Building Energy Profiles: A Geospatial Dataset for Dublin, Ireland

Description

Central to our investigation is the Building Energy Rating (BER) dataset of Ireland, sourced from GeoDirectory data. This dataset provides a foundational resource, encompassing a comprehensive range of building-scale parameters such as detailed addresses, geocode data (latitude and longitude), area, height, number of floors, roof type, construction age, radon emission, HVAC system details, and bedroom and bathroom counts. To enrich this dataset, we incorporated additional features from the Digital Landscape Models (DLM) Core Data from Tailte Éireann Surveying (PRIME2 Dataset). These enhancements include metrics such as nearest neighbor buildings, the density of the built environment surrounding each building, and district attributes like the ratio of green area to non-green area in the urban vicinity. Dataset Compilation: After carefully considering various data acquisition methods to capture building-scale and neighborhood-scale features, including both geometric and non-geometric attributes, as well as information about the surrounding built environment, we compiled a comprehensive dataset. Due to data protection policies, specific spatial details such as latitude, longitude, and addresses were omitted. However, the remaining data, aligned with our data acquisition objectives, is structured into a CSV file available in the mentioned repository. Key Features: 1. Building-Scale Attributes: o Identification and Location: Building ID, detailed address (excluding specific spatial details for privacy), geocode data. o Structural Details: Area, height, number of floors, roof type, construction age. o Energy and Environmental Data: BER rating, radon emission, HVAC system details. o Additional Metrics: Estimated number of bedrooms and bathrooms, water heating source, space heating source. 2. Neighborhood-Scale Attributes: o Environmental Context: Soil composition, presence of water bodies and green spaces, built-up areas. o Urban Infrastructure: Roads, pathways, networks, and other land uses. o Spatial Relationships: Built environment density, district green and non-green area, and land cover specification. Acknowledgment: We would like to thank the funder of the project, Science Foundation Ireland (SFI) under the NexSys SFI/21/SPP/3756 programme. We also thank to CEO, Tailte Éireann (acting on behalf of the Government of Ireland) to reproduce Tailte Éireann – Surveying maps and data for the annual copyright licence, CYAL50402364, © Tailte Éirean.n – Surveying.

Steps to reproduce

Utilizing datasets like the GeoDirectory Building Energy Ratings (BER) dataset of Ireland, supplemented by data of Digital Landscape Models (DLM) Core Data from Tailte Éireann Surveying (PRIME2 Dataset), land use map of Dublin, we acquire both geometric and non-geometric data related to buildings in Dublin at both building and neighborhood scales. These datasets enable us to perform effective neighborhood-scale analysis and built environment analysis within a geospatial context. Our methodology employs a diverse array of tools and software, including programming languages such as MATLAB and Python ( in the Jupyter Notebook interface), with libraries such as Geopandas, Pandas, NumPy, Seaborn, and Scikit-learn were used for data processing and analysing. Additionally, we conduct geospatial analyses using toolbox and plugins of the ArcGIS and QGIS software. Our approach involves data collection encompassing various parameters such as building attributes, neighborhood characteristics, and urban-scale built environment metrics at both building and neighborhood scales.

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