Knowledge mapping of data literacy: A bibliometric study using visual analysis

Abstract

Presenting a comprehensive knowledge map tailored for researchers within the domain of data literacy, facilitating swift comprehension of pivotal concepts, evolving trends, and emerging research frontiers. Employing advanced bibliometric analysis in conjunction with cutting-edge software tools including CiteSpace, Ucinet, and gCLUTO, the study meticulously examines a corpus of 1250 scholarly documents sourced from both the Web of Science (WoS) and Scopus datasets spanning the period from 2004 to 2023. The resultant scientific knowledge map illuminates the landscape of data literacy research, synthesizing a thorough and methodical literature review that seamlessly integrates qualitative and quantitative methodologies. Findings notably indicate a conspicuous uptick in scholarly interest surrounding data literacy post-2015, with a quantified exponential growth pattern depicted by the function y = 0.8777e 0.3384x . Key research focal points in data literacy foreground domains such as data management and utilization, decision-driven research in data literacy, pedagogical strategies for cultivating data literacy in educators and students, critical data literacy considerations, artificial intelligence, media literacy, among others. Future research trajectories appear poised toward advancing both the training methodologies and practical applications of media data literacy and critical data literacy within the context of information proliferation, particularly emphasizing educational settings.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 2 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.