Passports for circularity, e.g., digital product passports and material passports (MPs), have gained recognition as essential policy instruments for the Circular Economy goals of the European Union. Despite the growing number of approaches, there is a lack of knowledge about the data requirements and availabilities to create MPs for existing buildings. By deploying a mixed-method research design, this study identified the potential users and their data needs within the context of European social housing organisations. Three rounds of validation interviews with a total of 38 participants were conducted to create a data template for an MP covering maintenance, renovation, and demolition stages. This data template was then tested in a case study from the Netherlands to determine critical data gaps in creating MPs, including, but not limited to the composition of materials, presence of toxic or hazardous contents, condition assessment, and reuse and recycling potential of a product. Finally, an MP framework is proposed to address these data gaps by utilising the capabilities of enabling digital technologies (e.g., artificial intelligence and scanning systems) and supportive knowledge of human actors. This framework supports further research and innovation in data provision in creating MPs to narrow, slow, close, and regenerate the loops.

Passports for circularity, e.g., digital product passports and material passports (MPs), have gained recognition as essential policy instruments for the Circular Economy goals of the European Union. Despite the growing number of approaches, there is a lack of knowledge about the data requirements and availabilities to create MPs for existing buildings. By deploying a mixed-method research design, this study identified the potential users and their data needs within the context of European social housing organisations. Three rounds of validation interviews with a total of 38 participants were conducted to create a data template for an MP covering maintenance, renovation, and demolition stages. This data template was then tested in a case study from the Netherlands to determine critical data gaps in creating MPs, including, but not limited to the composition of materials, presence of toxic or hazardous contents, condition assessment, and reuse and recycling potential of a product. Finally, an MP framework is proposed to address these data gaps by utilising the capabilities of enabling digital technologies (e.g., artificial intelligence and scanning systems) and supportive knowledge of human actors. This framework supports further research and innovation in data provision in creating MPs to narrow, slow, close, and regenerate the loops.