Vagueness is pervasive in spatial concepts and relations. This presents a major obstacle to establishing the spatial and geo-spatial ontologies that will be required for the next generation of semantically aware spatial information systems. This  tutorial will examine the many issues and challenges that arise from vagueness in spatial information and explore a variety of approaches to dealing with them (including fuzzy logic, supervaluation semantics and standpoint semantics). The  theoretical analysis of vagueness will be applied to the problem of characterising particular types of geographic feature (such as, forest, lake, mountain, etc.). Representation and reasoning about "place" is a second, closely related theme of the  tutorial. The notion of "place" is central to human understanding of space and to the interrogation of spatial information. However, its semantics is elusive and controversial. The nature of "place" will be explored from both a logical and a social perspective.

The web page for the tutorial is at:

Organizer: Thora Tenbrink, University of Bremen, Germany

Many researchers use language to understand thought processes, for example by asking participants questions about how they performed a task, or by eliciting descriptions or think aloud protocols. Such information can be inspiring in various areas of cognitive science research. In order to exploit the information provided by linguistic data thoroughly, a systematic approach is required. The aim of this tutorial is to familiarize young and experienced researchers with the analysis of language produced in relation to spatial thought processes. Starting from various established perspectives on language in relation to cognitive science (psycholinguistics, verbal protocol and content analysis, cognitive linguistics, and discourse analysis), the method of Cognitive Discourse Analysis (CODA) will be introduced. CODA serves as a coherent framework for empirical methods at the interface of linguistics and spatial cognition. Practical examples will be used for illustration by interpreting sample data from ongoing research. See:

http://www.informatik.uni-bremen.de/~tenbrink/TutorialCosit.html