As algorithmic decision-making and data collection become pervasive within higher education, how can educators make sense of the systems that shape life and learning in the 21st century? Through a systematic review of the literature, the paper investigates the gaps in the literature, which prevent the formulation of potential pathways and principles on which educators’ data literacy can - and should - be developed and fostered. The analysis of 137 papers through the methods of classification under relevant categories, and key words mapping, showed that there is little attention on HE teachers, and most approaches to educators’ data literacy address management and technical abilities for data processing, with less concern on critical, ethical and personal approaches to datafication in education. The present dataset shows the full list of articles analysed. The dataset, and ods file, is composed by the following sheets: Codebook List of articles extracted from SCOPUS List of articles extracted from WOS List of articles extracted from ERIC List of articles extracted from DOAJ Interrater Agreement PRISMA workflow Analysis - First Level (classification of 137 articles selected) Analysis - Second Level (List of articles relating faculty development) Supplementary tables (counting articles in relation to the categories of analysis). As for the Keywords' Map, a second file .csv displays the text over which basis was performed the keyword maps analysis. A .txt file shows notes relating the analysis procedures using the software VOS-Viewer http://www.vosviewer.com/

This research has been parcially funded by the Project "Professional learning ecologies for Digital Scholarship: Supporting the Modernisation of Higher Education through Professionalism" , Spanish Ministry of Economy and Competitiveness, Programme "Ramón y Cajal" RYC-2016-19589. The authors wish to thank the colleagues of Edul@b for the insightful discussions about the classification adopted in the codebook.