NSF-CNPq Collaborative Research on Integrating Geospatial Information

Under this project, researchers at the University of Maine and the Brazilian National Institute for Space Research (INPE) are collaborating to study new models for integrating geographic information. The two research teams complement each other, providing a unique synergy in conceptual modeling and systems development. Long-term visits by Brazilian researchers assure a tight cooperation, and provide for integrated research and education. The work focuses on the semantics of spatial data collections that are stored in geographic information systems or spatial databases. Such collections often have diverse database schemas and lack conventions that would make them easily compatible, so that they could be combined to perform an integrated analysis. The goal of this research is to develop computational models that will allow us to compare, harmonize, and integrate geographic information across different ontologies and different spatial data models. The approach consists of a new integrated method to assess similarity based on common parts, functions, and attributes. In these similarity assessments, different contexts are considered through the operations a user intents to perform with the harmonized data. The results of this project will provide meaningful comparisons and integration of geospatial information, enabling better interoperation among geographic information systems. http://www.spatial.maine.edu/~max/CNPq.htm

Ontological Foundations for Geographic Information Science

We propose as a UCGIS research priority the topic of “Ontological Foundations for Geographic Information.” Under this umbrella we unify several interrelated research subfields, each of which deals with different perspectives on geospatial ontologies and their roles in geographic information science. While each of these subfields could be addressed separately, we believe it is important to address ontological research in a unitary, systematic fashion, embracing conceptual issues concerning what would be required to establish an exhaustive ontology of the geospatial domain, issues relating to the choice of appropriate methods for formalizing ontologies, and considerations regarding the design of ontology-driven information systems. This integrated approach is necessary, because there is a strong dependency between the methods used to specify an ontology, and the conceptual richness, robustness and tractability of the ontology itself. Likewise, information system implementations are needed as testbeds of the usefulness of every aspect of an exhaustive ontology of the geospatial domain. None of the current UCGIS research priorities provides such an integrative perspective, and therefore the topic of “Ontological Foundations for Geographic Information Science” is unique

III: Small: A Theory of Topological Relations for Compound Spatial Objects

Spatial data collections with an incomplete coverage yield regions with holes and separations that often cannot be filled by interpolation. Geosensor networks typically generate such configurations, and with the proliferation of sensor colonies, there is now an urgent need to provide users with better information technologies of cognitively plausible methods to search for or compare available spatial data sets that may be incomplete. The objective of the investigations is to advance knowledge about qualitative spatial relations for spatial regions with holes and/or separations. The core activity is the study of the interplay between topological spatial relations with holed regions and topological spatial relations with separated regions to address the potentially complex configurations that feature both holes and separations. Three characteristics of such a set of topological relations are addressed: the formalization of a sound set of relations at a granularity that allows for the distinction of the salient features of holed and separated regions, while offering the opportunity to generalize to coarser relations in a meaningful and consistent way; the relaxation of such relations so that the determination of the most similar relations follows immediately from the applied methodology; and the qualitative inference of new information from the composition of such relations to identify inconsistencies and to drawn information that is not immediately available from individual relations. The hypothesis is that combining the relation formalization with sound similarity and composition reasoning yields critical insights for a sufficiently expressive, common approach to modeling topological relations for holed regions and regions with separations. The resulting theory of topological spatial relations highlights a parallelism between relations with holed regions and regions with separations, which is most apparent when these regions are embedded on the surface of the sphere, while some parts of these regularities are often hidden in the usual planar embedding. Since topological relations are qualitative spatial descriptions, they come close to people\u27s own reasoning, so that a better understanding of the relations for compound spatial objects will have ramifications for qualitative spatial reasoning, without a need for drawing graphical depictions to make inferences. It also lays the foundation for linguistic constructs to communicate in natural language spatial configurations, ultimately leading to talking maps. An immediate impact of this theory of topological relations between holed and separated regions is on the querying and reasoning about dataset that are gathered by geosensor networks. Additional information available online: http://www.spatial.maine.edu/~max/holesAndParts.htm

07212 Abstracts Collection -- Constraint Databases, Geometric Elimination ang Geographic Information Systems

From 20.05. to 25.05., the Dagstuhl Seminar 07212 ``Constraint Databases, Geometric Elimination and Geographic Information Systems\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Application of Spatial Concepts to Genome Data

This project will investigate the application of geographic information science concepts and methods to the modeling and analysis of genome data. The primary objective of the research is to develop a data model for genomes that supports the graphical exploration of the higher order spatial arrangement of genome features through spatial queries and spatial data analysis tools. The spatial genome model formalizes topological and order relationships among genome features (before, after, overlap), uses metric properties to refine spatial topologies, and includes representations of features that have uncertain metric properties. The genome spatial model enhances the integrative and comparative potential of genome data by providing the foundation for more powerful spatial reasoning and inferences than can be achieved by data models that incorporate only a small subset of possible temporal-spatial relationships among genome features (e.g. order and distance). The research represents a logical extension from current feature by feature analytical approaches of genome studies to one that allows biologists to ask questions about the contextual and organizational significance of the spatial arrangement of genome features. These functional capabilities should, in turn, aid in the automation of repetitive analytical tasks associated with the mapping of genome features and drive the discovery of biologically significant aspects of genome organization and function

Multi-Modal Spatial Querying

This project investigates the use of two concurrent communication channels, graphics and speech, to achieve a successful interaction between a person and a geographic information system (GIS). The objective is to construct a multi-modal spatial query language in which users interact with a geographic database by drawing sketches of the desired configuration, while simultaneously talking about the spatial objects and the spatial relations drawn. This study will increase our understanding of multi-modal spatial interactions, and will lead to improved strategies for intelligent integration and processing of such multi-modal spatial queries in a GIS. The key to this interaction is the exploitation of complementary or redundant information present in both graphical and verbal descriptions of the same spatial scenes. A multiple-resolution model of spatial relations is used to capture the essential aspects of a sketch and its corresponding verbal description. The model stresses topological properties, such as containment and neighborhood, and considers metrical properties, such as distance and directions, as refinements where necessary. This model enables the retrieval of similar, not only exact, matches between a spatial query and a geographic database. Such new methods of multi-modal spatial querying and spatial similarity retrieval will empower experts as well as novice users to perform easier spatial searches, ultimately providing new user communities access to spatial databases

Algorithms for Hierarchical Spatial Reasoning

In several applications, there is the need to reason about spatial relations using multiple local frames of reference organized in aggregation hierarchies. In this paper we deal with direction relations, a special class of spatial relations that describe order in space (e.g., north, northeast). We assume a spatial database of points and regions. Points belong to regions, which may be parts of larger regions and so on. The direction relations between points in the same region are explicitly represented. Inference mechanisms are applied to extract the relation between points in different regions and detect inconsistencies. We study two complementary types of inference. The first one derives the relation between two points that exist in different regions through chains of common points using path consistency. The second type of inference uses the relation between ancestor regions to infer the relation between the points. The paper describes algorithms for both types of inference..