Resumen: The Covid-19 pandemic has highlighted the need for governments and health administrations at all levels to have an open data registry that facilitates decision-making in the planning and management of health resources and provides information to citizens on the evolution of the epidemic. The concept of “open data” includes the possibility of reutilization by third parties. Space and time are basic dimensions used to structure and interpret the data of the variables that refer to the health status of the people themselves. Hence, the main objective of this study is to evaluate whether the autonomous communities’ data files regarding Covid-19 are reusable to analyze the evolution of the disease in basic spatial and temporal analysis units at the regional and national levels. To this end, open data files containing the number of diagnosed cases of Covid-19 distributed in basic health or administrative spatial units and temporal units were selected from the portals of the Spanish autonomous communities. The presence of infection-related, demographic, and temporal variables, as well as the download format and metadata, were mainly evaluated. Whether the structure of the files was homogeneous and adequate for the application of spatial analysis techniques was also analyzed. The results reveal a lack of standardization in the collection of data in both spatial and temporal units and an absence of, or ambiguity in, the meaning of the variables owing to a lack of metadata. An inadequate structure was also found in the files of seven autonomous communities, which would require subsequent processing of the data to enable their reuse and the application of analysis and spatial modeling techniques, both when carrying out global analyses and when comparing patterns of evolution between different regions. Idioma: Inglés DOI: 10.3145/epi.2022.jul.10 Año: 2022 Publicado en: Profesional de la Informacion 31, 4 (2022), e310410 [14 pp.] ISSN: 1386-6710 Factor impacto JCR: 4.2 (2022) Categ. JCR: COMMUNICATION rank: 19 / 96 = 0.198 (2022) - Q1 - T1 Categ. JCR: INFORMATION SCIENCE & LIBRARY SCIENCE rank: 27 / 84 = 0.321 (2022) - Q2 - T1 Factor impacto CITESCORE: 6.1 - Computer Science (Q1) - Social Sciences (Q1)