The HPXML Data Dictionary (BPI-2200-S-2013 Standard for Home Performance-Related Data Collection v2.2.1) provides a standard vocabulary of data elements necessary to provide a general description of a whole house or single measure energy efficiency upgrade for reporting, rebate, and basic quality assurance purposes. Each of the data elements defined in the dictionary can be transferred using the HPXML standard transfer protocol. The dictionary includes terms related to:
- Buildings, building components and building systems
- Energy conservation measures
- Energy consumption
- Energy savings (estimated and actual)
The dictionary also includes several smaller datasets for specific use cases, for example, information collected during the audit and completion of a whole-house program. These datasets, with required data elements, can be found here.
Aligned with Industry Standards
HPXML is the most widely used implementation of the Department of Energy’s Building Energy Data Exchange Specification (BEDES). BEDES is a taxonomy of terms, definitions, and field formats created to facilitate the exchange of information on building characteristics and energy use for the commercial, multifamily and residential industries.
Terms in HPXML are also in process of being mapped to the Real Estate Standards Organization's Data Dictionary, which standardizes terms used in Multiple Listing Services (MLS) nationwide. This alignment will facilitate the auto-population of a home's energy efficiency features, including score and labels, into local MLS systems. Auto-population is an efficient way to introduce energy efficiency data into real estate transactions.
There are several pilots underway to test the auto-population of MLS using HPXML, including the Northeast Energy Efficiency Partnerships' (NEEP) Home Energy Labeling Information Exchange (HELIX) and Build It Green's Green Registry in California.
The HPXML Data Dictionary is designed to grow with the industry. The HPXML working group meets quarterly to discuss updates and revisions to the data standard. Recommendations for adding new or changing existing data elements or enumerations can be proposed on Github.