Screening Rural Data Sources D3.1.

McCallum, I. ORCID: https://orcid.org/0000-0002-5812-9988, Hofer, M. ORCID: https://orcid.org/0000-0002-2867-8943, Laso Bayas, J.C. ORCID: https://orcid.org/0000-0003-2844-3842, Kull, V, Vihinen, A., Ysebaert, R., Marianne, G., Giraud, T., Viry, M., Lampert, N., Voepel, H., Steele, J., Sorichetta, A., Tapia, C., Cuadrado, A., Miller, D., Hopkins, J., Farinelli, V., Ulman, M., Simek, P., et al. (2023). Screening Rural Data Sources D3.1. GRANULAR 10.5281/zenodo.10807437.

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Abstract

This document presents an initial screening of datasets that are relevant to capture rural diversity and to create novel indicators for rural areas. Following a semi-structured format of discovery and evaluation, we have documented 90 different datasets to date which are either already used to characterise rural areas, or could underpin novel indicators. In addition to identifying the datasets themselves and their locations, we provide a suite of associated meta-data. Evaluating the findings of this effort, we demonstrate that the majority of the datasets identified have regional to global coverage, have Local Administrative Unit to gridded (10m - 10km) granularity, are provided annually, are free and open and of moderate relevance in terms of indicator generation for rural areas. With the completion of this deliverable, exploration can begin on the development of the next generation of rural indicators.

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