A survey of logical models for OLAP databases
ACM SIGMOD Record
A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
Maintaining knowledge about temporal intervals
Communications of the ACM
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Algorithms for Hierarchical Spatial Reasoning
Geoinformatica
Composing cardinal direction relations
Artificial Intelligence
Building the Data Warehouse
The objects interaction matrix for modeling cardinal directions in spatial databases
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Spatial hierarchies and topological relationships in the spatial MultiDimER model
BNCOD'05 Proceedings of the 22nd British National conference on Databases: enterprise, Skills and Innovation
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Cardinal directions have turned out to be very important qualitative spatial relations due to their numerous applications in spatial wayfinding, GIS, qualitative spatial reasoning and in domains such as cognitive sciences, AI and robotics. They are frequently used as selection criteria in spatial queries. Moving objects data warehouses can help to analyze complex multidimensional data of a spatio-temporal nature and to provide decision support. However, currently there is no available method to query for cardinal directions between spatio-temporal objects in data warehouses. In this paper, we introduce the concept of a moving objects data warehouse (MODW) for storing and querying multidimensional spatio-temporal data. Further, we also present a novel two-phase approach to model and query for cardinal directions between moving objects by using the MODW framework. First, we apply a tiling strategy that determines the zone belonging to the nine cardinal directions of each spatial object at a particular time and then intersects them. This leads to a collection of grids over time called the Objects Interaction Graticule (OIG). For each grid cell, the information about the spatial objects that intersect it is stored in an Objects Interaction Matrix. In the second phase, an interpretation method is applied to these matrices to determine the cardinal direction between the moving objects. These results are integrated into MDX queries using directional predicates.