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

Journal Article (2020)
Author(s)

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)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1016/j.autcon.2020.103369
More Info
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Publication Year
2020
Language
English
Affiliation
External organisation
Issue number
16
Volume number
120

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.

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