Knowledge graph-driven smart contract for metadata checking in blockchain-based BIM collaboration

Xingyu Tao, Zhaoji Wu, Chengliang Zheng, Hao Liu, Moumita Das, Jack C.P. Cheng

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

Abstract

The increasing digitalization, especially the implementation of building information modelling (BIM) in the construction industry, has inevitably introduced cybersecurity vulnerabilities like data manipulation and denial of access. There is a trend of integrating BIM with blockchain in a design or construction process to secure data integrity and traceability. Metadata data (e.g., ID, version, digital signatures) of BIM models can be stored in a decentralized and unchangeable manner by blockchain. However, one limitation is that the current blockchain cannot detect the correctness of input metadata, contaminating the quality of BIM data in a shared blockchain and thereby hindering collaboration efficiency. Data interaction with blockchain relies on blockchain smart contracts. Therefore, this paper proposes a knowledge graph-driven smart contract (KGSC) for metadata checking in blockchain-based BIM collaboration. Two contributions of this work are: (1) 29 rules are reasoned and generated from the ISO 19650 knowledge graph, and (2) a KGSC algorithm is developed and verified. Results indicate that BIM data processed by the KGSC has higher compliance and accuracy.

Original languageEnglish
Publication statusPublished - 2023
Event30th International Conference on Intelligent Computing in Engineering 2023, EG-ICE 2023 - London, United Kingdom
Duration: 4 Jul 20237 Jul 2023

Conference

Conference30th International Conference on Intelligent Computing in Engineering 2023, EG-ICE 2023
Country/TerritoryUnited Kingdom
CityLondon
Period4/07/237/07/23

ASJC Scopus subject areas

  • Computer Science Applications
  • General Engineering

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