From environmental management to land planning and geo-marketing, the number of application domains that may greatly benefit from using data enriched with spatio-temporal features is expanding very rapidly. This book shows that a conceptual design approach for spatio-temporal databases is both feasible and easy to apprehend. While providing a firm basis through extensive discussion of traditional data modeling concepts, the major focus of the book is on modeling spatial and temporal information.

The growing emphasis on complexity concerns for ontologies has attracted signi cant interest from both the researchers' and the practitioners' communities in modularization techniques as a way to decrease the complexity of managing huge ontologies.Researchhasproducedmanycomplementaryandcompetingapproaches, mainly with the goal of supportingpractitioners' methodologieswith sound and p- cisely de nedfoundationsand alternatives.Existing prototypessubstantiate research results and experimental evaluations have been performed. Thus, a large body of work is available. This book has been designed to provide the reader with a detailed analysis of where we stand today and which concepts, theories and techniques for knowledge modularization we can con dently rely on. The material for the book has been - lected from research achievements that are mature enough to be considered as a rm and reliable basis on which to inspire further work and to develop solutions in c- crete environments. The content of the book has been organized in three parts. Part I holds a general introductionto theidea andissuescharacterizingmodularization.Thisisfollowedby three chapters that offer an in-depth analysis of properties, criteria and knowledge import techniques for modularization. The last chapter discusses one of the three approaches that implement the modularization idea. The two other approaches are covered in detail in parts II and III.

This book constitutes the refereed proceedings of the 26th International Conference on Conceptual Modeling, ER 2007, held in Auckland, New Zealand, in November 2007.

The 37 revised full papers presented together with 3 keynote lectures were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on data warehousing and data mining, design methodologies and tools, information and database integration, information modelling concepts and ontologies, integrity constraints, logical foundations of conceptual modelling, patterns and conceptual meta-modelling, requirements elicitation, reuse and reengineering, semi-structured data and XML, as well as Web information systems and XML.

From environmental management to land planning and geo-marketing, the number of application domains that may greatly benefit from using data enriched with spatio-temporal features is expanding very rapidly. Unfortunately, development of new spatio-temporal applications is hampered by the lack of conceptual design methods suited to cope with the additional complexity of spatio-temporal data. This complexity is obviously due to the particular semantics of space and time, but also to the need for multiple representations of the same reality to address the diversity of requirements from highly heterogeneous user communities. Conceptual design methods are also needed to facilitate the exchange and reuse of existing data sets, a must in geographical data management due to the high collection costs of the data. Yet, current practice in areas like geographical information systems or moving objects databases does not include conceptual design methods very well, if at all.

This book shows that a conceptual design approach for spatio-temporal databases is both feasible and easy to apprehend. While providing a firm basis through extensive discussion of traditional data modeling concepts, the major focus of the book is on modeling spatial and temporal information. Parent, Spaccapietra and Zimanyi provide a detailed and comprehensive description of an approach that fills the gap between application conceptual requirements and system capabilities, covering both data modeling and data manipulation features. The ideas presented summarize several years of research on the characteristics and description of space, time, and perception. In addition to the authors' own data modeling approach, MADS (Modeling of Application Data with Spatio-temporal features), the book also surveys alternative data models and approaches (from industry and academia) that target support of spatio-temporal modeling.

The reader will acquire intimate knowledge of both the traditional and innovative features that form a consistent data modeling approach. Visual notations and examples are employed extensively to illustrate the use of the various constructs. Therefore, this book is of major importance and interest to advanced professionals, researchers, and graduate or post-graduate students in the areas of spatio-temporal databases and geographical information systems.

"For anyone thinking of doing research in this field, or who is developing a system based on spatio-temporal data, this text is essential reading." (Mike Worboys, U Maine, Orono, ME, USA)

"The high-level semantic model presented and validated in this book provides essential guidance to researchers and implementers when improving the capabilities of data systems to serve the actual needs of applications and their users in the temporal and spatial domains that are so prevalent today." (Gio Wiederhold, Stanford U, CA, USA)"