Ospitaletto District Heating Expansion – Building Heat Demand and Network Dataset


FAIR Overall Score

73%

Abstract

This dataset provides georeferenced building-level annual heating demand estimates and district heating network geometry for the municipality of Ospitaletto (Brescia, Lombardy, Italy), developed to assess expansion opportunities for an existing 5th Generation District Heating (5GDHC) network. The building heat demand layer (Ospitaletto_heat.gpkg) covers 1,957 buildings with 17 attributes including footprint area, building height and volume, S/V ratio, functional use (residential/non-residential), INSPIRE-based typological class (SFH, s-MFH, l-MFH), estimated annual heating demand (MWh/year), distance to the DH network, and priority selection flags under two criteria. The DH network layer (DH_ospitaletto_network.gpkg) contains 21 pipe segments of the existing network. Both layers use the EPSG:3035 coordinate reference system. Heating demand was estimated through a data-fusion methodology combining building geometry (OpenStreetMap, cadastral data), climate inputs (Heating Degree Days, Southern Continental zone), energy consumption density benchmarks (INSPIRE for residential, Hotmaps for non-residential), and available metered consumption data for calibration. Network expansion priorities were assessed using two criteria: Criterion A selects buildings by maximizing the ratio of annual demand to distance from the network (kWh/y/m); Criterion B applies a 250 m buffer around the existing network and filters by minimum demand threshold (100 kWh/y). Produced within the MODERATE project (Horizon Europe Grant Agreement No. 101069834).

Citation

Landing page / DOI

Creative Commons Attribution 4.0 International

Contact for metadata

Eurac Research


FAIR Overall Score: 73%

Principle Score Earned Level
Findable 57% 4 of 7 moderate
Accessible 100% 7 of 7 advanced
Interoperable 67% 4 of 6 moderate
Reusable 67% 4 of 6 moderate

Assessed 2026-07-22 (metrics 0.8)

Evaluated by F-UJI web service: Anusuriya Devaraju, & Robert Huber. (2020). F-UJI - An Automated FAIR Data Assessment Tool. Zenodo. https://doi.org/10.5281/zenodo.6361400


No docs sources are available.