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Ontology-based knowledge representation for industrial megaprojects analytics using linked data and the semantic web
Advanced Engineering Informatics ( IF 8.0 ) Pub Date : 2020-10-08 , DOI: 10.1016/j.aei.2020.101164
Pouya Zangeneh , Brenda McCabe

The fourth industrial revolution has affected most industries, including construction and those within the delivery chain of megaprojects. These major paradigm shifts, however, did not considerably improve the track record in predicting project outcomes and estimating required resources. One reason is the lack of unified data definitions and expandable knowledge representation across project lifecycle to represent megaprojects for analytics. This paper proposes and evaluates a unified ontology for project knowledge representation that facilitates data collection, processing, and utilization for industrial megaprojects through their lifecycle. The proposed Uniform Project Ontology, or UPonto, provides a data infrastructure for project analytics by enabling logical deductions and inferences, and flexible expansion and partitioning of the data utilizing linked data and the semantic web. The ontology facilitates cost normalization processes, temporal queries, and graph queries using SPARQL, while defining universal semantics for a wide range of project risk factors and characteristics based on comprehensive research of the empirical project risk and success literature augmented by practical considerations gained through expert consultations. UPonto forms the basis for a project knowledge graph to utilize unstructured data; it as well provides semantic definitions for smart IoT agents to consume project risk data and knowledge.



中文翻译:

基于本体的知识表示,用于使用链接数据和语义网的工业大型项目分析

第四次工业革命已影响到大多数行业,包括建筑业和大型项目交付链中的那些行业。但是,这些重大的范式转换并没有在预测项目成果和估计所需资源方面显着改善跟踪记录。原因之一是缺乏统一的数据定义和跨项目生命周期的可扩展知识表示,无法表示用于分析的大型项目。本文提出并评估了用于项目知识表示的统一本体,该本体有助于在工业大型项目的整个生命周期中进行数据收集,处理和利用。拟议的统一项目本体(UPonto)通过启用逻辑推论和推理,为项目分析提供了数据基础架构,利用链接数据和语义网灵活地扩展和划分数据。本体使用SPARQL简化了成本规范化过程,时间查询和图形查询,同时基于对项目实证风险和成功文献的全面研究,并通过专家咨询获得的实践考虑,为广泛的项目风险因素和特征定义了通用语义。 。UPonto构成项目知识图利用非结构化数据的基础;它还为智能物联网代理提供语义定义,以使用项目风险数据和知识。同时根据对实证项目风险和成功文献的全面研究,为广泛的项目风险因素和特征定义通用语义,并通过专家咨询获得的实际考虑加以补充。UPonto构成项目知识图利用非结构化数据的基础;它还为智能物联网代理提供语义定义,以使用项目风险数据和知识。同时根据对实证项目风险和成功文献的全面研究,为广泛的项目风险因素和特征定义通用语义,并通过专家咨询获得的实际考虑加以补充。UPonto构成项目知识图利用非结构化数据的基础;它还为智能物联网代理提供语义定义,以使用项目风险数据和知识。

更新日期:2020-10-08
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