This CSV dataset provides comprehensive building metadata for 507 structures, enabling advanced performance analysis and benchmarking. The Building Data Genome Project dataset is a structured CSV file containing critical metadata for 507 distinct buildings. It captures essential building characteristics, including primary use types, total floor area, industry classification, timezone, and weather station references. This information acts as a foundational schema for energy modelling and performance studies. The data is formatted for high compatibility with standard data analysis software, allowing for systematic filtering and cross-referencing. By standardising these variables, the dataset facilitates rigorous comparative studies across diverse building typologies and climates, serving as a reliable reference for researchers and engineers.

The download is a 82 KB file containing .CSV files.

Professionals integrate this dataset by importing the CSV file into data analysis software such as Python, R, or Excel for further processing. It is primarily used to correlate building characteristics with energy consumption profiles. Engineers and analysts can join this metadata with time-series energy data to perform multi-variable regression or benchmarking. Ensure that the timezone and weather station identifiers are correctly mapped to local climate files during the initial data preparation phase to maintain accuracy in your performance simulations.

This dataset is essential for building performance professionals, energy auditors, and researchers working on large-scale portfolio analysis. It is best applied in the early stages of building retrofits or energy management projects where benchmarking is required. Use this data to normalise energy performance metrics across varied building typologies, including office buildings, retail spaces, and hotels. Practitioners often search for these files when conducting longitudinal energy studies, developing machine learning models for building operation, or establishing baseline performance indicators for sustainable design initiatives.