Ontology-based knowledge representation for industrial megaprojects analytics using linked data and the semantic web

Abstract 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.

[1]  Nora El-Gohary,et al.  Semantic NLP-Based Information Extraction from Construction Regulatory Documents for Automated Compliance Checking , 2016, J. Comput. Civ. Eng..

[2]  Nora El-Gohary,et al.  Extending Building Information Models Semiautomatically Using Semantic Natural Language Processing Techniques , 2016 .

[3]  Charles M. Eastman,et al.  Semantics of model views for information exchanges using the industry foundation class schema , 2012, Adv. Eng. Informatics.

[4]  G. Edward Gibson,et al.  Development of a Project Scope Definition and Assessment Tool for Small Industrial Construction Projects , 2017 .

[5]  Aining Yin,et al.  Ontology development for unified traditional Chinese medical language system , 2004, Artif. Intell. Medicine.

[6]  Tomás Pitner,et al.  Semantic BMS: Allowing usage of building automation data in facility benchmarking , 2018, Adv. Eng. Informatics.

[7]  Esbjörn Segelod Project Cost Overrun: Causes, Consequences, and Investment Decisions , 2017 .

[8]  Irem Dikmen,et al.  Ontology for Relating Risk and Vulnerability to Cost Overrun in International Projects , 2011 .

[9]  John D. Finnerty,et al.  Project Financing: Asset-Based Financial Engineering , 1996 .

[10]  Jakob Beetz,et al.  IfcOWL: A case of transforming EXPRESS schemas into ontologies , 2008, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[11]  Hanbin Luo,et al.  Ontology for safety risk identification in metro construction , 2019, Comput. Ind..

[12]  Zhen Chen,et al.  Grand Challenges in Construction Management , 2019, Front. Built Environ..

[13]  Ali M. Niknejad,et al.  An ontology supported risk assessment approach for the intelligent configuration of supply networks , 2016, Journal of Intelligent Manufacturing.

[14]  Zhipeng Zhou,et al.  Overview and Analysis of Ontology Studies Supporting Development of the Construction Industry , 2016, J. Comput. Civ. Eng..

[15]  Charles M. Eastman,et al.  An ontology-based approach for developing data exchange requirements and model views of building information modeling , 2016, Adv. Eng. Informatics.

[16]  Peter Mika,et al.  Social Networks and the Semantic Web , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).

[17]  Weili Fang,et al.  Ontology-Based Semantic Modeling of Knowledge in Construction: Classification and Identification of Hazards Implied in Images , 2020 .

[18]  Yacine Rezgui,et al.  Towards a semantic Construction Digital Twin: Directions for future research , 2020, Automation in Construction.

[19]  Heiko Paulheim Beyond DBpedia & YAGO - The New Kids on the Knowledge Graph Block , 2019, AICS.

[20]  Tamer E. El-Diraby,et al.  Ontology-based optimisation of knowledge management in e-Construction , 2005, J. Inf. Technol. Constr..

[21]  Rajiv Kohli,et al.  Digital Transformation in Latecomer Industries: CIO and CEO Leadership Lessons from Encana Oil & Gas (USA) Inc , 2011, MIS Q. Executive.

[22]  Quantifying Remoteness for Risk and Resilience Assessment Using Nighttime Satellite Imagery , 2020 .

[23]  Charles Reese,et al.  Handbook of OSHA Construction Safety and Health , 1999 .

[24]  Nora El-Gohary,et al.  Domain Ontology for Processes in Infrastructure and Construction , 2010 .

[25]  Song Wu,et al.  Construction risk knowledge management in BIM using ontology and semantic web technology , 2016 .

[26]  T. A. El‐Diraby,et al.  A taxonomy for construction terms in privatized‐infrastructure finance: supporting semantic exchange of project risk information , 2006 .

[27]  Miroslaw J. Skibniewski,et al.  Modelling residual value risk through ontology to address vulnerability of PPP project system , 2018, Adv. Eng. Informatics.

[28]  G Stix,et al.  The mice that warred. , 2001, Scientific American.

[29]  Yong K. Cho,et al.  Visualization, Information Modeling, and Simulation: Grand Challenges in the Construction Industry , 2016, J. Comput. Civ. Eng..

[30]  Jan Karlshøj,et al.  Managing interrelated project information in AEC Knowledge Graphs , 2019, Automation in Construction.

[31]  Peter E.D. Love,et al.  Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology , 2020, Automation in Construction.

[32]  Pieter Pauwels,et al.  Semantic web technologies in AEC industry: A literature overview , 2017 .

[33]  Nora El-Gohary,et al.  Ontology-based automated information extraction from building energy conservation codes , 2017 .

[34]  Masashi Matsuoka,et al.  Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification , 2018, Progress in Earth and Planetary Science.

[35]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[36]  William J. O'Brien,et al.  A shared ontology for integrated highway planning , 2019, Adv. Eng. Informatics.

[37]  Sheryl Staub-French,et al.  Ontology-based feature modeling for construction information extraction from a building information model , 2013 .

[38]  Chimay J. Anumba,et al.  Collaborative project information management in a semantic web environment , 2008 .

[39]  Charles M. Eastman,et al.  An ontology-based analysis of the industry foundation class schema for building information model exchanges , 2015, Adv. Eng. Informatics.

[40]  Gül E. Okudan Kremer,et al.  A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks , 2020, Adv. Eng. Informatics.

[41]  Alexander Verbraeck,et al.  Grasping project complexity in large engineering projects: The TOE (Technical, Organizational and Environmental) framework , 2011 .

[42]  Gerhard Weikum,et al.  YAGO 4: A Reason-able Knowledge Base , 2020, ESWC.

[43]  Mohamed Al-Hussein,et al.  Ontology-based semantic approach for construction-oriented quantity take-off from BIM models in the light-frame building industry , 2016, Adv. Eng. Informatics.

[44]  Ren-Jye Dzeng,et al.  A study of ontology-based risk management framework of construction projects through project life cycle , 2009 .

[45]  R.J. Scherer,et al.  A distributed multi-model-based Management Information System for simulation and decision-making on construction projects , 2011, Adv. Eng. Informatics.

[46]  Zeeshan Aziz,et al.  Challenges and drivers for data mining in the AEC sector , 2018, Engineering, Construction and Architectural Management.

[47]  Pieter Pauwels,et al.  EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology , 2016 .

[48]  Konstantin Schekotihin,et al.  OntoDebug: Interactive Ontology Debugging Plug-in for Protégé , 2018, FoIKS.

[49]  T. Mcnulty,et al.  DEVELOPING INNOVATIVE TECHNOLOGY , 1998 .

[50]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[51]  Mathias Bonduel,et al.  Scan-to-graph: Semantic enrichment of existing building geometry , 2020 .

[52]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[53]  F. Henry Abanda,et al.  Sustainable building technology knowledge representation: Using Semantic Web techniques , 2011, Adv. Eng. Informatics.

[54]  Tamer E. El-Diraby,et al.  E-Society Portal: Integrating Urban Highway Construction Projects into the Knowledge City , 2005 .

[55]  Deborah J. Fisher,et al.  Benchmarking in Construction Industry , 1995 .

[56]  James A. Hendler,et al.  DAML+OIL: An Ontology Language for the Semantic Web , 2002, IEEE Intell. Syst..

[57]  Peter Szolovits,et al.  What Is a Knowledge Representation? , 1993, AI Mag..

[58]  Asunción Gómez-Pérez,et al.  OOPS! (OntOlogy Pitfall Scanner!): An On-line Tool for Ontology Evaluation , 2014, Int. J. Semantic Web Inf. Syst..

[59]  M. S. Fox *,et al.  Knowledge provenance in enterprise information , 2005 .

[60]  Chimay J. Anumba,et al.  Using the semantic web for project information management , 2007 .

[61]  Jose Aguilar,et al.  Ontological emergence scheme in self-organized and emerging systems , 2020, Adv. Eng. Informatics.

[62]  B. Flyvbjerg What you Should Know about Megaprojects and Why: An Overview , 2014, 1409.0003.

[63]  Alistair Byrne How have we done , 2002 .

[64]  Christophe Cruz,et al.  IFC and building lifecycle management , 2008 .

[65]  Raja R. A. Issa,et al.  Ontology in the AEC Industry : A Decade of Research and Development in Architecture, Engineering, and Construction , 2015 .

[66]  Steffen Staab,et al.  Ontology Engineering Methodology , 2009, Handbook on Ontologies.

[67]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[68]  Boris Motik,et al.  HermiT: An OWL 2 Reasoner , 2014, Journal of Automated Reasoning.

[69]  Ronald J. Brachman,et al.  An overview of the KL-ONE Knowledge Representation System , 1985 .

[70]  Yueren Wang,et al.  Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications , 2019, Automation in Construction.

[71]  Keith R. Molenaar,et al.  Construction Project Cost Escalation Factors , 2009 .

[72]  Aminah Robinson Fayek,et al.  Initial metrics and pilot program results for measuring the performance of the Canadian construction industry , 2008 .

[73]  Bonsang Koo,et al.  Industry Foundation Classes for Project Management - A Trial Implementation , 1999, J. Inf. Technol. Constr..

[74]  Marta Sabou,et al.  Ontology (Network) Evaluation , 2012, Ontology Engineering in a Networked World.

[75]  Graham A. Davis,et al.  Bias and Error in Mine Project Capital Cost Estimation , 2008 .

[76]  Saeed Karshenas,et al.  Integrating Distributed Sources of Information for Construction Cost Estimating using Semantic Web and Semantic Web Service technologies , 2015 .

[77]  Martin Fischer,et al.  An Ontology for Relating Features with Activities to Calculate Costs , 2003 .

[78]  Nora El-Gohary,et al.  Ontology-Based Multilabel Text Classification of Construction Regulatory Documents , 2016, J. Comput. Civ. Eng..