Optimizing Carbon Footprint & Energy Performance for the Sustainability of Historic Buildings using Knowledge Graphs & Digital Twins

Cultural heritage preservation is crucial for climate resilience and sustainable development, requiring innovative tools, materials, and adaptive renovation to mitigate climate risks, reduce emissions, and enhance sustainability in line with the EU Green Deal and UN Sustainable Development Goals. This paper presents ongoing work integrating Knowledge Graphs, Digital Twins, and Building Information Modeling (BIM) to optimize the carbon footprint and energy performance of historic buildings through innovative restoration materials, energy harvesting technologies, and socially-driven approaches, aligning with net-zero-carbon goals. We propose a pipeline where a Digital Twin, incorporating a BIM model, simulates a historic building’s virtual representation to evaluate how different materials impact energy consumption and sustainability. The Knowledge Graph stores historical, real-time (sensor-based), and predicted weather data, enabling the Digital Twin to assess weather-driven energy performance variations and determine optimal material choices. As part of the EU-funded SINCERE project, this system provides a data-driven decision-making framework for stakeholders, supporting restoration, operation, and long-term sustainability planning for Built Cultural Heritage.