Query Transformation Method by Delaunay Triangulation for Multi-Source Distributed Spatial Database Systems Jung-Rae Hwang, Ji-Hyeon Oh, and Ki-Joune Li Spatiotemporal Database Lab. Pusan National University, South Korea {jrhwang,jhoh}@quantos.cs.pusan.ac.kr, lik@hyowon.cc.pusan.ac.kr / / ABSTRACT One of the difficulties in building a distributed GIS comes from the heterogeneity of spatial databases. In particular, positional mismatches between spatial databases arise due to several reasons, such as different scales, or different ground control points. They result in unreliable outputs of query processing. One simple solution is to correct positional data in spatial databases at each site, according to the most accurate one. This solution is however not practical in most of the cases where the autonomy of each database should be respected. In this paper, we propose a spatial query processing method without correcting positional data in each spatial database. Instead of correcting positional data, we dynamically transform a given query region or position onto each space where spatial objects of each site are located. Our method is based on an elastic transformation method by delaunay triangulation. 1 INTRODUCTION In recent years, the need has arisen for accessing data from distributed and preexisting spatial database systems or GIS. In order to realize a distributed spatial database system, we should overcome several problems, one of which comes from the heterogeneity of spatial databases. The heterogeneity includes a number of issues from spatial database management systems to data models. In this paper, we focus on the inconsistency of positional data between local spatial databases. The positional mismatches of spatial databases come from several reasons. Different organizations with their own acquisition and management policy of data may have inconsistent positional data. Different scales or accuracy are important reasons of the mismatches as well. Inconsistent positional data often comes from different surveying methods and different ground control points. And mismatches are often found when we merge two adjacent maps. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Copyright 2001 ACM XXXXXXXXX/XX/XX ...$5.00. Suppose that we have two different spatial databases, one for buildings and another for roads and traffic conditions. When the databases have been independently constructed, they may include mismatching positional data. If a user gives a query, “find the nearest object to point p” on these two databases at the same time, the query point p may be differently considered by each database and the system will give incorrect answers to the query as shown by figure 1. Since the user is normally ignorant in positional mismatches between two databases, he cannot specify different query positions for each database respectively, but the system is in charge of giving correct answer to the query regardless of the mismatches./ Figure 1. Positional Mismatch and Example of Query A number of researches and efforts have been done to resolve the heterogeneity of functions, data models and schemas in spatial database systems and GIS. The standardizations by ISO TC/211[7,8] and OGC (OpenGIS Consortium)[9] are important efforts to overcome the heterogeneity. But the heterogeneity of contents in spatial databases has been paid attention by very few works. In this paper, we propose a query processing method for distributed spatial database systems, where they have positional mismatches. In section 2, we will give a survey on related work and introduce the motivation of this paper. And in the next section, we will explain an elastic transformation method by delaunay triangulation, which is a fundamental concept of our method. We will propose our query processing method in section 4, and conclude this paper in section 5. 2 Related Work and Motivation As other types of databases, the heterogeneity problems arise in Site A Site B Query Point p B p A Correct Answer Result of Query Processing