Spatial high-resolution socio-energetic data for municipal energy system analyses

• Published in: Scientific data Vol. 6; no. 1; pp. 1 - 6
• Main Authors: Weinand, Jann M., McKenna, Russell, Mainzer, Kai
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 30.10.2019; Nature Publishing Group
• Subjects: 639/4077/2790; 639/4077/909/4083; 639/4077/909/4101/4096; 639/4077/909/4110; 706/4066/4068; Data Descriptor; Datasets; Humanities and Social Sciences; multidisciplinary; Population density; Science; Science (multidisciplinary); Typology; Wind power
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-019-0233-0

In the context of the energy transition, municipalities are increasingly attempting to exploit renewable energies. Socio-energetic data are required as input for municipal energy system analyses. This Data Descriptor provides a compilation of 40 indicators for all 11,131 German municipalities. In addition to census data such as population density, mobility data such as the number of vehicles and data on the potential of renewables such as wind energy are included. Most of the data set also contains public data, the allocation of which to municipalities was an extensive task. The data set can support in addressing a wide range of energy-related research challenges. A municipality typology has already been developed with the data, and the resulting municipality grouping is also included in the data set. Measurement(s) Demographic Data • vehicle • renewable energy Technology Type(s) digital curation Sample Characteristic - Environment city Sample Characteristic - Location Germany Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.9933890