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Research Details
Data, Measurement, and Empirical Methods in the Science of Science, Nature Human Behavior
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.
Type
Article
Author(s)
Lu Liu, Benjamin F. Jones, Brian Uzzi, Dashun Wang
Date Published
2023
Citations
Liu, Lu, Benjamin F. Jones, Brian Uzzi, and Dashun Wang. 2023. Data, Measurement, and Empirical Methods in the Science of Science. Nature Human Behavior.: 1046–1058.