Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction

Journal article (2020)

Authors

R. K. Soman Imperial College London, The Alan Turing Institute
Miguel Molina-Solana Universidad de Granada, Imperial College London
Jennifer K. Whyte The Alan Turing Institute, Imperial College London
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Published Date

2020

Language

English

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Abstract

In the construction sector, complex constraints are not usually modeled in conventional scheduling and 4D building information modeling software, as they are highly dynamic and span multiple domains. The lack of embedded constraint relationships in such software means that, as Automated Data Collection (ADC) technologies become used, it cannot automatically deduce the effect of deviations to schedule. This paper presents a novel method, using semantic web technologies, to model and validate complex scheduling constraints. It presents a Linked-Data based Constraint-Checking (LDCC) approach, using the Shapes Constraint Language (SHACL). A prototype web application is developed using this approach and evaluated using an OpenBIM dataset. Results demonstrate the potential of LDCC to check for constraint violation in distributed construction data. This novel method (LDCC) and its first prototype is a contribution that can be extended in future research in linked-data, BIM based rule-checking, lean construction and ADC.