Mission & Focus

The Informatics and Digital Twins group specialises in synchronising the real and digital world. Using linked data and semantic technologies to represent and structure knowledge, we create digital twins that enable learning from the past to predict the future. This process supports decision-making and strategic planning in the energy sector by providing a dynamic, data-driven approach for analysing, optimising, and managing energy infrastructures. 

Key Research Topics

Our main areas of research include:

• Information and knowledge management: We leverage semantic technologies, including ontologies and knowledge graphs, to structure and represent complex knowledge related to buildings, infrastructure, and energy systems. These semantic frameworks underpin our digital twin models, enabling seamless integration, interoperability, and enhanced understanding of diverse urban energy assets. By improving information structuring and knowledge representation, our research facilitates advanced decision-making, predictive analytics, and holistic management of energy resources within urban environments.

• Technical infrastructure to support Digital Twins: Our group develops robust, scalable, and interoperable frameworks designed to support multi-scale, cross-sectoral digital twins of urban energy systems. This infrastructure aims to process and integrate real-time data to support analysis across multiple domains such as buildings, transportation, and energy grids. Our research emphasises designing flexible, modular architectures that ensure resilience, scalability, and seamless collaboration among different digital twin instances to optimise the efficiency of urban energy ecosystems. 

• Analytics, simulation and visualisation: We create analytical tools and intuitive visualisation interfaces tailored specifically for stakeholders managing complex urban energy data. These tools empower users to explore, analyse, and interpret large-scale linked datasets, unlocking valuable insights and informing actionable decisions to improve energy efficiency and sustainability. By harnessing linked data approaches, we enable advanced analytics for urban energy management and provide greater transparency for decision-makers and stakeholders alike. 

Selected research projects

Our group is actively involved in the following projects:

• Digicities  - In this project, we are developing and piloting a linked semantic data exchange platform to assist in creating digital twins for energy planning. We lead this project and are responsible for developing the architecture and data models driving the platform.  
• REFORMERS - Renewable Energy Valleys to increase energy security while accelerating the green transition in Europe. In this project, we contribute to developing a Digital Twin Blueprint for Renewable Energy Valleys. Our role in this project is to define a data vocabulary to manage time- and spatially resolved data, including historical performance data, real-time operational data and future forecasts, such as price changes and energy availability.  
• Energenius - Leveraging the energy transition by gamified learning and AI, guided by cross-sectoral integrated services and digital twin models to foster accessible and human-centred energy-saving experiences. In this project, we are developing digital twins, AI-driven energy analytics, and interoperable data frameworks to test within ENERGENIUS. We are also providing our NEST demonstrator as a Leader Pilot. Through this collaboration, we gain valuable insights into how digitalisation can bridge the gap between energy performance data and actionable strategies to reduce energy consumption and improve efficiency. 
• SEET CoSi – Co-Evolution and Coordinated Simulation of the Swiss Energy System and Swiss Society focuses on the interaction between society and the energy system. This project explores how an architecture based on linked semantic technologies can enable data management integrated from multiple sources.