Guidance

Education estates property data model

Published 26 August 2026

Applies to England

Background

The Education estates strategy sets out the government’s long term plan to improve the education estate in England.

The strategy includes transforming how we capture, manage and use data across the lifecycle of the estate, which:

• supports responsible bodies in managing their estates effectively
• helps the Department for Education (DfE) make informed funding and investment decisions

The education estates property data model provides a common way to organise property data and is an essential part in delivering this transformation.

About the property data model

A data model sets out how data is organised and how different datasets relate to each other. This helps improve data quality and consistency, supporting interoperability (the ability for data to be shared and used across different systems and software).

The education estates property data model provides a common structure for collecting, managing and reporting estates data. It enables datasets to be linked, mapped and shared consistently, making it easier to combine, compare and analyse information over time and at different levels.

This provides reliable information about the estate that can be used across digital tools and services, helping organisations make informed decisions about investment, maintenance and improvement.

Using the property data model

The property data model is currently published as guidance.

Organisations that collect, manage or use education estates data are encouraged to organise their data to align with the levels in the model where possible, so it is clear which site, block and space the data relates to. The model will inform future DfE estates data collections.

The model has been developed using existing data standards and established estates data structures. For many organisations, it may already be similar to the data structures they use, or require only minimal changes to adopt.

It does not replace or amend other established standards.

Why the property data model is important

The property data model helps organisations link, combine and share estates data in a consistent way. By supporting consistency and interoperability, it enables data to be used reliably across different systems and tools.

This can help organisations:

• build a more complete, consistent and accurate picture of their estate
• link and share data from different sources more easily
• make better use of existing data and reduce duplicate data collection
• maintain a history of estate information over time, including when sites move between organisations
• improve the accuracy and efficiency of data linking, including through automation
• use new digital tools and approaches, such as data dashboards, digital twins and artificial intelligence (AI)
• use their existing platforms, systems and software as the data model is system-agnostic
• align with existing government and construction sector standards for managing property information

Who should use the property data model

The property data model applies to land and buildings across the school and college estate.

Schools

This guidance is for people and organisations responsible for overseeing, managing or using estates, property and infrastructure data in schools, including:

• proprietors, school leaders and academy leaders
• governors and academy trustees
• school business professionals
• those responsible for the day-to-day management of the school estate
• local authorities
• diocesan authorities and other religious authorities
• trustees of schools, including academy trusts, which means the members of the foundation which established the school. In foundation schools or voluntary schools, the trustees are the members of the foundation that established the school

For schools and academies with a religious character the trustees will be:

• the Church of England
• the Catholic Church
• other religious bodies

Further education colleges

This guidance is also for people involved in the strategic management, development, maintenance, safety and day-to-day operation of further education (FE) college estates.

This includes individuals and teams responsible for overseeing, managing and operating estates, property and infrastructure within:

• FE colleges
• land based colleges
• designated institutions

Throughout this guidance, these institutions are collectively referred to as ‘colleges’.

Structure of the property data model

The property data model uses a 4 level structure to organise property data consistently. This helps ensure data can be linked to the correct site, building and location.

The levels are:

• site
• block or facility
• floor or room
• assets and elements

The model provides a consistent framework that allows different types of property data to be linked together, including:

• funding data
• asset registers
• condition and structural survey information
• compliance and safety records

These datasets support both DfE activities, such as funding decisions, and estate management activities carried out by schools, colleges and responsible bodies.

Not all datasets will contain information at every level of the model. The level of detail available will vary between datasets. For example, some datasets may only include information at site or block level and will not contain data for lower levels of the structure.

The model will also allow sites and buildings to be linked to the relevant schools, colleges and responsible bodies. This provides a record of which organisation is responsible for the management, oversight and funding of sites and buildings.

These relationships can be maintained over time, helping to preserve the history of sites and buildings, including when they transfer between schools, colleges or responsible bodies.

Unique references and geospatial identifiers

The property data model provides a common structure for organising property data. To make sure data is linked to the correct location, it also needs a consistent set of unique identifiers.

DfE is developing geospatial identifiers that can be used to identify specific locations within the school and college estate, such as sites and buildings. These identifiers will help ensure that data relating to a location can be recorded consistently, linked accurately and tracked over time.

Property datasets often use different labels or references for locations, including:

• sites
• blocks
• floors
• rooms
• spaces

Because these references are not always consistent between datasets, it can be difficult to match information accurately. A common set of identifiers will make it easier to connect data from different sources and reduce the risk of errors.

Why geospatial identifiers are important

Information about school locations is often taken from Get information about schools (GIAS). This is usually based on postcodes, which may not accurately identify the site or land being referenced.

Geospatial identifiers are based on the physical location of a site or building. They provide a more precise and consistent way of identifying property assets and can be used reliably across different datasets and systems.

Using geospatial identifiers will make it easier to link other location-based information to the education estate, including:

• topography and terrain data
• land use information
• flood risk data
• weather and climate information

This could support new forms of analysis and provide further insight into the condition, resilience and management of the estate.

Related data standards 

The property data model has been developed to align with existing standards and data structures used across government, the construction sector and education estates.

It is based on and consistent with the:

• principles of Building Information Modelling (BIM)
• Industry Foundation Classes (IFC) data standard, which is supported by the ISO 19650 series of standards for information management
• Government Property Data Standard
• Condition Data Collection (CDC) data structure
• Uniclass, delivered by NBS

Future development

The property data model supports the aims of the Education Estates Strategy to improve how estates data is collected, managed and used across the education sector.

The model will inform future DfE estates data collections. DfE is developing a broader approach to collecting estates data that will support both:

• responsible bodies in managing and planning their estates
• DfE in making decisions about funding and investment

This is intended to build on the Condition Data Collection (CDC) programme and support a more joined-up approach to estates data.

Developing the data schema

DfE is developing a data schema for collecting estates data based on the property data model. A data schema is the detailed specification that defines how data is structured, stored and linked.

Responsible bodies and other sector organisations will have opportunities to provide feedback on the data schema as it is developed. This feedback will help inform future estates data collections, including planned activity from 2027 onwards.

The model and data schema will continue to be tested and refined. Any significant changes or improvements will be reflected in future updates to this guidance.

Geospatial identifiers

DfE is testing options for applying geospatial identifiers across the school and college estate and how these can be incorporated into the property data model.

Once this work is complete, this guidance will be updated to explain:

• the proposed approach to geospatial identifiers
• how identifiers will be assigned and managed
• how schools, colleges and responsible bodies will be able to access and use them

Give feedback

To provide any feedback or comments on this guidance, contact us via the Manage your education estate customer help portal.