{"title":"基于图形的系统的系统架构,支持维护道路基础设施的多尺度数字孪生","authors":"Ina Heise, Sebastian Esser, André Borrmann","doi":"10.1016/j.aei.2025.103649","DOIUrl":null,"url":null,"abstract":"<div><div>Road infrastructure constitutes a complex system characterized by multiple interacting subsystems. A comprehensive understanding of the correlations and dependencies among various road infrastructure elements is essential for enhancing infrastructure management and maintenance by providing a robust foundation for decision support. Digital Twins (DT) are recognized as effective tools for facilitating such decision-making. However, the development of comprehensive DTs considering road infrastructure in its entirety is still in its early stages. Hence, this paper focuses on the conceptualization of a digital representation of road infrastructure that enables the evaluation of relationships between the various heterogeneous subsystems. To accomplish this, we apply the systems-of-systems principle to road infrastructure. At its core, Labeled Property Graphs (LPG) are employed to capture intra-subsystem relationships and inter-system linkages, facilitating a holistic representation of interactions. Furthermore, we acknowledge the current organizational status of distributed responsibilities resulting in distributed data storage and maintenance by using the concept of federated databases. The presented approach enables multi-scale evaluations of relations among road infrastructure elements while preserving the system’s scalability and the distributed management of infrastructure data. Thus, previously separate data sets can be evaluated in relation to each other on a big scale. Doing so, the presented concept provides a foundation for extensive correlation studies between different heterogeneous infrastructure datasets. The concept is validated by applying it to a large-scale real-world data set stemming from multiple Bavarian road authorities, transferring into the proposed graph structure, and demonstrating the gained capabilities through cross-domain queries and analysis.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":"68 ","pages":"Article 103649"},"PeriodicalIF":9.9000,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A graph-based systems-of-systems architecture enabling multi-scale Digital Twins for maintaining road infrastructure\",\"authors\":\"Ina Heise, Sebastian Esser, André Borrmann\",\"doi\":\"10.1016/j.aei.2025.103649\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Road infrastructure constitutes a complex system characterized by multiple interacting subsystems. A comprehensive understanding of the correlations and dependencies among various road infrastructure elements is essential for enhancing infrastructure management and maintenance by providing a robust foundation for decision support. Digital Twins (DT) are recognized as effective tools for facilitating such decision-making. However, the development of comprehensive DTs considering road infrastructure in its entirety is still in its early stages. Hence, this paper focuses on the conceptualization of a digital representation of road infrastructure that enables the evaluation of relationships between the various heterogeneous subsystems. To accomplish this, we apply the systems-of-systems principle to road infrastructure. At its core, Labeled Property Graphs (LPG) are employed to capture intra-subsystem relationships and inter-system linkages, facilitating a holistic representation of interactions. Furthermore, we acknowledge the current organizational status of distributed responsibilities resulting in distributed data storage and maintenance by using the concept of federated databases. The presented approach enables multi-scale evaluations of relations among road infrastructure elements while preserving the system’s scalability and the distributed management of infrastructure data. Thus, previously separate data sets can be evaluated in relation to each other on a big scale. Doing so, the presented concept provides a foundation for extensive correlation studies between different heterogeneous infrastructure datasets. The concept is validated by applying it to a large-scale real-world data set stemming from multiple Bavarian road authorities, transferring into the proposed graph structure, and demonstrating the gained capabilities through cross-domain queries and analysis.</div></div>\",\"PeriodicalId\":50941,\"journal\":{\"name\":\"Advanced Engineering Informatics\",\"volume\":\"68 \",\"pages\":\"Article 103649\"},\"PeriodicalIF\":9.9000,\"publicationDate\":\"2025-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Engineering Informatics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1474034625005427\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Engineering Informatics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1474034625005427","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A graph-based systems-of-systems architecture enabling multi-scale Digital Twins for maintaining road infrastructure
Road infrastructure constitutes a complex system characterized by multiple interacting subsystems. A comprehensive understanding of the correlations and dependencies among various road infrastructure elements is essential for enhancing infrastructure management and maintenance by providing a robust foundation for decision support. Digital Twins (DT) are recognized as effective tools for facilitating such decision-making. However, the development of comprehensive DTs considering road infrastructure in its entirety is still in its early stages. Hence, this paper focuses on the conceptualization of a digital representation of road infrastructure that enables the evaluation of relationships between the various heterogeneous subsystems. To accomplish this, we apply the systems-of-systems principle to road infrastructure. At its core, Labeled Property Graphs (LPG) are employed to capture intra-subsystem relationships and inter-system linkages, facilitating a holistic representation of interactions. Furthermore, we acknowledge the current organizational status of distributed responsibilities resulting in distributed data storage and maintenance by using the concept of federated databases. The presented approach enables multi-scale evaluations of relations among road infrastructure elements while preserving the system’s scalability and the distributed management of infrastructure data. Thus, previously separate data sets can be evaluated in relation to each other on a big scale. Doing so, the presented concept provides a foundation for extensive correlation studies between different heterogeneous infrastructure datasets. The concept is validated by applying it to a large-scale real-world data set stemming from multiple Bavarian road authorities, transferring into the proposed graph structure, and demonstrating the gained capabilities through cross-domain queries and analysis.
期刊介绍:
Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.