Multi-Paradigm Reasoning for Access to Heterogeneous GIS

Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place. Mediation architectures like VirGIS overcome syntactical and semantical heterogeneity between several distributed sources. On mobile devices, however, this kind of solution is not suitable, due to limitations, mostly regarding bandwidth, computation power, and available storage space. The aim of this paper is to present a solution for providing powerful reasoning mechanisms accessible from mobile applications and involving data from several heterogeneous sources. By adapting contents to time and location, mobile web information systems can not only increase the value and suitability of the service itself, but can substantially reduce the amount of data delivered to users. Because many problems pertain to infrastructures and transportation in general and to way finding in particular, one cornerstone of the architecture is higher level reasoning on graph networks with the Multi-Paradigm Location Language MPLL. A mediation architecture is used as a “graph provider” in order to transfer the load of computation to the best suited component – graph construction and transformation for example being heavy on resources. Reasoning in general can be conducted either near the “source” or near the end user, depending on the specific use case. The concepts underlying the proposal described in this paper are illustrated by a typical and concrete scenario for web applications

This is the tricky part: When directions become difficult

Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace humangenerated directions, which are often incomplete, vague, or in error. However, humangenerated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems

This is the tricky part: When directions become difficult

Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace human-generated directions, which are often incomplete, vague, or in error. However, human-generated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems

The significance of Traveler's Route Knowledge for Choice of commuting mode of transport

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Travelling in a city is an essential part of everyone’s life, whether it is the routine daily commute or navigating to a previously unknown place, and can be accomplished with a variety of means of transport. This thesis explores how personal, first-hand route knowledge influences choice of mode of transport. This is motivated by the premise that human-oriented approach for computer systems design can be of significant benefit to the user. Public (bus, train, tram, metro) and private (bicycle, car, on foot) means of transport are considered and compared. Collected survey data analysed with a logistic regression method does not show any relationship between route knowledge and choice of mode of transport

Cognitive Mapping and Wayfinding in Children’s Home- School Itinerary

According to environmental and behavioural theories, individuals in their early years of cognitive development enter a world full of environmental stimuli that motivate them to perceive and learn. As a result of many perception processes, people convert and transfer perceived information into cognitive patterns that inform their understanding of the surroundings in which they operate and navigate around them. This paper aims to better understand the processes involved in navigating the home-school journey for children and delve into the likely impact of gender and age group of children on their perception of the environment and attempt to identify some of the factors that may affect their spatial behaviour. In doing so, there is the intention to develop a new approach to investigating wayfinding for school age children during their home-school journey. The approach consists of combining the analysis of cognitive maps drawn up by children, observation of their travel routines and space syntax tools. After contextualising the research through a literature review covering issues such as children’s spatial perception, navigation, wayfinding, and imageability, the paper describes the methods used to carry out the research, presents the results of the research and discusses them in order to shed some light on children’s wayfinding on the school journey

An Egocentric Spatial Data Model for Intelligent Mobile Geographic Information Systems

Individuals in unknown locations, such as utility workers in the field, soldiers on a mission, or sightseeing tourists, share the need for an answer to two basic questions: Where am I? and What is in front of me?Because such information is not readily available in foreign locations, aids in the form of paper maps or mobile GISs, which give individuals an all-inclusive view of the environment, are often used. This panoptic view may hinder the positioning and orienteering process, since people perceive their surroundings perspectively from their current position. In this thesis, I describe a novel framework that resolves this problem by applying sensors that gather the individual\u27s spatial frame of reference. This spatial frame of reference, in combination with an egocentric spatial data model enables an injective mapping between the real world and the data frame of reference, hence, alleviating the individual\u27s cognitive workload. Furthermore, our egocentric spatial data model allows intelligent mobile Geographic Information Systems to capture the notions of here and there, and, consequently, provides insight into the individual\u27s surroundings. Finally, our framework, in conjunction with the context given by the task to be performed, enables intelligent mobile Geographic Information Systems to implicitly answer questions with respect to where, what, and how

A Qualitative Representation of Spatial Scenes in R2 with Regions and Lines

Regions and lines are common geographic abstractions for geographic objects. Collections of regions, lines, and other representations of spatial objects form a spatial scene, along with their relations. For instance, the states of Maine and New Hampshire can be represented by a pair of regions and related based on their topological properties. These two states are adjacent (i.e., they meet along their shared boundary), whereas Maine and Florida are not adjacent (i.e., they are disjoint). A detailed model for qualitatively describing spatial scenes should capture the essential properties of a configuration such that a description of the represented objects and their relations can be generated. Such a description should then be able to reproduce a scene in a way that preserves all topological relationships, but without regards to metric details. Coarse approaches to qualitative spatial reasoning may underspecify certain relations. For example, if two objects meet, it is unclear if they meet along an edge, at a single point, or multiple times along their boundaries. Where the boundaries of spatial objects converge, this is called a spatial intersection. This thesis develops a model for spatial scene descriptions primarily through sequences of detailed spatial intersections and object containment, capturing how complex spatial objects relate. With a theory of complex spatial scenes developed, a tool that will automatically generate a formal description of a spatial scene is prototyped, enabling the described objects to be analyzed. The strengths and weaknesses of the provided model will be discussed relative to other models of spatial scene description, along with further refinements

Topological Equivalence and Similarity in Multi-Representation Geographic Databases

Geographic databases contain collections of spatial data representing the variety of views for the real world at a specific time. Depending on the resolution or scale of the spatial data, spatial objects may have different spatial dimensions, and they may be represented by point, linear, or polygonal features, or combination of them. The diversity of data that are collected over the same area, often from different sources, imposes a question of how to integrate and to keep them consistent in order to provide correct answers for spatial queries. This thesis is concerned with the development of a tool to check topological equivalence and similarity for spatial objects in multi-representation databases. The main question is what are the components of a model to identify topological consistency, based on a set of possible transitions for the different types of spatial representations. This work develops a new formalism to model consistently spatial objects and spatial relations between several objects, each represented at multiple levels of detail. It focuses on the topological consistency constraints that must hold among the different representation of objects, but it is not concerned about generalization operations of how to derive one representation level from another. The result of this thesis is a?computational tool to evaluate topological equivalence and similarity across multiple representations. This thesis proposes to organize a spatial scene -a set of spatial objects and their embeddings in space- directly as a relation-based model that uses a hierarchical graph representation. The focus of the relation-based model is on relevant object representations. Only the highest-dimensional object representations are explicitly stored, while their parts are not represented in the graph