These questions and others were discussed at COSIT'07, the Eighth International Conference on Spatial Information Theory, which was held 19-23 September 2007 in Mount Eliza, Victoria, Australia. The COSIT conference series has been shaping and leading interdisciplinary research in theoretical GIScience for more than a decade, involving disciplines such as spatial information science, artificial intelligence, cognitive science, neuroscience, cognitive psychology, cognitive anthropology, linguistics and philosophy.
COSIT usually takes place in Europe or North America. This year researchers from the Asian-Pacific region (forming about one-third of the participants) had a chance to participate and share their ideas. This mixture of "old" and "new" faces worked very successfully for COSIT'07. Held at Melbourne Business School, Mount Eliza , COSIT'07 had more participants and a more competitive paper selection process than at any previous COSIT. The tranquil setting created a relaxed atmosphere for the intensive discussions between participants, discussions that went on even through the nights.
The first day held four international workshops. The topics covered included spatial cognition and architectural design, semantic similarity in geographic applications, distributed and mobile spatial computing, and social networks in geographic space. The next three days were structured into formal knowledge representation, ontologies and similarity (day 1), perception and cognitive mapping (day 2), and qualitative reasoning, navigation and spatial uncertainty (day 3). The last conference day is traditionally reserved for a doctoral colloquium at which talented doctoral students have the opportunity to present their research ideas to their peers, as well as to more senior researchers, frequently for the first time.
So, where is spatial information theory currently located, and where is it heading? Here are the bigger issues at play:
- Ontology and semantics promise to provide foundations for integration and interoperability - pressing issues in practice, and increasingly in the future.
- Learning about our environments by developing models and studying cognitive representations that deal with incomplete knowledge and imprecise observations. Progress here is immediately relevant for robotics, autonomous vehicles and supporting human navigation.
- Communication of spatial information to people using cognitive and linguistic concepts, including understanding the differences between languages and cultures. The applications that will profit are not the expert tools, but all the ubiquitous services supporting everyday decisions.