Data, measurement and empirical methods in the science of science

Lu Liu, Benjamin F. Jones, Brian Uzzi, Dashun Wang*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

The advent of large-scale datasets that trace the workings of science has encouraged researchers from many different disciplinary backgrounds to turn scientific methods into science itself, cultivating a rapidly expanding ‘science of science’. This Review considers this growing, multidisciplinary literature through the lens of data, measurement and empirical methods. We discuss the purposes, strengths and limitations of major empirical approaches, seeking to increase understanding of the field’s diverse methodologies and expand researchers’ toolkits. Overall, new empirical developments provide enormous capacity to test traditional beliefs and conceptual frameworks about science, discover factors associated with scientific productivity, predict scientific outcomes and design policies that facilitate scientific progress.

Original languageEnglish (US)
Pages (from-to)1046-1058
Number of pages13
JournalNature human behaviour
Volume7
Issue number7
DOIs
StatePublished - Jul 2023

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Social Psychology
  • Behavioral Neuroscience

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