Towards the Semantic Enrichment of Trajectories Using Spatial Data Infrastructures

Author:

Vidal-Filho Jarbas NunesORCID,Times Valéria CesárioORCID,Lisboa-Filho JugurtaORCID,Renso ChiaraORCID

Abstract

The term Semantic Trajectories of Moving Objects (STMO) corresponds to a sequence of spatial-temporal points with associated semantic information (for example, annotations about locations visited by the user or types of transportation used). However, the growth of Big Data generated by users, such as data produced by social networks or collected by an electronic equipment with embedded sensors, causes the STMO to require services and standards for enabling data documentation and ensuring the quality of STMOs. Spatial Data Infrastructures (SDI), on the other hand, provide a shared interoperable and integrated environment for data documentation. The main challenge is how to lead traditional SDIs to evolve to an STMO document due to the lack of specific metadata standards and services for semantic annotation. This paper presents a new concept of SDI for STMO, named SDI4Trajectory, which supports the documentation of different types of STMO—holistic trajectories, for example. The SDI4Trajectory allows us to propose semi-automatic and manual semantic enrichment processes, which are efficient in supporting semantic annotations and STMO documentation as well. These processes are hardly found in traditional SDIs and have been developed through Web and semantic micro-services. To validate the SDI4Trajectory, we used a dataset collected by voluntary users through the MyTracks application for the following purposes: (i) comparing the semi-automatic and manual semantic enrichment processes in the SDI4Trajectory; (ii) investigating the viability of the documentation processes carried out by the SDI4Trajectory, which was able to document all the collected trajectories.

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

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1. Handling Knowledge Over Moving Object Trajectories Using Formal Concept Analysis;Lecture Notes in Computer Science;2024

2. Identifying the cargo types of road freight with semi-supervised trajectory semantic enhancement;International Journal of Geographical Information Science;2023-11-29

3. Fog Computing for Spatial Data Infrastructure: Challenges and Opportunities;Multi-Disciplinary Applications of Fog Computing;2023-08-03

4. STO2Vec: A Multiscale Spatio-Temporal Object Representation Method for Association Analysis;ISPRS International Journal of Geo-Information;2023-05-21

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