Towards spatio‐temporal data modeling of geo‐tagged shipping information

Abstract

Spatio-temporal data models deal with capturing information characterized by both spatial and temporal semantics. In this paper we review current approaches for spatio-temporal data modelling and present out initial results for selecting the most relevant approach: Object-Oriented modeling for means of modeling geo-tagged shipping information. The shipping information is provided by the well-known LLLOYD’s lists dataset. We have introduced the case study and dataset characteristics used in the research project and presented our data model in Unified Modeling Language (UML). The model focuses on spatio-temporal events where characteristics are categorized as thematic, spatial and temporal attributes. The paper follows up with discussion on the selected approach and results, and finally ends with presenting the future outlook.