Longitudinal data are widely recognised as a key resource for studying how educational inequalities emerge, evolve, and persist over time. However, despite growing interest in longitudinal approaches, researchers and policymakers often lack a clear overview of which longitudinal education datasets exist, how they are structured, and to what extent they can be used to analyse inequality dynamics across countries. This paper addresses this gap by presenting the results of a large-scale empirical mapping of longitudinal datasets on student learning outcomes in Europe. The paper draws on the mapping activity conducted within the Horizon Europe project LINEup (Longitudinal Data for INequalities in Education), which identified, documented, and analysed longitudinal datasets covering primary and secondary education (ISCED 1–3) across 32 European countries. The mapping resulted in 103 validated longitudinal datasets from administrative sources, surveys, and hybrid designs, providing the first cross-country overview of educational longitudinal data. Methodologically, the mapping followed a structured, multi-step strategy combining evidence from a systematic literature review, an expert questionnaire involving over 300 stakeholders across 28 countries, and extensive desk research. Datasets were assessed against shared inclusion criteria and documented using a standardised metadata template capturing longitudinal design, temporal span, learning outcomes, contextual variables, geographical scope, and data accessibility. A multi-level validation process ensured consistency and comparability across national contexts. The results highlight substantial cross-country variation in the availability, structure, and quality of included datasets. National-level datasets offer broader coverage and longer observation periods, often supported by established administrative infrastructures, while sub-national and project-based datasets provide richer contextual information but face limitations in continuity, representativeness, and access. Across countries, gaps remain in the availability of school- and teacher-level variables and in the transparency of access conditions. Access to microdata is uneven, with legal, technical, and institutional barriers limiting secondary use. Rather than advancing a theoretical interpretation of these differences, the paper focuses on the descriptive and methodological contribution of systematic mapping. It shows how mapping makes visible both existing data resources and the constraints when designing longitudinal and comparative studies. By organising heterogeneous datasets within a shared analytical framework, the mapping supports informed data selection and identifies priorities for future data development. Systematic mapping is a necessary precondition for strengthening the use of longitudinal evidence in education research and policy. By clarifying the current landscape of longitudinal education data in Europe, the mapping contributes to more transparent, cumulative, and methodologically grounded research on educational inequalities.

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