Semantic Data Warehouse Modelling for Trajectories
Michael Mireku Kwakye

TL;DR
This paper presents a semantic data warehouse framework for trajectories, enabling enhanced analysis and inference of movement patterns through ontology-based modeling and semantic enrichment.
Contribution
It introduces a generic ontology modeling framework for semantic trajectory data warehouses, facilitating adaptable, high-granularity data processing and advanced trend analysis.
Findings
Supports semantic inference for trajectory data
Enables predictive trend analysis in movement data
Provides a flexible modeling platform for various domains
Abstract
The trajectory patterns of a moving object in a spatio-temporal domain offers varied information in terms of the management of the data generated from the movement. A trajectory data warehouse is a data repository for the data and information of trajectory objects and their associated spatial objects for defined temporal periods. The query results of trajectory objects from the data warehouse are usually not enough to answer certain trend behaviours and meaningful inferences without the associated semantic information of the trajectory object or the geospatial environment within a specified purpose or context. This paper formulates and designs a generic ontology modelling framework that serves as the background model platform for the design of a semantic data warehouse for trajectories. This semantic trajectory data warehouse can be adaptable for trajectory data processing and analytics…
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