Emergence and evolution of data literacy: Insights from a bibliometric study

Abstract

This study aims to contribute to the pertinent body of knowledge by examining the field of data literacy (DL) to better understand its trends and evolution, thematic clusters, relevant studies and the most productive authors and journals. The analysis of scientific literature indexed by Web of Science from 1980 to 2023 ( n = 1704 items) combined co-occurrence (using VOSviewer) and co-citation (using CiteSpace) techniques based on the words in the title and abstract, as well as the keywords, authors and journals. There is evidence of four main trend topics (Data Literacy, Statistical Literacy, Data-based assessment and e-society) and six thematic clusters (Data Literacy, Statistical Literacy, Quantitative Literacy, Big Data, Data Science and Quantitative Skills). With DL emerging in 2011, the research initially focused on both quantitative and statistical literacy, and later (2012–2016) shifted toward applying statistical literacy to various disciplines. Since 2018, the use of data has led to the emergence of fields like big data and data science, resulting in progress being made in data literacy. The combination of the two analysis techniques offers complementary perspectives: co-word analysis reveals fields of application, and co-citation analysis shows the internal evolution of the discipline. This study evidences a significant increase in publications on DL, indicating its expansion to several disciplines and a promising, yet uncertain, future.