Baher A. El-Geresy

A Filter Flow Visual Querying Language and Interface for Spatial Databases

In this paper a visual approach to querying in spatial databases is presented. A filter flow methodology is used to consistently express different types of queries in these systems. Filters are used to represent operations on the database and pictorial icons are used throughout the language for filters, operators and spatial relations. Different granularities of the relations are presented in a hierarchical fashion for spatial constraints. The language framework and functions are described and examples are used to demonstrate its capabilities in representing different levels of queries, including spatial joins and composite spatial joins. Here, the primary focus is on the query language itself but an overview of the implemented interface of the language is also provided.

A framework for combining rules and geo-ontologies

Geo-ontologies have a key role to play in the development of the geospatial-semantic web, with regard to facilitating the search for geographical information and resources. They normally hold large amounts of geographic information and undergo a continuous process of revision and update. Hence, means of ensuring their integrity are crucial and needed to allow them to serve their purpose. This paper proposes the use of qualitative spatial reasoning as a tool to support the development of a geo-ontology management system. A new framework for the representation of and reasoning over geo-ontologies is presented using the web ontology language (OWL) and its associated reasoning tools. Spatial reasoning and integrity rules are represented using a spatial rule engine extension to the reasoning tools associated with OWL. The components of the framework are described and the implementation of the spatial reasoning engine is presented. This work is a step towards the realisation of a complete geo-ontology management system for the semantic web.

Order in space: a general formalism for spatial reasoning

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.

Spatio-Temporal Geographic Information Systems: A Causal Perspective

In this paper approaches to conceptual modelling of spatio-temporal domains are identified and classified into five general categories: location-based, object or feature-based, event-based, functional or behavioural and causal approaches. Much work has been directed towards handling the problem from the first four view points, but less from a causal perspective. It is argued that more fundamental studies are needed of the nature of spatio-temporal objects and of their interactions and possible causal relationships, to support the development of spatio-temporal conceptual models. An analysis is carried out on the nature and type of spatio-temporal causation and a general classification is presented.

Supporting Frameworks for the Geospatial Semantic Web

A lot of information on the web is geographically referenced. Discovering and linking this information poses eminent research challenges to the geospatial semantic web, with regards to the representation and manipulation of geographic data. Towards addressing these challenges, this work explores the potential of the current semantic web languages and tools. In particular, an integrated logical framework of rules and ontologies, using current W3C standards, is assessed for modeling geospatial ontologies of place encoding both symbolic and geometric references to place locations. Spatial reasoning is incorporated in the framework to facilitate the deduction of implicit semantics and for expressing spatial integrity constraints. The logical framework is then extended with geo-computation engines that offer more effective manipulations of geometric information. Example data sets mined from web resources are used to demonstrate and evaluate both frameworks, offering insights to their potentials and limitations.

SPARQS: a qualitative spatial reasoning engine

In this paper the design and implementation of a general qualitative spatial reasoning engine (SPARQS) is presented. Qualitative treatment of information in large spatial databases is used to complement the quantitative approaches to managing those systems, in particular, it is used for the automatic derivation of implicit spatial relationships and in maintaining the integrity of the database. To be of practical use, composition tables of spatial relationships between different types of objects need to be developed and integrated in those systems. The automatic derivation of such tables is considered to be a major challenge to current reasoning approaches. In this paper, this issue is addressed and a new approach to the automatic derivation of composition tables is presented. The method is founded on a sound set-theoretical approach for the representation and reasoning over arbitrarily shaped objects in space. A reasoning engine tool, SPARQS, has been implemented to demonstrate the validity of the approach. The engine is composed of a basic graphical interface where composition tables between the most common types of spatial objects are built. An advanced interface is also provided, where users are able to describe shapes of arbitrary complexity and to derive the composition of chosen spatial relationships. Examples of the application of the method using different objects and different types of spatial relationships are presented and new composition tables are built using the reasoning engine.

A Qualitative Approach to Integration in Spatial Databases

This paper considers the problem of integrating data sets which hold information about the same features in space. The approach proposed is based on allowing inconsistent data sets to coexist in the database and explicitly representing the nature of inconsistencies among those sets. A qualitative level of representation is created where the data sets can be integrated and manipulated using qualitative reasoning techniques. A systematic approach is used to identify classes and levels of consistency which can be checked in isolation. This provides the flexibility for two data sets to be integrated without necessarily being totally consistent in every aspect. The method is simple and can be used in many applications which incorporates the modelling and manipulation of spatial entities such as GIS, CAD and image databases.

A visual query language for large spatial databases

In this paper a visual approach to querying in large spatial databases is presented. A diagrammatic technique utilising a data flow metaphor is used to express different kinds of spatial and non-spatial constraints. Basic filters are designed to represent the various types of queries in such systems. Icons for different types of spatial relations are used to denote the filters. Different granularities of the relations are presented in a hierarchical fashion when selecting the spatial constraints. Spatial joins and composite spatial and non-spatial constraints are represented consistently in the language.

Towards a general theory for modelling qualitative space

Qualitative spatial representation and reasoning are techniques for modeling and manipulating objects and relationships in space. Finding ways for defining the complete and sound (physically plausible) set of relationships between spatial objects is a prerequisite for the development and realization of qualitative representation and reasoning formalisms. Establishing the set of sound relationships is a complicated task especially when complex objects are considered. Hence, current approaches to qualitative representation and reasoning are limited to handling simple spatial objects. In this paper, we introduce a constraint-based approach to qualitative representation of topological relationships by defining a set of general soundness rules. The rules reduce the combinatorial set of relations produced by the method to the complete and physically possible ones. The rules are general and apply to objects of arbitrary complexity and together with the representation and reasoning formalism form a theory for qualitative space.

Episodes in space: qualitative representation and reasoning over spatio-temporal objects

There is growing interest in many application domains for the temporal treatment and manipulation of spatially referenced objects. Handling the time dimension in spatial databases can greatly enhance and extend their functionality and usability by offering means of understanding the spatial behaviour in time. Few works, to date, have been directed towards the development of formalisms for representation and reasoning in this domain. In this paper, a new approach is presented for the representation and reasoning over spatio-temporal relationships. The approach is simple and aims to satisfy the requirements of coherency, expressiveness and reasoning power. Consistent behaviours of spatial objects in time are denoted episodes. The topology of the domain is defined by decomposing episodes into representative components and relationships are defined between those components. Spatio-temporal reasoning is achieved by composing the relationships between the object components using constraint networks. New composition tables between simple spatio-temporal regions and between regions and volumes are also derived and used in the reasoning process.