Spatial databases accomplishments and research needs

Shashi Shekhar, Sanjay Chawla, Siva Ravada, Andrew Fetterer, Xuan Liu, Chang Tien Lu

Research output: Contribution to journalArticlepeer-review

119 Scopus citations

Abstract

Spatial databases, addressing the growing data management and analysis needs of spatial applications such as Geographic Information Systems, have been an active area of research for more than two decades. This research has produced a taxonomy of models for space, spatial data types and operators, spatial query languages and processing strategies, as well as spatial indexes and clustering techniques. However, more research is needed to improve support for network and field data, as well as query processing (e.g., cost models, bulk load). Another important need is to apply spatial data management accomplishments to newer applications, such as data warehouses and multimedia information systems. The objective of this paper is to identify recent accomplishments and associated research needs of the near term.

Original languageEnglish (US)
Pages (from-to)45-55
Number of pages11
JournalIEEE Transactions on Knowledge and Data Engineering
Volume11
Issue number1
DOIs
StatePublished - 1999

Bibliographical note

Funding Information:
This work is sponsored, in part, by the United States Army High Performance Computing Research Center under the auspices of the Department of the Army, Army Research Laboratory Cooperative Agreement No. DAAH04-95-2-0003 and Contract No. DAAH04-95-C-0008, the contents of which do not necessarily reflect the position or the policy of the government; no official govenmental endorsement should be inferred. This work was also supported, in part, by the National Science Foundation under Grant No. 9631539. We thank Professor Jaideep Srivastava for technical commentary and Christiane McCarthy for helping to improve the readability of the paper.

Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.

Keywords

  • Databases
  • Geographic information systems
  • Multidimensional
  • Object-relational
  • Spatial databases

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