The evolution of data science and big data research: A bibliometric analysis: A bibliometric analysis

Research output: Contribution to journalArticlepeer-review


In this study the evolution of Big Data (BD) and Data Science (DS) literatures and the relationship between the two are analyzed by bibliometric indicators that help establish the course taken by publications on these research areas before and after forming concepts. We observe a surge in BD publications along a gradual increase in DS publications. Interestingly, a new publications course emerges combining the BD and DS concepts. We evaluate the three literature streams using various bibliometric indicators including research areas and their origin, central journals, the countries producing and funding research and startup organizations, citation dynamics, dispersion and author commitment. We find that BD and DS have differing academic origin and different leading publications. Of the two terms, BD is more salient, possibly catalyzed by the strong acceptance of the pre-coordinated term by the research community, intensive citation activity, and also, we observe, by generous funding from Chinese sources. Overall, DS literature serves as a theory-base for BD publications.
Original languageEnglish
Pages (from-to)1563-1581
Number of pages19
Issue number3
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).


  • Bibliometric analysis
  • Big Data
  • Data Science
  • Evolution
  • Relationship

ASJC Scopus subject areas

  • General Social Sciences
  • Computer Science Applications
  • Library and Information Sciences


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