Purpose Data literacy is becoming widely accepted by professionals and laypeople alike. It has a long-standing reputation for usefulness and can therefore be considered an emerging life skill. It is also one of the foundations of artificial intelligence (AI) literacy. Therefore, our aim is to present and appreciate their nature and evolution by reflecting on them. Design/methodology/approach Based on a literature review of narrative sources, this paper provides a systematic overview of a selection of important literature on data for research and for citizenship. Findings Among other considerations, the interest in data literacy shows that data are a valuable key resource, so this paper reflects on the main efforts in this area. This means that conclusions can be drawn from both the theoretical development of DL and the evidence of a remarkable practical development. The results confirm that DL is a growing field with great relevance and that it affects several versions of existing datasets. As shown above, it not only plays an essential role but also advances the interrelationship between different literacies. Originality/value Our exploration of the characteristics of the data-driven age is based on an overview of diverse data literacies and related approaches, which are closely linked to other types of literacy. Our findings are summarised in a table that compares the main characteristics of the different categories of data and AI literacy, offering a broader perspective.
Varga et al. (2025) studied this question.