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HARMONISE Common Information Model

Creating a Shared Language for Smart Energy

Every smart energy community tells a story through data.

Buildings generate energy.
Solar panels produce electricity.
Batteries store it.
Sensors monitor performance.
Weather services provide forecasts.
Energy management systems decide what happens next.

The challenge is that each of these technologies often describes itself differently.

For smart energy communities to operate efficiently, they need more than data,they need a common understanding of that data.

This is why HARMONISE has developed its Common Information Model (CIM).

What is a Common Information Model?

A Common Information Model is essentially a shared digital vocabulary. It defines how energy assets, devices, measurements and services should be described so that every participating system interprets information consistently. Instead of every technology using its own terminology, the CIM creates one common reference that everyone can understand. Think of it as a universal dictionary for smart energy communities.

Making complexity simple

One of the most innovative aspects of the HARMONISE approach is that it hides technical complexity from users. Site managers should not need to be experts in semantic technologies or knowledge engineering to configure their energy systems. Instead, HARMONISE separates simple, human-readable site descriptions from the underlying technical representation. This means that local energy communities can describe their buildings, renewable assets and sensors using straightforward configurations, while the platform automatically generates the advanced semantic models needed by digital applications.

Why is this important?

The Common Information Model supports many of the intelligent services that will power tomorrow’s energy communities.

For example, it allows software to:

  • Automatically discover available solar plants and battery systems
  • Understand which sensors provide which measurements
  • Identify communication channels for connected devices
  • Validate incoming data before it is used
  • Support forecasting and optimisation tools without manual configuration

In other words, the system becomes capable of understanding its own infrastructure.

HARMONISE Common Information Model

From data to knowledge

HARMONISE goes beyond simply storing information. The project transforms energy data into a Knowledge Graph. A Knowledge Graph is a structured network of connected information that allows software to understand relationships between different assets.

Instead of simply knowing that a temperature sensor exists, the system also understands:

  • which building it belongs to,
  • what it measures,
  • which heating system it supports,
  • and how that information can be used by other services.

This richer understanding makes advanced queries, automation and intelligent decision-making possible.

Built on European standards

Rather than starting from scratch, the HARMONISE Common Information Model builds upon internationally recognised semantic standards and ontologies. This approach ensures compatibility with existing initiatives while avoiding unnecessary duplication. The result is a flexible framework that can evolve alongside future European digital energy ecosystems.

A foundation for the future

As the HARMONISE pilots demonstrate the platform in real environments across Europe, the Common Information Model will become the backbone that connects diverse technologies into one coherent ecosystem. Because the future of smart energy is not simply about collecting more data. It is about ensuring that every system understands the data it receives and can use it to make better decisions.

That is the role of the HARMONISE Common Information Model: creating the shared language that enables truly interoperable smart energy communities.

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Optimizing Energy for Smart, Green Cities

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

This project has been partially funded by the European Union’s Horizon Europe research and innovation programme under the grant agreement No. 101138595 and by the Descriere imagine Swiss Government.

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