Abstract
Modeling spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems, computer vision, environmental data management systems, etc. Because of complex requirements, it is challenging to represent spatiotemporal data and its features in databases and to effectively query them. This article presents a new approach to model and query the spatiotemporal data of fuzzy spatial and complex objects and/or spatial relations. In our case study, we use a meteorological database application in an intelligent database architecture, which combines an object-oriented database with a knowledgebase for modeling and querying spatiotemporal objects.
| Original language | English |
|---|---|
| Pages (from-to) | 3665-3682 |
| Number of pages | 18 |
| Journal | Information Sciences |
| Volume | 178 |
| Issue number | 19 |
| DOIs | |
| Publication status | Published - Oct 1 2008 |
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Keywords
- Fuzzy logic
- Knowledgebase
- Meteorological database application
- Object-oriented database
- Spatiotemporal data
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Information Systems
- Information Systems and Management
- Statistics, Probability and Uncertainty
- Electrical and Electronic Engineering
- Statistics and Probability
Cite this
Modeling and querying fuzzy spatiotemporal databases. / Sözer, Aziz; Yazici, Adnan; Oǧuztüzün, Halit; Taş, Osman.
In: Information Sciences, Vol. 178, No. 19, 01.10.2008, p. 3665-3682.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Modeling and querying fuzzy spatiotemporal databases
AU - Sözer, Aziz
AU - Yazici, Adnan
AU - Oǧuztüzün, Halit
AU - Taş, Osman
PY - 2008/10/1
Y1 - 2008/10/1
N2 - Modeling spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems, computer vision, environmental data management systems, etc. Because of complex requirements, it is challenging to represent spatiotemporal data and its features in databases and to effectively query them. This article presents a new approach to model and query the spatiotemporal data of fuzzy spatial and complex objects and/or spatial relations. In our case study, we use a meteorological database application in an intelligent database architecture, which combines an object-oriented database with a knowledgebase for modeling and querying spatiotemporal objects.
AB - Modeling spatiotemporal data, in particular fuzzy and complex spatial objects representing geographic entities and relations, is a topic of great importance in geographic information systems, computer vision, environmental data management systems, etc. Because of complex requirements, it is challenging to represent spatiotemporal data and its features in databases and to effectively query them. This article presents a new approach to model and query the spatiotemporal data of fuzzy spatial and complex objects and/or spatial relations. In our case study, we use a meteorological database application in an intelligent database architecture, which combines an object-oriented database with a knowledgebase for modeling and querying spatiotemporal objects.
KW - Fuzzy logic
KW - Knowledgebase
KW - Meteorological database application
KW - Object-oriented database
KW - Spatiotemporal data
UR - http://www.scopus.com/inward/record.url?scp=47849099587&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47849099587&partnerID=8YFLogxK
U2 - 10.1016/j.ins.2008.05.034
DO - 10.1016/j.ins.2008.05.034
M3 - Article
VL - 178
SP - 3665
EP - 3682
JO - Information Sciences
JF - Information Sciences
SN - 0020-0255
IS - 19
ER -