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Mobility Data: Modeling, Management, and Understanding

Hardback

Main Details

Title Mobility Data: Modeling, Management, and Understanding
Authors and Contributors      Edited by Chiara Renso
Edited by Stefano Spaccapietra
Edited by Esteban Zimanyi
Physical Properties
Format:Hardback
Pages:378
Dimensions(mm): Height 242,Width 162
Category/GenreDatabases
ISBN/Barcode 9781107021716
ClassificationsDewey:005.74
Audience
Professional & Vocational
Illustrations 6 Tables, unspecified; 14 Plates, color; 30 Halftones, unspecified; 65 Line drawings, unspecified

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 14 October 2013
Publication Country United Kingdom

Description

Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make it manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.

Author Biography

Chiara Renso is a permanent researcher at the Institute of Information Science and Technologies at the Italian National Research Council, Italy. Her research interests are related to spatio-temporal data mining, reasoning, data mining query languages, semantic data mining, and trajectory data mining. Stefano Spaccapietra is an honorary professor at the School of Computer and Communication Sciences, Swiss Federal Institute of Technology, in Lausanne, Switzerland, where he has been chairing the database laboratory for more than twenty years. Together with Christine Parent, he developed MADS, a conceptual spatio-temporal data model equipped with multi-representation support, which gained worldwide renown and has been used in several applications. Esteban Zimanyi is a Professor and Director of the Department of Computer and Decision Engineering of the Universite Libre de Bruxelles. His current research interests include business intelligence, geographic information systems, spatio-temporal databases, data warehouses, and Semantic Web. He has co-authored two books and co-edited four books in the domains of spatio-temporal modeling, spatio-temporal data warehouses, and business intelligence.