Introducing the EERAdata Decision Support Tool – key takeaways from national workshops

Over the course of almost three years, EERAdata has been developing a tool to guide municipalities and regions through the collection and processing of their building and demographic data to prioritise Energy Efficiency measures in planning, renovating, and constructing buildings.

EERAdata has been working with 3 pilot local authorities, the City of Copenhagen in Denmark, the Municipality of Velenje in Slovenia, and the Andalusian Energy Agency in Spain, creating a Decision Support Tool (DST) to identify building stock that could be upgraded to be more sustainable and energy efficient.

Between September and November 2021, workshops were held in Andalusia, Velenje and Copenhagen with regional stakeholders. The main goal was to introduce the DST and train the potential end-users in the use of the tool, but also to allow them to test it and provide feedback to support the tool’s development further.

Within the events, the presentations featured an overview of the methodologies and a live demonstration of the DST by the EERAdata partners, and an open discussion was facilitated amongst the participants after the demonstrations were concluded.

The main activities of the workshops focused on validating the methodological approach and acquiring feedback for future improvement and next steps. The ambition of the workshop was to specify the applicability of the DST on the case of public buildings (included in the DST database) that are considered by the municipalities for energy renovation in the upcoming years. Special attention was also attributed to the results that could be expected when using the DST tool, given the individual energy characteristics and the characteristics of the selected pilot buildings, as well as how to quantify and understand their value in actual investment programmes.

The feedback from participants was overwhelmingly positive which indicated the validity of the EERAdata approach and the demand for further development of the DST.


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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 847101.