Enhancing Sustainability Through Quality Controlled Energy Data: The Horizon 2020 EnerMaps Project

Simon Pezzutto, Dario Bottino-Leone () and Eric John Wilczynski
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Simon Pezzutto: Institute for Renewable Energy, European Academy of Bolzano (EURAC Research), Viale Druso 1, 39100 Bolzano, Italy
Dario Bottino-Leone: Institute for Renewable Energy, European Academy of Bolzano (EURAC Research), Viale Druso 1, 39100 Bolzano, Italy
Eric John Wilczynski: Institute for Renewable Energy, European Academy of Bolzano (EURAC Research), Viale Druso 1, 39100 Bolzano, Italy

Sustainability, 2025, vol. 17, issue 17, 1-15

Abstract: The Horizon 2020 EnerMaps project addresses the fragmentation and variable reliability of European energy datasets by developing a reproducible quality control (QC) framework aligned with FAIR principles. This research supports sustainability goals by enabling better decision making in energy management, resource optimization, and sustainable policy development. This study applies this framework to an initial inventory of 50 spatially referenced energy datasets, classifying them into three assessment levels and subjecting each level to progressively deeper checks: expert consultation, metadata verification against a customized “DataCite/schema.org” schema, documentation review, completeness analysis, consistency testing via simple linear regressions, comparative descriptive statistics, and community feedback preparation. The results show that all datasets are findable and accessible, yet critical FAIR attributes remain weak: 68% lack explicit licenses and 96% omit terms-of-use statements; methodology descriptions are present in 77% of cases, while quantitative accuracy information appears in only 43%. Completeness screening reveals that more than half of the datasets exhibit over 20% missing values in one or more key dimensions. Consistency analyses nevertheless indicate statistically significant correlations ( p < 0.05) for the majority of paired comparisons, supporting basic reliability. By improving the FAIRness (Findable, Accessible, Interoperable, Reusable) of energy data, this study directly contributes to more effective sustainability assessments and interventions. The proposed QC workflow therefore provides a scalable route to improve the transparency, comparability, and reusability of heterogeneous energy data, and its adoption could accelerate open energy modelling and policy analysis across Europe.

Keywords: sustainable energy management; FAIR principles; quality control; metadata assessment; sustainable decision-making (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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