Alia Abdelmoty

We propose a general approach for reasoning in space. The approach is composed of a set of two general constraints to govern the spatial relationships between objects in space, and two rules to propagate relationships between those objects. The approach is based on a uniform representation of the topology of the space as a connected set of components using a structure called adjacency matrix which can capture the topology of objects of different complexity in any space dimension. The relationships between objects are represented by the intersection of the space components. The approach is also shown to be applicable to reasoning in the temporal domain and is used to explain the conceptual neighbourhood phenomenon related to the reasoning process. A major advantage of the method is that reasoning between objects of any complexity can be achieved in a defined limited number of steps. Hence, the incorporation of spatial reasoning mechanisms in spatial information systems becomes possible.

This paper describes how a deductive object-oriented database (DOOD) can be used to support the storage and management of data which is typical of that found in geographic information systems (GIS). This is done with two aims in mind: to illustrate how a combination of deductive and object-oriented facilities can be applied effectively in an advanced application, thereby motivating the development of DOOD systems; and to show how geographic database systems stand to gain from the utilisation of advanced data modelling and inference facilities as supported by a DOOD. The paper describes the DOOD system which has been used for prototyping a range of geographic concepts, presents a framework for the structural organisation of GIS data using an object-oriented data model, and shows how a logic query language can be used within this structural framework to perform a range of analyses.

The representation of complex spatial domains in conventional databases suffers from fragmented representation of object structure, lack of instance-level spatial relationships, and the generation of large combinatoric search spaces in query analysis. The deductive capabilities provided by a deductive database offer some assistance in solving these problems, in particular by enabling spatial reasoning to be performed by a Geographic Information System (GIS). Deduction in the database is used to support the natural representation of complex spatial object structures in single and multi-layered Geographic DataBases (GDB), inference of implicit spatial relationships, and the manipulation of multiple resolution spatial representations. In addition, deductive capabilities are shown to be essential for automatic data input and update in a GDB. Coupled with appropriate structural representation, spatial reasoning is an important tool for the realization of an effective GDB.

A geo-ontology has a key role to play in the development of a spatially aware search engine, with regard to providing support for query disambiguation, query term expansion, relevance ranking and web resource annotation. This paper reviews those functions and identifies the challenges arising in the construction and maintenance of such an ontology. Two current contenders for the representation of the geo-ontology are GML, a specific markup language for geographic domains and OWL, a generic ontology representation language. Both languages are used to model the geo-ontology designed for supporting web retrieval of geographic concepts. The powers and limitations of the languages are identified. In particular, the paper highlights the lack of representation and reasoning abilities for different types of rules needed for supporting the geo-ontology.

This paper presents an approach to the development of a deductive object-oriented database system, describing the key design decisions and their consequences for implementation. The approach is novel, in that it integrates an object-oriented database system manipulated using an imperative programming language (ROCK) with a logic language for expressing queries and methods (ROLL). The integration is made seamless by deriving both the imperative and logic languages from a single formally defined data model, thereby avoiding impedance mismatches when they are integrated.

Ontologies play a key role in Semantic Web research. A common use of ontologies in Semantic Web is to enrich the current Web resources with some well-defined meaning to enhance the search capabilities of existing web searching systems. This paper reports on how ontologies developed in the EU Semantic Web project SPIRIT are used to support retrieval of documents that are considered to be spatially relevant to users’ queries. The query expansion techniques presented in this paper are based on both a domain and a geographical ontology. The proposed techniques are distinguished from conventional ones in that a query is expanded by derivation of its geographical query footprint. The techniques are specially designed to resolve a query (such as castles near Edinburgh) that involves spatial terms (e.g. Edinburgh) and fuzzy spatial relationships (e.g. near) that qualify the spatial terms. Various factors are taken into account to support intelligent expansion of a spatial query, including, spatial terms as encoded in the geographical ontology, non-spatial terms as encoded in the domain ontology, as well as the semantics of the spatial relationships and their context of use. Some experiments have been carried out to evaluate the performance of the proposed techniques using sample realistic ontologies.

The SPIRIT search engine provides a test bed for the development of web search technology that is specialised for access to geographical information. Major components include the user interface, a geographical ontology, maintenance and retrieval functions for a test collection of web documents, textual and spatial indexes, relevance ranking and metadata extraction. Here we summarise the functionality and interaction between these components before focusing on the design of the geo-ontology and the development of spatio-textual indexing methods. The geo-ontology supports functionality for disambiguation, query expansion, relevance ranking and metadata extraction. Geographical place names are accompanied by multiple geometric footprints and qualitative spatial relationships. Spatial indexing of documents has been integrated with text indexing through the use of spatio-textual keys in which terms are concatenated with spatial cells to which they relate. Preliminary experiments demonstrate considerable performance benefits when compared with pure text indexing and with text indexing followed by a spatial filtering stage.