Moving Objects Databases (The Morgan Kaufmann Series in Data Management Systems) by Ralf Hartmut G?ting

by Ralf Hartmut Güting

The current trends in consumer electronics--including the use of GPS-equipped PDAs, phones, and vehicles, as well as the RFID-tag tracking and sensor networks--require the database support of a specific flavor of spatio-temporal databases. These we call Moving Objects Databases. Why do you need this book? With current systems, most data management professionals are not able to smoothly integrate spatio-temporal data from moving objects, making data from, say, the path of a hurricane very difficult to model, design, and query. Whether your field is geology, national security, urban planning, mobile computing, or almost anything in between, this book's concepts and techniques will help you solve the data management problems associated with this kind of data.Part of the Morgan Kaufmann Series in Data Management Systems.

Hardcover

First published August 23, 2005

Reviews

[Peter Aronson · Rating 3 out of 5]

It is perhaps unfortunate that despite being 18-years-old, no newer book on this subject has appeared. While it contains some useful ideas and many useful references, the actual text is less useful to a practitioner in the field than it would be to a student of computer science. This book is probably a fine (if somewhat dated) textbook, but as a coherent approach to the problem of moving object database, it has some lacks.

First, it reads like it was edited together out of papers popular in the field at the time it was written, with the result that terminology and notation, and how algorithms are presented, change from chapter to chapter. There is no synthesis, only collection of problems and incomplete solutions in no particular order and in varying degrees of detail.

It is in practical terms, gratuitously "mathy", specifying approaches mathematically when they would be clearer in English or pseudo-code or maybe even actual code (is there is no actual code in this book). Also, it repeatedly leaves off discussion of edge cases, which, if anyone has ever actually worked with geographic data, if often where 90% of the effort occurs. And there is no discussion of such necessary issues as coordinate systems or resolution or stability of algorithms. And I don't trust any of the big O notation in this book because of all the cases they hand-wave away.

This is a very academic book, and I don't mean that in a good way.

It is at its best when it drops the math and formal discussions and actually addresses the problems in natural language. And while its solutions are a real mixed bag, it does bring up a lot of interesting problems.