Transportation Asset Management and Visualization Using Semantic Models and Google Earth

Abstract

Transportation asset management is important in planning and resource allocation for infrastructure maintenance, operations, and improvements. This paper presents the design and initial implementation of the kernel of a software system for asset management with the use of nonproprietary standards and open source software with state-of-the-art visualization capabilities. An innovative software design is presented; it combines semantic models of mobile and stationary transportation assets with the visualization capabilities of Google Earth. Semantic models can represent complex relationships between diverse asset classes. Semantic query across asset classes and properties is also a key feature. Google Earth is used for visualization because of its accessibility to a wide range of users and ability to combine different types of data. A visualization server was developed that implements the semantic model. The model defines stationary and mobile assets, including culverts, end treatments, and real-time traffic sensors. Spatial and semantic queries are used to construct layers displayed within Google Earth. Results show that the developed semantic models facilitate integration of software and hardware systems. Semantic modeling, using resource description framework (RDF) and web ontology language (OWL), provides a richer transportation world model than is possible with existing object-oriented or relational methods. Definition of classes and properties with a standardized syntax allows separation of design and implementation.

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