Ontology-Based Information Integration: A State-of-the-Art Review in Road Asset Management

Lei, Xiang; Wu, Peng; Zhu, Junxiang; Jun, Wang

doi:10.1007/s11831-021-09668-6

Cited by 9 publications

(6 citation statements)

References 86 publications

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“…Another ontology focusing on Concrete Bridge Rehabilitation Project Management (CBRPMO) was developed to model domain information during the rehabilitation procedures (Wu et al 2021). For the area of road AM, a variety of ontology developments mainly has focused on the operation and maintenance phase (Lei et al 2021). For example, an important outcome of the European research project INTERLINK was the development of the European Road Object Type Library (EUROTL) (Luiten et al 2018).…”

Section: Ontologies For the Transportation Infrastructure Domainmentioning

confidence: 99%

BIM-Enabled Infrastructure Asset Management Using Information Containers and Semantic Web

Hagedorn

Liu

König

et al. 2023

J. Comput. Civ. Eng.

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The paper proposes a solution for a Building Information Modeling (BIM)-enabled Infrastructure Asset Management System (AMS) for road owners. The approach provides asset managers with a strategy for the dynamic use of Information Containers for Linked Document Delivery (ICDDs), considering the requirements of stakeholders across domains in the operational phase. The state of the art shows how information management can be carried out utilizing information containers employing Semantic Web technologies Resource Description Framework (RDF), SPARQL, and R2RML. The key output is developing a web-based platform that implements ICDD containers for asset management. Existing AMS are integrated by using SQL data mapped to RDF-based ontology data in the container. The use of existing domain-specific ontologies for infrastructure in combination with the linkage of domain knowledge to a three-dimensional BIM model is a step beyond the state of the art and practice in the construction industry. Linking inside the container allows for querying data across several information models and ontology-based data to create stakeholder-specific data views. The approach was demonstrated in two use cases. The first was related to the visual inspection of a concrete bridge. The detection of damage and the process of communicating the damage to a contractor charged with the repair were described. The second use case was related to a road pavement and demonstrated how decision-making about maintenance activities can be supported using cross-domain information containers.

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Section: Ontologies For the Transportation Infrastructure Domainmentioning

confidence: 99%

BIM-Enabled Infrastructure Asset Management Using Information Containers and Semantic Web

Hagedorn

Liu

König

et al. 2023

J. Comput. Civ. Eng.

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“…The ontology and the reasoner are two core components in a knowledge graph. In the field of construction, a variety of ontologies have been established for different scenarios, such as concrete bridge rehabilitation (Wu et al, 2021a), road asset management (Lei et al, 2021), and construction defects (Lee et al, 2016). However, most reasoners on these ontologies in construction are rule-based requiring manual intervention (Lei et al, 2021).…”

Section: Opportunities Knowledge Graphmentioning

confidence: 99%

Graph neural networks in building life cycle: a review

Yilong¹,

Wang²,

Reza³

et al. 2022

Proceedings of the 2022 European Conference on Computing in Construction

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Graph neural networks (GNNs) have attracted much attention in the field of machine learning because of their excellent performance on graph data. Graph data in the architecture, engineering and construction (AEC) sector is very common, such as bubble diagrams for space planning and point clouds for scan-to-BIM models. Some studies in AEC have adopted GNNs to solve practical problems. However, there has been a limited focus on the outcomes of these studies. Therefore, this paper aims to review the applications of GNNs in the building lifecycle. A wide range of existing literature was retrieved. The result shows that the adoption of GNNs is still in its infancy but has been increasing dramatically in recent years. Ten application domains were identified from the planning stage to the operation stage. In addition, the challenges and opportunities of GNNs adoption in AEC were discussed providing directions for future research.

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“…Generally, there are four stages in the life cycle of road assets: planning, construction, operation, and maintenance [37]. The majority of research studies in this field have discussed the operation and management of road-related assets, as information about road infrastructure plays an important role in better decision making [38]. Highway management system information is used for road management, operation, and maintenance alike.…”

Section: Highway Management System (Model) In Koreamentioning

confidence: 99%

Development of a Conceptual Data Model for 3D Geospatial Road Management Based on LandInfra Standard: A Case Study of Korea

Buuveibaatar

Lee

2022

IJGI

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In practice, road management data are typically managed in two-dimensional (2D) geospatial forms. However, 2D geographic information system (GIS)-based road infrastructure management data have limitations in their representation of complex roads, such as interchanges, bridges, and tunnels. As such, complex and large road network management data cannot be adequately managed in a 2D GIS-based form. This study discusses the use of the LandInfra standard for road infrastructure management in Korea, considering its focus on land and civil engineering infrastructure facilities. To facilitate the transition from 2D to 3D GIS, we analyzed existing road management models of road pavement and road register information and created Unified Modeling Language (UML) class diagrams depicting these models. Then, existing road management classes and LandInfra classes were mapped. Based on the results, we propose a road management model based on the Facility, Alignment, and Road parts of LandInfra. For its implementation, several classes of the proposed data model were encoded into InfraGML using real-world data input. Taken together, this study shows how the LandInfra standard can be extended and applied to the field of road infrastructure management in Korea, supporting the transition from a 2D to a 3D GIS-based model.

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Ontology-Based Information Integration: A State-of-the-Art Review in Road Asset Management

Cited by 9 publications

References 86 publications

BIM-Enabled Infrastructure Asset Management Using Information Containers and Semantic Web

BIM-Enabled Infrastructure Asset Management Using Information Containers and Semantic Web

Graph neural networks in building life cycle: a review

Development of a Conceptual Data Model for 3D Geospatial Road Management Based on LandInfra Standard: A Case Study of Korea

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