A Model Comparison for Spatiotemporal Data in Ubiquitous Environments: A Case Study
Author(s) -
S. Y. Noh,
Shashi K. Gadia
Publication year - 2011
Publication title -
journal of information processing systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.288
H-Index - 23
eISSN - 2092-805X
pISSN - 1976-913X
DOI - 10.3745/jips.2011.7.4.635
Subject(s) - computer science , tuple , ubiquitous computing , data model (gis) , context (archaeology) , data modeling , process (computing) , temporal database , data mining , object (grammar) , query language , database , artificial intelligence , human–computer interaction , paleontology , mathematics , discrete mathematics , biology , operating system
In ubiquitous environments, many applications need to process data with time and space dimensions. Because of this, there is growing attention not only on gathering spatiotemporal data in ubiquitous environments, but also on processing such data in databases. In order to obtain the full benefits from spatiotemporal data, we need a data model that naturally expresses the properties of spatiotemporal data. In this paper, we introduce three spatiotemporal data models extended from temporal data models. The main goal of this paper is to determine which data model is less complex in the spatiotemporal context. To this end, we compare their query languages in the complexity aspect because the complexity of a query language is tightly coupled with its underlying data model. Throughout our investigations, we show that it is important to intertwine space and time dimensions and keep one-to-one correspondence between an object in the real world and a tuple in a database in order to naturally express queries in ubiquitous applications.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom