Dataset: A generalisable data-driven filtering methodology for Energy Performance Certification databases

The dataset supports the research conducted in "Defining a data-driven standardized generalizable methodology to validate a large EPC dataset, a case study in Ireland" by Raushan et al. (2024). It consists of a filtered Energy Performance Certificate (EPC) database for residential buildings in Ireland, obtained through rigorous data validation methods to eliminate erroneous entries and outliers. EPCs contain crucial details regarding building energy efficiency and characteristics. The original EPC database for Ireland is publicly accessible but contains over 1 million unfiltered entries with inconsistent and erroneous values, potentially biasing analysis. This processed dataset enhances the quality and reliability of EPC data for applications in building stock modeling and research. The data is openly available in .CSV format, accompanied by the methodology employed for processing the raw database, documented in comprehensive Python scripts. Supplementary notes and metadata provide insights into the filtering process, experimental design, and details of 213 variables categorized into informational, thermophysical, geometric, and system attributes. By making this standardized, data-driven filtered EPC dataset accessible, the research empowers stakeholders, both novice and expert, to utilize this higher quality input for understanding and analyzing the Irish housing stock.