These are data from domestic Energy Performance Certificates (EPC) summarised by Lower Super Output Areas (LSOA) to preserve anonymity. Duplicate EPC's are removed with only the most recent retained in this dataset. Key attributes are summarised by percent and sum within each LSOA. This helps inform the evidence base for Combined Authority investment in energy efficiency and environmental protection.

These are data from domestic Energy Performance Certificates (EPC). Duplicate EPC's are removed with only the most recent retained in this dataset. Locations are the centroid of the postcode in which the property falls, hence there may be multiple properties at each centroid location. Indices of multiple deprivation (IMD) deciles are also added to the data. These are related to the Lower Super Output Area of the property. These data help to inform the evidence base for Combined Authority investment in energy efficiency and environmental protection.

Database of standardised energy saving operations covered by the Energy Savings Certificate scheme.

The dataset contains integrated information of the Spanish territory, regarding energy certification, building monitoring, and geographical data. The integration has been carried out by means of semantic technologies. Following of the Linked Data principles helps to guarantee standard methods of accessing the data as well as to connect data to the existing dataset on the Web of Data. The dataset is a knowledge base for end-users. It has a clear objective of providing information that stakeholders need for improving energy efficiency of buildings, influencing, thus, their respective decision-making areas

EPC Bands of dwellings in England and Wales, by property type, tenure, property age and whether new or existing.

If you want to give feedback on this dataset, or wish to request it in another form (e.g csv), please fill out this survey here. We are a not-for-profit research organisation keen to see how others use our open models and tools, so all feedback is appreciated! It's a short form that takes 5 minutes to complete.

Important Note: Before downloading this dataset, please read the License and Software Attribution section at the bottom.

This dataset aligns with the work published in Centre for Net Zero's report "Hitting the Target". In this work, we simulate a range of interventions to model the situations in which we believe the UK will meet its 600,000 heat pump installation per year target by 2028. For full modelling assumptions and findings, read our report on our website.

The code for running our simulation is open source here.

This dataset contains over 9 million households that have been address matched between Energy Performance Certificates (EPC) data and Price Paid Data (PPD). The code for our address matching is here. Since these datasets are Open Government License (OGL), this dataset is too. We basically model specific columns from various datasets, as set out in our methodology section in our report, to simplify and clean up this dataset for academic use. License information is also available in the appendix of our report above.

The EPC data loaders can be found here (the data is here) and the rest of the schemas and data download locations can be found here.

Note that this dataset is not regularly maintained or updated. It is correct as of January 2022. The data was curated and tested using dbt via this Github repository and would be simple to rerun on the latest data.

The schema / data dictionary for this data can be found here.

Our recommended way of loading this data is in Python. After downloading all "parts" of the dataset to a folder. You can run:

import pandas as pd


data = pd.read_parquet("path/to/data/folder/")

Licenses and software attribution:

For EPC, PPD and UK House Price Index data:

For the EPC data, we are permitted to republish this providing we mention that all researchers who download this dataset follow these copyright restrictions. We do not explicitly release any Royal Mail address data, instead we use these fields to generate a pseudonymised "address_cluster_id" which reflects a unique combination of the address lines and postcodes, as well as other metadata. When viewing ICO and GDPR guidelines, this still counts as personal data, but we have gone to measures to pseudonymise as much as possible to fulfil our obligations as a data processor. You must read this carefully before downloading the data, and ensure that you are using it for the research purposes as determined by this copyright notice.

Contains HM Land Registry data © Crown copyright and database right 2021. This data is licensed under the Open Government Licence v3.0.

Contains OS data © Crown copyright and database right 2022.

Contains Office for National Statistics data licensed under the Open Government Licence v.3.0.

The OGL v3.0 license states that we are free to:

copy, publish, distribute and transmit the Information;

adapt the Information;

exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application.

However we must (where we do any of the above):

acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence;

You can see more information here.

For XOServe Off Gas Postcodes:

This dataset has been released openly for all uses here.

For the address matching:

GNU Parallel: O. Tange (2018): GNU Parallel 2018, March 2018, https://doi.org/10.5281/zenodo.1146014

This data set lists sustainability metric data for state-owned buildings. These data are used to track state departments’ progress toward the goals mandated in Executive Order B-18-12. The metrics tracked in this set are total water use, total energy use, renewable energy generation and LEED certifications. The data set also includes building information for the 1722 buildings listed including, building name, address, total square footage and use type. These data are entered by property owners from each state department into the database Energy Star Portfolio Manager. Most data are obtained by property owner using the utility bill; however, some of the information is automatically fed into the database by the utility company.

Abstract copyright UK Data Service and data collection copyright owner.

The Smart Energy Research Lab (SERL) delivers a unique energy data resource to the UK research community that enables a broad range of multi-disciplinary, socio-technical research relating to energy consumption in domestic buildings.

The SERL Observatory is transforming Great Britain's energy research through the long-term provision of high quality, high-resolution energy data that provides a reliable evidence base for intervention, observational and longitudinal studies across the socio-technical spectrum.

The goals of the Smart Energy Research Lab are to provide:

• A trusted data resource for researchers to utilise large-scale, high-resolution energy data
• An effective mechanism for collecting and linking energy data with other contextual data
• High quality data management to ensure fit-for-purpose data are provisioned to researchers

Participant recruitment began in August 2019. Approximately 1,700 participants were recruited from central and southern England and from Wales as part of a pilot study that tested different recruitment strategies. The second recruitment wave took place in August-September 2020, and the third wave at the start of 2021. SERL recruited over 13,000 households which are regionally representative across England, Scotland and Wales. Recruitment is also designed to be representative of each Index of Multiple Deprivation (IMD) quintile; an area-based relative measure of deprivation.

For the latest edition (released in May 2024), all SERL data up to and including 31st December 2023 were made available. Users should note that this is the 6th edition of SERL data that has been released, though the citation may refer to the 7th edition.

All code provided with the data is now managed on the SERL GitHub website.

Smart meter data:

• Daily and half-hourly energy (electricity and gas) consumption data
• Tariff data
• Additional smart meter technical data

Contextual data:

• SERL survey (initial) completed by participant households on sign-up providing data on household information and building characteristics.
• Energy Performance Certificate (EPC) data
• Weather data
• SERL Covid-19 survey: sent to wave 1 participants in May 2020 to understand their circumstances during the first lockdown
• SERL survey (Follow-up 2023): sent to all active participants in early 2023 to investigate the impact of rapidly rising energy costs in 2022/2023

SERL data will be updated and made available to researchers on a quarterly basis. SERL is an evolving data resource and thus new editions of the data might include:

• additional records – more smart meter data, since the previous edition
• additional participants – more participants recruited since the previous release
• additional variables – where new variables become available to SERL

Further information about SERL can be found on serl.ac.uk and in the associated documentation. The 'Key Documents' section of the SERL website, which links to all publications that use SERL data, can be found at serl.ac.uk/key-documents. If you do not see your SERL-data publication listed, please contact the SERL team via info@serl.ac.uk.

For the latest edition (released in November 2024), all SERL smart meter and climate data have been updated to June 2024. Users should note that this is the 7th edition of SERL data that has been released, though the citation may refer to the 8th edition.

The SERL Observatory panel provides data primarily relating to energy demand and consumption in domestic buildings in Great Britain.

The London Building Stock Model v2 provides energy efficiency data for all London homes. This includes information on EPC ratings, heating systems, insulation levels and building fabric. This dataset represents an update of the original London Building Stock Model, and it brings together data from Energy Performance Certificates (EPCs), alongside data from other sources such as the London borough councils and the GLA. For properties that don't have data from an EPC or an alternative source, we’ve generated modelled values for these properties through machine learning. For more information on our methodology, please see this blog post. An interactive map for this data is available here. The data from the London Building Stock Model interactive map has been made available through the data extracts below. The current version of the London Building Stock Model v2 is based on data from October 2024. The data contains Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'. © Crown copyright and database rights 2023

The London Building Stock Model v2 provides energy efficiency data for all London homes. This includes information on EPC ratings, heating systems, insulation levels and building fabric.

This dataset represents an update of the original London Building Stock Model, and it brings together data from Energy Performance Certificates (EPCs), alongside data from other sources such as the London borough councils and the GLA. For properties that don't have data from an EPC or an alternative source, we’ve generated modelled values for these properties through machine learning. For more information on our methodology, please see this blog post.

An interactive map for this data is available here. The data from the London Building Stock Model interactive map has been made available through the data extracts below.

The current version of the London Building Stock Model v2 is based on data from October 2024.

The data contains Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'. © Crown copyright and database rights 2023

The London Building Stock Model v2 provides energy efficiency data for all London homes. This includes information on EPC ratings, heating systems, insulation levels and building fabric. This dataset represents an update of the original London Building Stock Model, and it brings together data from Energy Performance Certificates (EPCs), alongside data from other sources such as the London borough councils and the GLA. For properties that don't have data from an EPC or an alternative source, we’ve generated modelled values for these properties through machine learning. For more information on our methodology, please see this blog post. An interactive map for this data is available here. The data from the London Building Stock Model interactive map has been made available through the data extracts below. The current version of the London Building Stock Model v2 is based on data from October 2024. The data contains Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'. © Crown copyright and database rights 2023

Land Registry Price Paid Data (PPD) have been published as open data since 2013. These data have been transformative for house price variation research in the UK as they are a comprehensive record of residential transactions at address level and cover the whole of England and Wales over a period dating back to 1995. Despite the utility of these data, a lack of attribute information relating to the properties, such as total floor area information, is identified as one of the major shortcomings of the PPD data. This means that the impacts of stock mix on broader price patterns cannot be fully accounted for. This research outlines one approach which addresses this deficiency by combining transaction information from the official open Land Registry Price Paid Data (PPD) with property size information form the official open Domestic Energy Performance Certificates (EPCs). A four-stage data linkage is created to generate a new linked dataset, representing 79% of the full market sales in the Land Registry PPD. This new linked dataset details 5,732,838 transactions in England and Wales between 2011 and 2019, along with each property's total floor area and the number of habitable rooms. Codes for other commonly used spatial units from Output Area to Local Authority are also included in the dataset. This offers greater flexibility for the exploration of house price variation in England and Wales at different spatial scales. The data collection includes the scripts used for linkage, as well as the resulting dataset.

Current residential house price variation research in the UK is limited by lack of an open and comprehensive house price database that contains both transaction price alongside dwelling attributes such as size. This research outlines one approach which addresses this deficiency in England and Wales through combining transaction information from the official open Land Registry Price Paid Data (PPD) and property size information form the official open Domestic Energy Performance Certificates (EPCs). A four-stage data linkage is created to generate a new linked data, representing 79% of the full market sales in Land Registry PPD. This new linked dataset offers greater flexibility for the exploration of house price (house price per square metre) variation in England and Wales at different spatial scales over postcode unit between 2011 and 2019.

The Mayor is committed to cutting fuel poverty and increasing the energy efficiency of buildings across London. To help target where action is most needed, the Mayor has developed a London Building Stock Model with the UCL Energy Institute. The London Building Stock Model is a database of all the energy and carbon data collected through the Mayor’s energy programmes and policies. It provides a snapshot of all London’s buildings (both domestic and non-domestic) with information on their energy performance certificates as of 2017.

More information is available here, and an interactive map is available here.

Most of the data from the London Building Stock Model interactive map has been made available through the data extracts below. Please note that the data extracts are based on Ordnance Survey's list of London properties as of 2023. However, as the London Building Stock Model data is from 2017, some of the properties might not have any London Building Stock Model data attached to them.

The data contains Ordnance Survey mapping and the data is published under Ordnance Survey's 'presumption to publish'. © Crown copyright and database rights 2023

The dataset made available presents the park of Data Centres funded by the Investment Directorate of the Bank of Territories, in investments or loans. This game specifies the name of the data center, its location, the actors of the project (operator, other shareholders and financing banks), its progress (under construction, delivered or in service), the expected or actual date of its commissioning, its technical characteristics (target PUE at full load, TIER level, IT power, number of target bays), its certifications in areas such as energy efficiency and the holding rate of Caisse des Dépôts. Note that the CDC’s detention rate (in %) can be devoid of purpose and then left blank. The certifications/codes of conduct indicated and the responsible bodies are: * Design certification – “Tier Certification of Design Documents” from Uptime Institute – * European Code of Conduct – “The European Code of Conduct for Energy Efficiency in Data Centre” of the European Commission – ‘https://e3p.jrc.ec.europa.eu/communities/data-centres-code-conduct’ * ISO 27001 certification – ISO Information Security Management (International Organisation for Standardisation)/IEC (International Electrotechnical Commission) – ‘https://www.iso.org/fr/isoiec-27001-information-security.html’ * HDS certification – “Hosting of health data” by a certification body accredited by COFRAC – * Bureau Veritas certification – Certification of data center projects by Bureau Veritas in the design, construction and reception phases – https://www.bureauveritas.fr/newsroom/bureau-veritas-certification-de-projet-de-datacenter This game is produced by Banque des Territoires, Caisse des Dépôts (CDC).