The Consistency of Relational Database and Object-Relational Database in GIS Applications

This final year project involves a research and a simple Geographical Information System (GIS) application that will show GIS, spatial data, spatial database management, which focused on relational and object-relational database management system. The main objectives of this project is to study and gain deeper understanding on the implementation of the two types of databases in GIS applications, to compare the level of performance between the databases in a GIS application and to determine the most suggested database to be implemented in a GIS application. The scope of the study will focus on integrating a GIS application that implements Malacca spatial database with two different database management system, namely relational database and objectrelational database system. The performance of each database system will be identified and compared. Rapid Development environment methodology will be utilized in the research on the performance of relational and object-relational databases in GIS applications and also in the development of an application that will implement the database with GIS applications. This methodology basically involved overlapping Planning, Analysis, Design and Implementation phases. Database development design process involved conceptual, logical and physical design stages. This report also includes discussions on the consistency of relational database as well as of the objectrelational database in GIS applications. This report suggests GIS application developer to choose object-relational database in order to manage both spatial and attributes data for the applications efficiently. Furthermore, the result from the object-relational database will be more consistent and reliable compared to a relational database and the performance is better. Recommendations for continuing this project are to compare and determine the level of consistency between relational database and object-relational database in World Wide Web environment or with multi-user accessing the database concurrently in order to study on the effects to the level of consistency and also to develop a map query interface

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

Semantic Storage: Overview and Assessment

The Semantic Web has a great deal of momentum behind it. The promise of a ‘better web’, where information is given well defined meaning and computers are better able to work with it has captured the imagination of a significant number of people, particularly in academia. Language standards such as RDF and OWL have appeared with remarkable speed, and development continues apace. To back up this development, there is a requirement for ‘semantic databases’, where this data can be conveniently stored, operated upon, and retrieved. These already exist in the form of triple stores, but do not yet fulfil all the requirements that may be made of them, particularly in the area of performing inference using OWL. This paper analyses the current stores along with forthcoming technology, and finds that it is unlikely that a combination of speed, scalability, and complex inferencing will be practical in the immediate future. It concludes by suggesting alternative development routes