Open Data in Higher Education: Definitions, Trends, and Challenges

This record contains the full report Open Data in Higher Education: Definitions, Trends, and Challenges (PDF) and the dataset underpinning the narrative literature review on which the analytical framework is based.

The report critically examines the evolving role of open data in higher education, addressing conceptual foundations, emerging trends, institutional practices, and ethical implications. It explores two major traditions of open data—open government data and open research/educational data—and analyses their intersection within universities. Drawing on a narrative literature review conducted through a structured database search (SCOPUS, Web of Science, EBSCO) and forward snowball sampling until theoretical saturation, the study identifies key conceptual nodes and thematic trends. The final corpus includes peer-reviewed articles, reports, grey literature, and relevant institutional resources.

Beyond conceptual clarification, the report synthesizes international case studies and institutional practices, highlighting applications of open data for governance, learning analytics, predictive modelling, teaching innovation, and digital transformation. Particular attention is paid to data literacy, interoperability standards, ontologies, and FAIR principles. The analysis also addresses persistent challenges, including data quality, standardization, privacy, surveillance concerns, commercialization risks, and ethical governance.

The report concludes with institutional, policy, and pedagogical recommendations for fostering responsible and human-centred open data ecosystems in higher education. It advocates for integrating open data into teaching and learning practices while strengthening ethical frameworks and digital competencies.

The accompanying dataset documents the literature selection process, screening workflow, and bibliographic corpus used to ground the review and thematic analysis.