Spatio Temporal Databases

Spatio-Temporal Databases explores recent trends in flexible querying and reasoning about time- and space-related information in databases. It shows how flexible querying enhances standard querying expressiveness in many different ways, with the aim of facilitating extraction of relevant data and information. Flexible spatial and temporal reasoning denotes qualitative reasoning about dynamic changes in the spatial domain, characterized by imprecision or uncertainty (or both). Many of the contributions focus on GIS, while some others are more general, or focus on related application fields, presenting theoretical viewpoints and techniques that are inspiring or can be adapted for GIS. The first part bundles the contributions on advances at the theoretical level, also discussing examples and opening further perspectives. The second part presents contributions on well-developed applications. The authors explain how to handle imprecision and uncertainty, demonstrating how advanced techniques can help to solve diverse problems related to GIS.

A summary of research carried out in the CHOROCHRONOS Project, established as an EC-funded Training and Mobility Research Network with the objective of studying the design, implementation, and application of spatio-temporal database management systems. The nine coherent chapters by leading research groups are written in a tutorial style, making the research contributions of the project accessible to a wider audience interested in spatio-temporal information processing. Following an introductory overview, the book presents chapters on ontologies for spatio-temporal databases, conceptual models, spatio-temporal models and languages, access methods and query processing, architectures and implementation of spatio-temporal DBMS, interactive spatio-temporal documents, and future perspectives.

This book constitutes the refereed proceedings of the International Workshop on Spatio-Temporal Database Management Systems, STDBM'99, held in Edinburgh, UK, in September 1999 as a satelite event of VLDB'99. The 13 revised full papers presented were carefully selected from 30 papers submitted. The book offers topical sections on understanding and manipulating spatio-temporal data; integration, exchange, and visualization; query processing; index evaluation; and constraints and dependencies.

Temporal database systems are systems that provide special support for storing, querying, and updating historical and/or future data. Current DBMSs provide essentially no temporal features at all, but this situation is likely to change soon for a variety of reasons; in fact, temporal databases are virtually certain to become important sooner rather than later, in the commercial world as well as in academia. This book provides an in-depth description of the foundations and principles on which those temporal DBMSs will be built. These foundations and principles are firmly rooted in the relational model of data; thus, they represent an evolutionary step, not a revolutionary one, and they will stand the test of time. This book is arranged in three parts and a set of appendixes: * Preliminaries: Provides a detailed review of the relational model, and an overview of the Tutorial D language. * Laying the Foundations: Explains basic temporal data problems and introduces fundamental constructs and operators for addressing those problems. * Building on the Foundations: Applies the material of the previous part to issues of temporal database design, temporal constraints, temporal query and update, and much more. * Appendixes: Include annotated references and bibliography, implementation considerations, and other topics. Key features: * Describes a truly relational approach to the temporal data problem. * Addresses implementation as well as model issues. * Covers recent research on new database design techniques, a new normal form, new relational operators, new update operators, a new approach to the problem of "granularity," support for "cyclic point types," and other matters. * Includes review questions and exercises in every chapter. * Suitable for both reference and tutorial purposes.

Time and Relational Theory provides an in-depth description of temporal database systems, which provide special facilities for storing, querying, and updating historical and future data. Traditionally, database management systems provide little or no special support for temporal data at all. This situation is changing because: Cheap storage enables retention of large volumes of historical data in data warehouses Users are now faced with temporal data problems, and need solutions Temporal features have recently been incorporated into the SQL standard, and vendors have begun to add temporal support to their DBMS products Based on the groundbreaking text Temporal Data & the Relational Model (Morgan Kaufmann, 2002) and new research led by the authors, Time and Relational Theory is the only book to offer a complete overview of the functionality of a temporal DBMS. Expert authors Nikos Lorentzos, Hugh Darwen, and Chris Date describe an approach to temporal database management that is firmly rooted in classical relational theory and will stand the test of time. This book covers the SQL:2011 temporal extensions in depth and identifies and discusses the temporal functionality still missing from SQL. Understand how the relational model provides an ideal basis for taming the complexities of temporal databases Learn how to analyze and evaluate commercial temporal products with this timely and important information Be able to use sound principles in designing and using temporal databases Understand the temporal support recently added to SQL with coverage of the new SQL features in this unique, accurate, and authoritative reference Appreciate the benefits of a truly relational approach to the problem with this clear, user friendly presentation

"This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher.

This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobile phone calls and are designed around cellular towers and places of interest. Density-based pattern queries capture the aggregate behavior of trajectories as groups. Several evaluation algorithms are presented for finding groups of trajectories that move together in space and time, i.e. within a predefined distance to each other. Finally, the brief describes a generic framework, called DivDB, for diversifying query results. Two new evaluation methods, as well as several existing ones, are described and tested in the proposed DivDB framework. The efficiency and effectiveness of all the proposed complex motion pattern queries are demonstrated through an extensive experimental evaluation using real and synthetic spatio-temporal databases. This clear evaluation of new query processing techniques makes Spatio-Temporal Database a valuable resource for professionals and researchers studying databases, data mining, and pattern recognition.