Morgan Claypool P u b l i s h e rs & w w w . m o r g a n c l a y p o o l . c o m Series Editor: M. Tamer Özsu, University of Waterloo C M & Mor g a n Cl aypool Publ i s h e rs & SYNTHESIS LECTURES ON DATA MANAGEMENT SYNTHESIS LECTURES ON DATA MANAGEMENT About SYNTHESIs This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis Lectures provide concise, original presentations of important research and development topics, published quickly, in digital and print formats. For more information visit www.morganclaypool.com M. Tamer Özsu, Series Editor ISBN: 978-1-60845-832-5 9 781608 458325 90000 Series ISSN: 2153-5418 MAMOULIS SPATIAL DATA MANAGEMENT MOR GA N & CLAY POOl Spatial Data Management Nikos Mamoulis, Hong Kong University Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R–tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high- dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Spatial Data Management Nikos Mamoulis Morgan Claypool P u b l i s h e rs & w w w . m o r g a n c l a y p o o l . c o m Series Editor: M. Tamer Özsu, University of Waterloo C M & Mor g a n C l aypool Publi s h e rs & SYNTHESIS LECTURES ON DATA MANAGEMENT SYNTHESIS LECTURES ON DATA MANAGEMENT About SYNTHESIs This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis Lectures provide concise, original presentations of important research and development topics, published quickly, in digital and print formats. For more information visit www.morganclaypool.com M. Tamer Özsu, Series Editor ISBN: 978-1-60845-832-5 9 781608 458325 90000 Series ISSN: 2153-5418 MAMOULIS SPATIAL DATA MANAGEMENT MOR GA N & CLAY POOl Spatial Data Management Nikos Mamoulis, Hong Kong University Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R–tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high- dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Spatial Data Management Nikos Mamoulis Morgan Claypool P u b l i s h e rs & w w w . m o r g a n c l a y p o o l . c o m Series Editor: M. Tamer Özsu, University of Waterloo C M & Mor g a n C l aypool Publi s h e rs & SYNTHESIS LECTURES ON DATA MANAGEMENT SYNTHESIS LECTURES ON DATA MANAGEMENT About SYNTHESIs This volume is a printed version of a work that appears in the Synthesis Digital Library of Engineering and Computer Science. Synthesis Lectures provide concise, original presentations of important research and development topics, published quickly, in digital and print formats. For more information visit www.morganclaypool.com M. Tamer Özsu, Series Editor ISBN: 978-1-60845-832-5 9 781608 458325 90000 Series ISSN: 2153-5418 MAMOULIS SPATIAL DATA MANAGEMENT MOR GA N & CLAY POOl Spatial Data Management Nikos Mamoulis, Hong Kong University Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R–tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high- dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. Spatial Data Management Nikos Mamoulis Spatial Data Management Synthesis Lectures on Data Management Editor M.Tamer Özsu, University of Waterloo The series will publish 50- to 125 page publications on topics pertaining to data management. The scope will largely follow the purview of premier information and computer science conferences, such as ACM SIGMOD, VLDB, ICDE, PODS, ICDT, and ACM KDD. Spatial Data Management Nikos Mamoulis Database Repairing and Consistent Query Answering Leopoldo Bertossi Managing Event Information: Modeling, Retrieval, and Applications Amarnath Gupta and Ramesh Jain Fundamentals of Physical Design and Query Compilation David Toman and Grant Weddell Methods for Mining and Summarizing Text Conversations Giuseppe Carenini, Gabriel Murray, and Raymond Ng Probabilistic Databases Dan Suciu, Dan Olteanu, Christopher Ré, and Christoph Koch Peer-to-Peer Data Management Karl Aberer Probabilistic Ranking Techniques in Relational Databases Ihab F. Ilyas and Mohamed A. Soliman Uncertain Schema Matching Avigdor Gal Fundamentals of Object Databases: Object-Oriented and Object-Relational Design Suzanne W. Dietrich and Susan D. Urban iii Advanced Metasearch Engine Technology Weiyi Meng and Clement T. Yu Web Page Recommendation Models: Theory and Algorithms Sule Gündüz-Ögüdücü Multidimensional Databases and Data Warehousing Christian S. Jensen,Torben Bach Pedersen, and Christian Thomsen Database Replication Bettina Kemme, Ricardo Jimenez Peris, and Marta Patino-Martinez Relational and XML Data Exchange Marcelo Arenas, Pablo Barcelo, Leonid Libkin, and Filip Murlak User-Centered Data Management Tiziana Catarci, Alan Dix, Stephen Kimani, and Giuseppe Santucci Data Stream Management Lukasz Golab and M. Tamer Özsu Access Control in Data Management Systems Elena Ferrari An Introduction to Duplicate Detection Felix Naumann and Melanie Herschel Privacy-Preserving Data Publishing: An Overview Raymond Chi-Wing Wong and Ada Wai-Chee Fu Keyword Search in Databases Jeffrey Xu Yu, Lu Qin, and Lijun Chang Copyright © 2012 by Morgan & Claypool All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher. Spatial Data Management Nikos Mamoulis www.morganclaypool.com ISBN: 9781608458325 paperback ISBN: 9781608458332 ebook DOI 10.2200/S00394ED1V01Y201111DTM021 A Publication in the Morgan & Claypool Publishers series SYNTHESIS LECTURES ON DATA MANAGEMENT Lecture #21 Series Editor: M. Tamer Özsu, University of Waterloo Series ISSN Synthesis Lectures on Data Management Print 2153-5418 Electronic 2153-5426 Spatial Data Management Nikos Mamoulis University of Hong Kong SYNTHESIS LECTURES ON DATA MANAGEMENT #21 C M & cLaypoolMorgan publishers & ABSTRACT Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R–tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains:management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking,data mining and OLAP, privacy-preserving data publishing, and spatial keyword search. KEYWORDS spatial data management,geographical information systems,indexing,query evaluation, query optimization, spatial networks To Elena, Vasili, and Dimitri for their love and support To Dimitri and Thalia for bringing me up well [...]... modern Database Management System (DBMS) The mapping of many data management tasks to spatial management problems and the maturity of the developed indexing and searching approaches for spatial data has rendered spatial data management a core database research area Spatial Database Management Systems (SDBMSs) manage large collections of spatial objects, which apart from conventional features include spatial. .. evolution of spatial data management In Chapter 2, we provide a formal overview of the most commonly used spatial data model, introduce typical spatial queries, and discuss spatial data management issues Chapter 3 overviews the spatial access methods, developed for the efficient indexing of spatial objects, with a focus on the dominant R–tree index Evaluation techniques for the most common spatial query... find application in non -spatial data management as well In many applications, data can be modeled as low-dimensional points in a feature space; then, spatial data management can be used to facilitate search or analysis Areas where spatial data management technology is commonly applied include data mining and warehousing, multimedia information systems, bioinformatics, and scientific data analysis For example,... reviewed in Chapter 4 Chapter 5 is an introduction on the management of data located on spatial (road) networks Finally, in Chapter 6, we overview recent applications of spatial data management and trends, including management of spatio-temporal data, similarity search in high-dimensional spaces, top-k and skyline queries, spatial data mining, and spatial keyword search Nikos Mamoulis November 2011 Acknowledgments... a need for the efficient management of large-scale spatial data More recently, Location Based Services (LBS) brought spatial data management needs to common users, who routinely run spatial queries on their computers or mobile devices Although the evolution of spatial data management was mainly driven by the need to provide efficient support for the ever-increasing volume of spatial information, in applications... to spatial data types, predicates, and queries Then, we discuss the necessary extensions that should be performed to a DBMS in order to effectively support spatial data management Finally, we discuss the historical evolution of SDBMSs and other applications that use spatial data management technology 1.1 SPATIAL DATA TYPES, PREDICATES, AND QUERIES The most commonly supported and frequently used spatial. .. handle spatial data Since 1995, Informix (later acquired by IBM) includes spatial data support and an R–tree index implementation Oracle included basic spatial data capabilities as early as 1984 When Oracle 8 was released in 1997, it included the Oracle Spatial extension, with mature spatial indexing and search support IBM DB2 includes a Spatial Extender since the late 1990’s, which supports spatial data. .. evaluation Finally, Chapter 6 overviews recent developments and trends on spatial data management, including management of spatio-temporal data, similarity search in high-dimensional spaces, top-k and skyline queries, spatial data mining, and spatial keyword search BIBLIOGRAPHIC NOTES There are several textbooks devoted to spatial data management The textbook by Shekhar and Chawla [2003], based on an earlier... DEVELOPMENT As in most technology fields, in spatial data management, research precedes development In the 1980’s, spatial data management started as an extension to the existing relational database technology to support the more complex data types found in geographical information systems In this first decade, the research focus was on appropriate index methods for spatial data, given the inadequacy of relational... products to handle spatial data Examples include the IBM DB2 Spatial Extender, Oracle Spatial, and Microsoft SQL Server 2008 Open-source database products followed a similar path (e.g., PostGIS in PostgreSQL, MySQL, SpatiaLite in SQLite), showing that the support of location and geometry types is essential in any DBMS Besides database engines, GIS products traditionally support spatial database management . 2153-5418 MAMOULIS SPATIAL DATA MANAGEMENT MOR GA N & CLAY POOl Spatial Data Management Nikos Mamoulis, Hong Kong University Spatial database management deals. 2153-5418 MAMOULIS SPATIAL DATA MANAGEMENT MOR GA N & CLAY POOl Spatial Data Management Nikos Mamoulis, Hong Kong University Spatial database management deals