A Data Literacy Competence Model for Higher Education and Research
Martina M. Echtenbruck, Simone Fühles-Ubach, Boris Naujoks, Elisabeth Kaliva
TL;DR
The paper addresses the lack of a unified definition for data literacy by developing the DaLI Competence Model, a seven-area framework for higher education and research. It synthesizes existing data-literacy frameworks and grounds competencies in a data lifecycle tailored to academic settings, with strong emphasis on ethics, legality, and open data. The model provides a structured basis for curriculum design, teaching, and assessment, while enabling cross-disciplinary adoption and long-term data reuse. Future work includes implementing modules, developing assessments, and integrating considerations for AI to keep the framework current in an evolving data landscape.
Abstract
In an increasingly data-driven world, the ability to understand, interpret, and use data - data literacy - is emerging as a critical competence across all academic disciplines. The Data Literacy Initiative (DaLI) at TH Köln addresses this need by developing a comprehensive competence model for promoting data literacy in higher education. Based on interdisciplinary collaboration and empirical research, the DaLI model defines seven overarching competence areas: "Establish Data Culture", "Provide Data", "Manage Data", "Analyze Data", "Evaluate Data", "Interpret Data", and "Publish Data". Each area is further detailed by specific competence dimensions and progression levels, providing a structured framework for curriculum design, teaching, and assessment. Intended for use across disciplines, the model supports the strategic integration of data literacy into university programs. By providing a common language and orientation for educators and institutions, the DaLI model contributes to the broader goal of preparing students to navigate and shape a data-informed society.
