Motivated by the increasing need to handle complex, dynamic, uncertain multidimensional data in location-based warehouses, this paper proposes a novel probabilistic data model that can address the complexities of such data. The model provides a foundation for handling complex hierarchical and uncertain data, e.g., data from the location-based services domain such as transportation infrastructures and the attached static and dynamic content such as speed limits and vehicle positions. The paper also presents algebraic operators that support querying of such data. Use of pre-aggregation for implementation of the operators is also discussed. The work is motivated with a real-world case study, based on our collaboration with a leading Danish vendor of location-based services.
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