostly in similar domains as those selected by Li et al To take this a step further, we also identified all the 40,819 Scopus-indexed publications representing the career-long output of all the scientists awarded a Nobel prize in Physics, Chemistry, or Medicine/Physiology in 1995-2017. These 40,819 papers are mapped in Fig 1E and they still show strong clustering into the same, few scientific fields.…”

“…The Nobel prize is undoubtedly the most visible, influential, and coveted award across science. Nobel laureates represent a readily demarcated and most illustrious cohort of exceptional scientists, and data on their work have been repeatedly used [1][2][3][4][5][6][7][8][9][10][11][12][13][14] to assess aspects of citation impact, perception of rewards, credit allocation, paradigm shifts, and networking in science. Much can be learned by studying this influential cohort.…”