Reproducible science of science at scale: pySciSci

Alexander J. Gates, Albert László Barabási

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

Science of science (SciSci) is a growing field encompassing diverse interdisciplinary research programs that study the processes underlying science. The field has benefited greatly from access to massive digital databases containing the products of scientific discourse—including publications, journals, patents, books, conference proceedings, and grants. The subsequent proliferation of mathematical models and computational techniques for quantifying the dynamics of innovation and success in science has made it difficult to disentangle universal scientific processes from those dependent on specific databases, data-processing decisions, field practices, etc. Here we present pySciSci, a freely available and easily adaptable package for the analysis of large-scale bibliometric data. The pySciSci package standardizes access to many of the most common data sets in SciSci and provides efficient implementations of common and advanced analytical techniques.

Original languageEnglish
Pages (from-to)700-710
Number of pages11
JournalQuantitative Science Studies
Volume4
Issue number3
DOIs
StatePublished - 8 Dec 2023
Externally publishedYes

Keywords

  • bibliometric data
  • citation networks
  • code
  • research assessment
  • science of science
  • scientometrics

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