ITcon Vol. 25, pg. 41-54, http://www.itcon.org/2020/2

Generating partial civil information model views using a semantic information retrieval approach

DOI:10.36680/j.itcon.2020.002
submitted:March 2019
revised:August 2019
published:January 2020
editor(s):Kumar B.
authors:Tuyen Le, Assistant Professor, (Corresponding author)
Department of Civil Engineering, Clemson University, SC, USA;
tuyenl@clemson.edu

H. David Jeong, Professor,
Department of Construction Science, Texas A&M, College Station, TX, USA;
djeong@arch.tamu.edu

Stephen B. Gilbert, Associate Professor,
Department of Industrial & Manufacturing Systems Engineering, Iowa State University, IA, USA;
gilbert@iastate.edu

Evgeny Chukharev-Hudilainen, Associate Professor,
Applied Linguistics & Technology Program, Iowa State University, IA, USA;
evgeny@iastate.edu
summary:Open data standards (e.g. LandXML, TransXML, CityGML) are a key to addressing the interoperability issue in exchanging civil information modeling (CIM) data throughout the project life-cycle. Since these schemas include rich sets of data types covering a wide range of assets and disciplines, model view definitions (MVDs) which define subsets of a schema are required to specify what types of data to be shared in accordance with a specific exchange scenario. The traditional procedure for generating and implementing MVDs is time-consuming and laborious as entities and attributes relevant to a particular data exchange context are manually identified by domain experts. This paper presents a method that can locate relevant information from a source XML data schema for a specific domain based on the user's keyword. The study employs a semantic resource of civil engineering terms to understand the semantics of a keyword-based query. The study also introduces a novel context-based search technique for retrieving related entities and their referenced objects. The developed method was tested on a gold standard of several LandXML subschemas. The experiment results show that the semantic MVD retrieval algorithm achieves a mean average precision of nearly 90%. The research is original, being a novel method for extracting partial civil information models given a keyword from the end user. The method is expected to become a fundamental tool assisting professionals in extracting data from complex digital datasets.
keywords:Civil Information Modeling, Model View Definition, Civil Engineering Lexicon, Information Retrieval, Context-Aware
full text: (PDF file, 0.81 MB)
citation:Le T, Jeong H D, Gilbert S B, Chukharev-Hudilainen E (2020). Generating partial civil information model views using a semantic information retrieval approach, ITcon Vol. 25, pg. 41-54, https://doi.org/10.36680/j.itcon.2020.002