Exploration of Data Literacy Research Using a Network of Cluster Mapping Approach

Data literacy is essential for academics, researchers, and emerging data management professionals. The quality of scientific productivity is determined by the underlying knowledge of data collection or generation during the research process, which impacts data literacy. This research aims to investigate the current state of data literacy by examining bibliographic data with no constraints on themes or time periods. The generation of digital data has increased, and storage capacity and accessing devices have improved in the upgraded version, but where is the proper education for dealing with data? The research team must focus on data literacy to address all of these challenges. This paper will provide an overview and groundwork for data literacy based on previously published literature. This study used scholarly literature from Elsevier’s Scopus database to conduct a knowledge network and mapping analysis. The global contributors and significant countries are mapped with institutions and authors. Primary areas are identified using a keyword co-occurrence network. Influential research papers and journals were identified using Document Co-Citation Analysis (DCA) and Journal Co-Citation Analysis (JCA). This paper highlights the insightful features of data literacy by conducting scientometric analysis with CiteSpace and VOSviewer. It reveals that researchers lack basic data management skills and end with complicated and ambiguous research findings. Researchers must emphasize the importance and fundamentals of data literacy skills and some metrics that may be used to assess the acquired skills.