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<p>Wider implementation of circular economy practices in the construction sector requires predicting the availability, properties, and qualities of reusable components beyond mere material quantities. However, data describing the geometric attributes, material properties, and modes of assembly of products available in current buildings is limited. To address this data gap, we present the Digital Inventory for Swiss Construction Systems (DISCS), a database structure that provides detailed information on component attributes in as-built load-bearing and insulating layers of existing buildings. The dataset currently provides granular data for 102 buildings in Switzerland, each digitalised into a building information model and parameterised using a custom library of 78 attributes. The database structure facilitates the operationalisation of an inventory for construction systems, providing a basis for stock prediction that supports the upscaling of component reuse in new projects. This data descriptor motivates the need for such a database, describes its ontology, and validates its use through a series of first-level analyses.</p>

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Digital Inventory of Swiss Construction Systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月18日

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  • Aldrick Arceo,
  • Maléna Bastien-Masse,
  • Barbara Lambec,
  • Corentin Fivet

摘要

Wider implementation of circular economy practices in the construction sector requires predicting the availability, properties, and qualities of reusable components beyond mere material quantities. However, data describing the geometric attributes, material properties, and modes of assembly of products available in current buildings is limited. To address this data gap, we present the Digital Inventory for Swiss Construction Systems (DISCS), a database structure that provides detailed information on component attributes in as-built load-bearing and insulating layers of existing buildings. The dataset currently provides granular data for 102 buildings in Switzerland, each digitalised into a building information model and parameterised using a custom library of 78 attributes. The database structure facilitates the operationalisation of an inventory for construction systems, providing a basis for stock prediction that supports the upscaling of component reuse in new projects. This data descriptor motivates the need for such a database, describes its ontology, and validates its use through a series of first-level analyses.