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Spatial Data Structures
, 1995
"... An overview is presented of the use of spatial data structures in spatial databases. The focus is on hierarchical data structures, including a number of variants of quadtrees, which sort the data with respect to the space occupied by it. Suchtechniques are known as spatial indexing methods. Hierarch ..."
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Cited by 287 (13 self)
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An overview is presented of the use of spatial data structures in spatial databases. The focus is on hierarchical data structures, including a number of variants of quadtrees, which sort the data with respect to the space occupied by it. Suchtechniques are known as spatial indexing methods. Hierarchical data structures are based on the principle of recursive decomposition. They are attractive because they are compact and depending on the nature of the data they save space as well as time and also facilitate operations such as search. Examples are given of the use of these data structures in the representation of different data types such as regions, points, rectangles, lines, and volumes.
An asymptotically optimal multiversion Btree
, 1996
"... In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion Btree that supports insertions and deletions of data ite ..."
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Cited by 162 (8 self)
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In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion Btree 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. Our multiversion Btree is asymptotically optimal in the sense that the time and space bounds are asymptotically the same as those of the (singleversion) Btree in the worst case. The technique we present for transforming a (singleversion) Btree into a multiversion Btree is quite general: it applies to a number of hierarchical external access structures with certain properties directly, and it can be modified for others.
A Survey of Research on Deductive Database Systems
 JOURNAL OF LOGIC PROGRAMMING
, 1993
"... The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems. ..."
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Cited by 100 (6 self)
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The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems.
A DistanceScan Algorithm for Spatial Access Structures
, 1994
"... In geographic information systems it is often useful to select an object located closest to a given point or to scan the objects with respect to their distance to a given point in ascending order. An example for a query of this type would be to retrieve ten hotels with at least three stars lying clo ..."
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Cited by 30 (5 self)
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In geographic information systems it is often useful to select an object located closest to a given point or to scan the objects with respect to their distance to a given point in ascending order. An example for a query of this type would be to retrieve ten hotels with at least three stars lying closest to the venue of a conference. Various subtypes of similar queries exist. On the other hand, research in geometric access structures has concentrated mainly on range queries. We present an efficient algorithm for closest and distancescanqueries of various kinds. Our algorithm is based on the nearest neighbour algorithm for kdtrees given by Friedman et al. [FBF77] and refined by Sproull [Spr91]. We adapt this algorithm to external access structures and extend it to process a broader class of queries. Furthermore we show that the algorithm can be applied to point objects as well as to nonpoint objects, and that it can be used with all spatial access structures using a hierarchical dir...
The Application of Spacefilling Curves to the Storage and Retrieval of Multidimensional Data
, 2000
"... Indexing of multidimensional data has been the focus of a considerable amount of research effort over many years but no generally agreed paradigm has emerged to compare with the impact of the BTree, for example, on the indexing of onedimensional data. At the same time, the need for efficient meth ..."
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Cited by 16 (3 self)
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Indexing of multidimensional data has been the focus of a considerable amount of research effort over many years but no generally agreed paradigm has emerged to compare with the impact of the BTree, for example, on the indexing of onedimensional data. At the same time, the need for efficient methods is ever more important in an environment where databases become larger and more complex in their structures. Mapping multidimensional data to one dimension, thus enabling onedimensional access methods to be exploited, has been suggested in the literature but for the most part interest has been confined to the Zorder curve. The possibility of using other curves, such as the Hilbert and Graycode curves, whose characteristics differ from those of the Zorder curve, has also been suggested. In this thesis we design and implement a working le store which is underpinned by the principle of mapping multidimensional data to one of a variety of spacefilling curves and their variants. Data is then indexed using a B+ Tree which remains compact, regardless of the volume and number of dimensions. The implementation has entailed developing
Extending a spatial access structure to support additional standard attributes
, 1995
"... In recent years, many access structures have been proposed supporting access to objects via their spatial location. However, additional nongeometric properties are always associated with geometric objects, and in practice it is often necessary to use select conditions based on spatial and standard ..."
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Cited by 11 (4 self)
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In recent years, many access structures have been proposed supporting access to objects via their spatial location. However, additional nongeometric properties are always associated with geometric objects, and in practice it is often necessary to use select conditions based on spatial and standard attributes. An obvious idea to improve the performance of queries with mixed select conditions is to extend spatial access structures with additional dimensions for standard attributes. Whereas this idea seems to be simple and promising at rst glance, a closer look brings up serious problems, especially with select conditions containing arithmetic expressions or select conditions for nonpoint objects and with Boolean operators like or and not. In this paper we present a solution to overcome the problems sketched above which is based on three pillars: (1) We present powerful basic techniques to deal with arithmetic conditions containing mathematical operations (like `+', `;', ` ', and `=') and range queries for nonpoint objects. (2) We introduce a technique which allows to decompose select conditions containing Boolean operators and to reduce the processing of such a select condition to the processing of its elementary parts. (3) We showhow other operations like joins and distancescans can be integrated into this query processing architecture.
Adapting the Transformation Technique to Maintain MultiDimensional NonPoint Objects in kdTree Based Access Structures
 PROC. 3RD ACM INT. WORKSHOP ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACMGIS '95)
, 1995
"... In [10, 18] the transformation technique has been proposed to store kdimensional intervals  which serve as bounding boxes for arbitrary geometric objects in many applications  as 2kdimensional points in a point access structure. Unfortunately the transformation technique has two pitfalls: (1) ..."
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Cited by 4 (0 self)
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In [10, 18] the transformation technique has been proposed to store kdimensional intervals  which serve as bounding boxes for arbitrary geometric objects in many applications  as 2kdimensional points in a point access structure. Unfortunately the transformation technique has two pitfalls: (1) The transformation leads to a skew distribution of the 2kdimensional image points. (2) Processing a range query searching all objects intersecting a given query region, there is a mismatch between thekdimensional query region and the 2kdimensional access structure. In this paper we propose two techniques to overcome these problems which can be directly applied tokdtree based point access structures: (1) We present a sophisticated split strategy to determine the split dimension and the split position in case of a bucket split which exploits the knowledge about the distribution of the image points of the transformation technique to gain an extremely exible and robust access structure. (2) We propose a retransformation of the 2kdimensional data regions in the access structure into the originalkdimensional data space in order to compare these regions with thekdimensional query region. Furthermore we state experimental results, which demonstrate, that the presented techniques allow to maintainkdimensional nonpoint objects with nearly the same performance as kdimensional point objects.
Efficient Window Block Retrieval in QuadtreeBased Spatial Databases
 GeoInformatica
, 1996
"... An algorithm is presented to answer window queries in a quadtreebased spatial database environment by retrieving all of the quadtree blocks in the underlying spatial database that cover the quadtree blocks that comprise the window. It works by decomposing the window operation into suboperations ov ..."
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Cited by 3 (2 self)
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An algorithm is presented to answer window queries in a quadtreebased spatial database environment by retrieving all of the quadtree blocks in the underlying spatial database that cover the quadtree blocks that comprise the window. It works by decomposing the window operation into suboperations over smaller window partitions. These partitions are the quadtree blocks corresponding to the window. Although a block b in the underlying spatial database may cover several of the smaller window partitions, b is only retrieved once rather than multiple times. This is achieved by using an auxiliary main memory data structure called the active border which requires O(n) additional storage for a window query of size n \Theta n. As a result, the algorithm generates an optimal number of disk I/O requests to answer a window query (i.e., one request per covering quadtree block). A proof of correctness and an analysis of the algorithm's execution time and space requirements are given, as are some ex...
Die Nutzung mehrdimensionaler Zugriffsstrukturen für Anfragen über Standardattributen
 IN PROC. GIFACHTAGUNG DATENBANKSYSTEME IN BURO, TECHNIK UND WISSENSCHAFT
, 1995
"... In den vergangenen Jahren hat es zahlreiche vielversprechende ..."
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Cited by 1 (1 self)
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In den vergangenen Jahren hat es zahlreiche vielversprechende