Collaboration on an Ontology for Generalisation

workshopInternational audienceTo move beyond the current plateau in automated cartography we need greater sophistication in the process of selecting generalisation algorithms. This is particularly so in the context of machine comprehension. We also need to build on existing algorithm development instead of duplication. More broadly we need to model the geographical context that drives the selection, sequencing and degree of application of generalisation algorithms. We argue that a collaborative effort is required to create and share an ontology for cartographic generalisation focused on supporting the algorithm selection process. The benefits of developing a collective ontology will be the increased sharing of algorithms and support for on-demand mapping and generalisation web services

Collaboration on an Ontology for Generalisation

To move beyond the current plateau in automated cartography we need greater sophistication in the process of selecting generalisation algorithms. This is particularly so in the context of machine comprehension. We also need to build on existing algorithm development instead of duplication. More broadly we need to model the geographical context that drives the selection, sequencing and degree of application of generalisation algorithms. We argue that a collaborative effort is required to create and share an ontology for cartographic generalisation focused on supporting the algorithm selection process. The benefits of developing a collective ontology will be the increased sharing of algorithms and support for on-demand mapping and generalisation web services

From taxonomies to ontologies: formalizing generalization knowledge for on-demand mapping

© 2015 Cartography and Geographic Information Society Automation of the cartographic design process is central to the delivery of bespoke maps via the web. In this paper, ontological modeling is used to explicitly represent and articulate the knowledge used in this decision-making process. A use case focuses on the visualization of road traffic accident data as a way of illustrating how ontologies provide a framework by which salient and contextual information can be integrated in a meaningful manner. Such systems are in anticipation of web-based services in which the user knows what they need, but do not have the cartographic ability to get what they want

Formalising cartographic generalisation knowledge in an ontology to support on-demand mapping

This thesis proposes that on-demand mapping - where the user can choose the geographic features to map and the scale at which to map them - can be supported by formalising, and making explicit, cartographic generalisation knowledge in an ontology. The aim was to capture the semantics of generalisation, in the form of declarative knowledge, in an ontology so that it could be used by an on-demand mapping system to make decisions about what generalisation algorithms are required to resolve a given map condition, such as feature congestion, caused by a change in scale. The lack of a suitable methodology for designing an application ontology was identified and remedied by the development of a new methodology that was a hybrid of existing domain ontology design methodologies. Using this methodology an ontology that described not only the geographic features but also the concepts of generalisation such as geometric conditions, operators and algorithms was built. A key part of the evaluation phase of the methodology was the implementation of the ontology in a prototype on-demand mapping system. The prototype system was used successfully to map road accidents and the underlying road network at three different scales. A major barrier to on-demand mapping is the need to automatically provide parameter values for generalisation algorithms. A set of measure algorithms were developed to identify the geometric conditions in the features, caused by a change in scale. From this a Degree of Generalisation (DoG) is calculated, which represents the “amount” of generalisation required. The DoG is used as an input to a number of bespoke generalisation algorithms. In particular a road network pruning algorithm was developed that respected the relationship between accidents and road segments. The development of bespoke algorithms is not a sustainable solution and a method for employing the DoG concept with existing generalisation algorithms is required. Consideration was given to how the ontology-driven prototype on-demand mapping system could be extended to use cases other than mapping road accidents and a need for collaboration with domain experts on an ontology for generalisation was identified. Although further testing using different uses cases is required, this work has demonstrated that an ontological approach to on-demand mapping has promise

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

Modelling geographic phenomena at multiple levels of detail: A model generalisation approach based on aggregation

Considerable interest remains in capturing once geographical information at the fine scale, and from this, automatically deriving information at various levels of detail and scale via the process of map generalisation. This research aims to develop a methodology for transformation of geographic phenomena at a high level of detail directly into geographic phenomena at higher levels of abstraction. Intuitive and meaningful interpretation of geographical phenomena requires their representation at multiple levels of detail. This is due to the scale dependent nature of their properties. Prior to the cartographic portrayal of that information, model generalisation is required in order to derive higher order phenomena typically associated with the smaller scales. This research presents a model generalisation approach able to support the derivation of phenomena typically present at 1:250,000 scale mapping, directly from a large scale topographic database (1:1250/1:2500/1:10,000). Such a transformation involves creation of higher order or composite objects, such as settlement, forest, hills and ranges, from lower order or component objects, such as buildings, trees, streets, and vegetation, in the source database. In order to perform this transformation it is important to model the meaning and relationships among source database objects rather than to consider the object in terms of their geometric primitives (points, lines and polygons). This research focuses on two types of relationships: taxonomic and partonomic. These relationships provide different but complimentary strategies for transformation of source database objects into required target database objects. The proposed methodology highlights the importance of partonomic relations for transformation of spatial databases over large changes in levels of detail. The proposed approach involves identification of these relationships and then utilising these relationships to create higher order objects. The utility of the results obtained, via the implementation of the proposed methodology, is demonstrated using spatial analysis techniques and the creation of ‘links’ between objects at different representations needed for multiple representation databases. The output database can then act as input to cartographic generalisation in order to create maps (digital or paper). The results are evaluated using manually generalised datasets

SPLITAREA: an algorithm for weighted splitting of faces in the context of a planar partition

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Advanced techniques for the management of geological mapping

This research is deemed of importance in the solution of one of the main complex problems in geological map production, the transfer from the 1:25.000 geologic data base, that has a resolution corresponding to that at which data are gathered in the field, to the printing of 1:50.000 geological maps. The problems relate mainly to the greater detail of information contained in the database and the smaller printing scale. They can be classified into the design of a geological database scheme that allows the generalization process based on the rules relating the geological objects to one another, symbol overcrowding, and symbol overlapping. The challenge is to specify and implement a digital version of the decision rules used by geologists and cartographers to generate the final map. Often in practice these rules tend to be highly ambiguous, subjective, and inadequate in view of the modern need of automated generalization of geological information for land-use planning. The proposed system is based on the application of conventional and artificial intelligence computer techniques to the production of digital geological cartography, from the gathering of geologic data in the field to some printed product of wide usability. The objectives can be summarised as follows: 1 A support system for the iterative identification and characterization of geological objects based on an ad hoc geological and stratigraphic dictionary; 2 The identification and implementation of a hierarchical geological database schema for the automated reclassification or generalization of a geological database; 3 A hierarchical expert system for the automated revision and multiple representation of a geological database in view of new interpretation criteria of the geological information or for the production of maps on demand; 4 A system for avoiding symbol overcrowding or overlapping during the production of a geological map, which identifies the geological rules interacting between the geological objects represented in a map

3D visualization of cadastre : assessing the suitability of visual variables and enhancement techniques in the 3D model of condominium property units

La visualisation 3D de données cadastrales a été exploitée dans de nombreuses études, car elle offre de nouvelles possibilités d’examiner des situations de supervision verticale des propriétés. Les chercheurs actifs dans ce domaine estiment que la visualisation 3D pourrait fournir aux utilisateurs une compréhension plus intuitive d’une situation où des propriétés se superposent, ainsi qu’une plus grande capacité et avec moins d’ambiguïté de montrer des problèmes potentiels de chevauchement des unités de propriété. Cependant, la visualisation 3D est une approche qui apporte de nombreux défis par rapport à la visualisation 2D. Les précédentes recherches effectuées en cadastre 3D, et qui utilisent la visualisation 3D, ont très peu enquêté l’impact du choix des variables visuelles (ex. couleur, style) sur la prise de décision. Dans l’optique d'améliorer la visualisation 3D de données cadastres, cette thèse de doctorat examine l’adéquation du choix des variables visuelles et des techniques de rehaussement associées afin de produire un modèle de condominium 3D optimal, et ce, en fonction de certaines tâches spécifiques de visualisation. Les tâches visées sont celles dédiées à la compréhension dans l’espace 3D des limites de propriété du condominium. En ce sens, ce sont principalement des tâches notariales qui ont été ciblées. De plus, cette thèse va mettre en lumière les différences de l’impact des variables visuelles entre une visualisation 2D et 3D. Cette thèse identifie dans un premier temps un cadre théorique pour l'interprétation des variables visuelles dans le contexte d’une visualisation 3D et de données cadastrales au regard d’une revue de littéraire. Dans un deuxième temps, des expérimentations ont été réalisées afin de mettre à l’épreuve la performance des variables visuelles (ex. couleur, valeur, texture) et des techniques de rehaussement (transparence, annotation, déplacement). Trois approches distinctes ont été utilisées : 1) discussion directe avec des personnes œuvrant en géomatique, 2) entrevue face à face avec des notaires et 3) questionnaire en ligne avec des groupes ciblés. L’utilisabilité mesurée en termes d’efficacité, d’efficience et de degré de satisfaction a servi aux comparaisons des expérimentations. Les principaux résultats de cette recherche sont : 1) Une liste de tâches visuelles notariales utiles à la délimitation des unités de propriété dans le contexte de la visualisation 3D de condominium ; 2) Des recommandations quant à l'adéquation de huit variables visuelles et de trois techniques de rehaussement afin d’optimiser la réalisation d’un certain nombre de tâches notariales ; 3) Une analyse comparative de la performance de ces variables entre une visualisation 2D et 3D.3D visualization is being widely used in GIS (geographic information system) and CAD (computer-aided design) applications. It has also been introduced in cadastre studies to better communicate overlaps to the viewer, where the property units vertically stretch over or cover one part of the land parcel. Researchers believe that 3D visualization could provide viewers with a more intuitive perception, and it has the capability to demonstrate overlapping property units in condominiums unambiguously. However, 3D visualization has many challenges compared with 2D visualization. Many cadastre researchers adopted 3D visualization without thoroughly investigating the potential users, the visual tasks for decision-making, and the appropriateness of their representation design. Neither designers nor users may be aware of the risk of producing an inadequate 3D visualization, especially in an era when 3D visualization is relatively novel in the cadastre domain. With a general aim to improve the 3D visualization of cadastre data, this dissertation addresses the design of the 3D cadastre model from a graphics semiotics viewpoint including visual variables and enhancement techniques. The research questions are, firstly, what is the suitability of the visual variables and enhancement techniques in the 3D cadastre model to support the intended users' decision-making goal of delimitating condominium property units, and secondly, what are the perceptual properties of visual variables in 3D visualization compared with 2D visualization? This dissertation firstly identifies the theoretical framework for the interpretation of visual variables in 3D visualization as well as cadastre-related knowledge with literature review. Then, we carry out a preliminary evaluation of the feasibility of visual variables and enhancement techniques in a form of an expert-group review. With the result of the preliminary evaluation, this research then performs the hypothetico-deductive scientific approach to establishing a list of hypotheses to be validated by empirical tests regarding the suitability of visual variables and enhancement techniques in a cartographic representation of property units in condominiums for 3D visualization. The evaluation is based on the usability specification, which contains three measurements: effectiveness, efficiency, and preference. Several empirical tests are conducted with cadastral users in the forms of face-to-face interviews and online questionnaires, followed by statistical analysis. Size, shape, brightness, saturation, hue, orientation, texture, and transparency are the most discussed and used visual variables in existing cartographic research and implementations; thus, these eight visual variables have been involved in the tests. Their perceptual properties exhibited in the empirical test with concrete 3D models in this work are compared with those in a 2D visualization, which is derived from a literature-based synthesis. Three enhancement techniques, including labeling, 3D explosion, and highlighting, are tested as well. There are three main outcomes of this work. First, we established a list of visual tasks adapted to notaries for delimiting property units in the context of 3D visualization of condominium cadastres. Second, we describe the suitability of eight visual variables (Size, Shape, Brightness, Saturation, Hue, Orientation, Texture, and Transparency) of the property units and three enhancement techniques (labeling, 3D explosion and highlighting) in the context of 3D visualisation of condominium property units, based on the usability specification for delimitating visual tasks. For example, brightness only shows good performance in helping users distinguish private and common parts in the context of 3D visualization of property units in condominiums. As well, color hue and saturation are effective and preferable. The third outcome is a statement of the perceptual properties’ differences of visual variables between 3D visualization and 2D visualization. For example, according to Bertin (1983)’s definition, orientation is associative and selective in 2D, yet it does not perform in a 3D visualization. In addition, 3D visualization affects the performance of brightness, making it marginally dissociative and selective

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond