Definition
ConsiderNregions R 1 , R 2 ,…,R N and a time axis consisting of discrete timestamps 1, 2,…,T, where T represents the total number of recorded timestamps (i.e., the length of history). The position and area of a region R i may vary along with time, and its extent at timestamp t is denoted as R i (t). Each region carries a set of measures R i (t).ms, also called the aggregate data of R i (t). The measures of regions change asynchronously with their extents. In other words, the measure of R i (1 ≤ i ≤ N) may change at a timestamp t (i.e., R i (t).ms ≠ R i (t − 1).ms), while its extent remains the same (i.e., \( {R}_i(t) = {R}_i\left(t-1\right) \)), and vice versa.
A spatio-temporal data warehouse stores the above information, and efficiently answers the spatio-temporal window aggregate query, which specifies an area q R and a time interval q T of continuous timestamps. The goal is to return the...
Keywords
- Spatio-temporal Data Warehouse
- On-Line Analytical Processing (OLAP)
- Host Index
- OLAP Operations
- OLAP Applications
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Tao, Y., Papadias, D. (2014). Spatio-Temporal Data Warehouses. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_362-2
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_362-2
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