Imperial College London
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ProfessorJenniferWhyte

Faculty of Engineering, Department of Civil and Environmental Engineering

Laing O'Rourke/RAEng Chair in Systems Integration
 
 
 
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Contact

 

+44 (0)20 7594 9245j.whyte Website

 
 
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Assistant

 

Mr Tim Gordon +44 (0)20 7594 5031

 
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Location

 

436Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Soman:2020:10.1016/j.autcon.2020.103369,
author = {Soman, R and Molina, Solana M and Whyte, J},
doi = {10.1016/j.autcon.2020.103369},
journal = {Automation in Construction},
title = {Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction},
url = {http://dx.doi.org/10.1016/j.autcon.2020.103369},
volume = {120},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Soman,R
AU  - Molina,Solana M
AU  - Whyte,J
DO  - 10.1016/j.autcon.2020.103369
PY  - 2020///
SN  - 0926-5805
TI  - Linked-Data based Constraint-Checking (LDCC) to support look-ahead planning in construction
T2  - Automation in Construction
UR  - http://dx.doi.org/10.1016/j.autcon.2020.103369
UR  - http://hdl.handle.net/10044/1/81464
VL  - 120
ER  -
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