Open AccessJournal Article
Indexing and Retrieval of Historical Aggregate Information about Moving Objects
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TLDR
This paper argues that the spatial and temporal dimensions should be modeled as a combined dimension on the data cube and present data structures, which integrate spatiotemporal indexing with pre-aggregation, and develops methods that utilize the proposed structures for efficient execution of ad-hoc group-bys.Abstract:
Spatio-temporal databases store information about the positions of individual objects over time. In many applications however, such as traffic supervision or mobile communication systems, only summarized data, like the average number of cars in an area for a specific period, or phones serviced by a cell each day, is required. Although this information can be obtained from operational databases, its computation is expensive, rendering online processing inapplicable. A vital solution is the construction of a spatiotemporal data warehouse. In this paper, we describe a framework for supporting OLAP operations over spatiotemporal data. We argue that the spatial and temporal dimensions should be modeled as a combined dimension on the data cube and present data structures, which integrate spatiotemporal indexing with pre-aggregation. While the well-known materialization techniques require a-priori knowledge of the grouping hierarchy, we develop methods that utilize the proposed structures for efficient execution of ad-hoc group-bys. Our techniques can be used for both static and dynamic dimensions.read more
Citations
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Journal ArticleDOI
Indexing spatiotemporal archives
TL;DR: A number of algorithms and heuristics are elaborated that can be used to preprocess a spatiotemporal archive in order to produce finer object approximations, which will greatly improve query performance in comparison to the straightforward approaches.
Proceedings Article
Indexing Spatiotemporal Archives.
TL;DR: In this article, a robust indexing scheme for answering spatiotemporal queries more efficiently is proposed, where a number of algorithms and heuristics are elaborated that can be used to preprocess a spatio-temporal archive in order to produce finer object approximations, which, in combination with a multiversion index structure, will greatly improve query performance.
Proceedings ArticleDOI
Efficient trajectory joins using symbolic representations
TL;DR: This paper considers how to efficiently evaluate trajectory joins, i.e., how to identify all pairs of similar trajectories between two datasets, and proposes a pruning heuristic for reducing the number of trajectory pairs that need to be examined.
Proceedings ArticleDOI
Time relaxed spatiotemporal trajectory joins
TL;DR: An experimental study revealing the advantages of using two important heuristics that turn the symbolic represenation approach effective for TRSTJ queries for solving Time Relaxed Spatiotemporal Trajectory Join queries.
Book ChapterDOI
Multidimensional structures dedicated to continuous spatiotemporal phenomena
TL;DR: This paper will introduce mechanisms, based on interpolation, to spatial and temporal dimensions which will give the user the impression of navigating in a continuous hypercube and propose a multidimensional model and some operations used for an OLAP of field-based data.
References
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Proceedings ArticleDOI
R-trees: a dynamic index structure for spatial searching
TL;DR: A dynamic index structure called an R-tree is described which meets this need, and algorithms for searching and updating it are given and it is concluded that it is useful for current database systems in spatial applications.
Proceedings ArticleDOI
The R*-tree: an efficient and robust access method for points and rectangles
TL;DR: The R*-tree is designed which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory which clearly outperforms the existing R-tree variants.
Posted Content
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Jim Gray,Surajit Chaudhuri,Adam Bosworth,Andrew Layman,Don Reichart,Murali Venkatrao,Frank Pellow,Hamid Pirahesh +7 more
TL;DR: The cube operator as discussed by the authors generalizes the histogram, cross-tabulation, roll-up, drill-down, and sub-total constructs found in most report writers, and treats each of the N aggregation attributes as a dimension of N-space.
Book
The data warehouse toolkit: practical techniques for building dimensional data warehouses
TL;DR: This definitive guide succinctly explains how to build a data warehouse by using actual case studies of existing data warehouses developed for specific types of business applications such as retail, manufacturing, banking, insurance, subcriptions and airline reservations.
Journal ArticleDOI
An asymptotically optimal multiversion B-tree
TL;DR: A multiversion B-tree that supports insertions and deletions of data items at the current version and range queries and exact match queries for any version, current or past and is asymptotically optimal.