RESUMEN
In this article, we present the dataset of mills from 1880 and 1920s-1930s in the area of the former Galicia (78,500 km2), now in Ukraine and Poland. The data was obtained as a result of manual vectorisation from 162 map sheets at scales of 1:115,200 and 1:100,000, according to the map legends. We found 4022 mill locations for 1880 and 3588 for the 1920s-1930s. We present them as vector points in shapefile, GML, GeoJSON, KML formats with attributes for seven types of mills for 1880 and ten types of mills for 1920s-1930s, and mills counted in a 10 km grid. The data can be used in economic, demographic and environmental reconstructions, e.g. to estimate historical anthropopressure related to settlement, agriculture and forestry. Mills are often associated with river structures such as floodgates, dams, and millraces and therefore they are a good example of human interference in river ecosystems. They can also be one criteria for identifying areas where the local population used traditional environmental knowledge. It can be useful for a contemporary assessment of the environment's suitability for devices using renewable energy sources. Finally, the data on the remains of former mills is suitable for the protection of cultural heritage sites that are technical monuments related to traditional food processing and industry.
RESUMEN
Scientists from many disciplines need historical administrative boundaries in order to analyse socio-economic data in space and time. In this paper, we present a set of historical data consisting of administrative unit boundaries and exemplary socio-economic attributes for Austrian Silesia, an historical region located in modern Czechia and Poland. The dataset covers nearly 700 administrative unit boundaries on the level of cadastral or political communes and their subparts and was acquired through manual vectorisation of historical maps (1:28,800) from the period 1837-1841. The local-level units can be easily joined into higher-level divisions such as court or political districts for the period 1837-1910. The data can then be combined with statistical data collected approximately every 10 years for a similar period. Within the quality assessment, the relations between cartographic and census data and their credibility are analysed. The present dataset provides many possibilities for joining a wide range of historical statistical data to better understand various demographic and economic processes based on advanced analyses, e.g., by using GIS.