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About the IES

History and Evolution of IES

The Information Exchange Standard (IES) was developed to address the challenge of inconsistent and fragmented data exchange across different organisations, sectors, and systems. Initially established within defence and national security, the standard has evolved into a cross-sector resource supporting a wide range of industries, including buildings, transport and utilities. At its heart, IES provides a standardised foundation for structuring data in a way that ensures consistency, interoperability, and adaptability.

IES operates under a structured, multi-sector governance framework that ensures transparency, consistency, and long-term sustainability. The governance structure consists of:

Representing key sectors and responsible for setting strategic direction, approving major updates, and ensuring cross-domain alignment

Managing extensions such as IES Built Environment, IES People, and other sector-specific models, ensuring their alignment with the IES framework

Responsible for implementing changes, managing version control, validating ontologies, and ensuring compliance with semantic web standards

This governance model ensures that IES remains neutral, scalable, and adaptable, supporting the needs of both public and private sector stakeholders while maintaining technical robustness.

The Future of IES

IES is continuously evolving to meet the demands of an increasingly interconnected digital landscape. Future developments include:

1

Expanding

sectoral adoption through new domain-specific working groups
2

Strengthening

interoperability with international data standards
3

Enhancing

governance structures to support cross-industry collaboration
4

Driving

innovation by incorporating emerging technologies and evolving best practices
5

Leveraging

AI for Ontology Extension Development

As part of its commitment to innovation, IES is exploring the use of large language models (LLMs) and generative AI to accelerate the ontology extension process. By using AI-powered tools to generate candidate extensions, experienced ontologists can review, refine, and validate new domain models more efficiently, significantly reducing the time required to develop viable extensions. This approach enables faster adoption and evolution of IES across multiple industries.