Visualising the structure of document search results: A comparison of graph theoretic approaches

This is the post-print of the article - Copyright @ 2010 Sage PublicationsPrevious work has shown that distance-similarity visualisation or ‘spatialisation’ can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or ‘cluster growing’ strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of non-metric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion

CacophonyViz: Visualisation of Birdsong Derived Ecological Health Indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

CacophonyViz : Visualisation of birdsong derived ecological health indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

Web-based discovery and dissemination of multidimensional geographic information

A spatial data clearinghouse is an electronic facility for searching, viewing, transferring, ordering, advertising, and disseminating spatial data from numerous sources via the Internet. Governments and other institutions have been implementing spatial data clearinghouses to minimise data duplication and thus reduce the cost of spatial data acquisition. Underlying these clearinghouses are geoportals and databases of geospatial metadata.A geoportal is an access point of a spatial data clearinghouse and metadata is data that describes data. The success of a clearinghouse's spatial data discovery system is dependent on its ability to communicate the contents of geospatial metadata by providing both visual and analytical assistancet o a user. The model currently adopted by the geographic information community was inherited from generic information systems and thus to an extent ignores spatial characteristics of geographic data. Consequently, research in Geographic Information Retrieval (GIR) has focussed on spatial aspects of webbased data discovery and acquisition. This thesis considers how the process of GIR from geoportals can be enhanced through multidimensional visualisation served by web-based geographic data sources. An approach is proposed for the presentation of search results in ontology assisted GIR. Also proposed is an approach for the visualisation of multidimensional geographic data from web-based data sources. These approaches are implemented in two prototypes, the Geospatial Database Online Visualisation Environment (GeoDOVE) and the Spatio-Temporal Ontological Relevance Model (STORM). A discussion of their design, implementation and evaluation is presented. The results suggest that ontology-assisted visualisation can improve a user's ability to identify the most relevant multidimensional geographic datasets from a set of search results. Additional results suggest that it is possible to offer the proposed visualisation approaches on existing geoportal frameworks. The implication of the results is that multidimensional visualisation should be considered by the wider geographic information community as an alternative to historic approaches for presenting search results on geoportals, such as the textual ranked list and two-dimensional maps.EThOS - Electronic Theses Online ServiceUniversity of Newcastle upon TyneGBUnited Kingdo

Development of Multidimensional Eating Disorder Inventory Information System Framework - Managing Digital Adolescent Healthcare Ecosystem

Data sources associated with Eating Disorder (ED) events are heterogeneous. They intensely influence the lives of millions of teenagers. The EDs can lead to obesity or vice versa and succumb to many linked chronic illnesses. We examine the existing research on Eating Disorder Inventory (EDI) to explore connectivity between multiple domains of the healthcare ecosystem. The present study identifies various attribute dimensions of EDI – M , interpreted as multidimensional , an egghead idiom to model and integrate with an integrated conceptual framework. The research aims to develop a Multidimensional Eating Disorder Inventory Information System (MEDIIS) to manage the EDI-M attributes, interpreted in various data sources and domains. We further evaluate the EDI metadata to explore the connectivity between multiple attributes dimensions of EDs. The phenomenon of eating-disorder attribute connectivity is established with overweight, obesity and diabetic conditions, articulating EDI-M applicability in the MEDIIS framework

3D Cadastre visualization and dissemination: Most recent progresses and future directions

The 3D Cadastre has been investigated from many viewpoints (including legal, organizational and technical). However, to date little research has focused specifically on visualizationrelated aspects despite the value-added of the third dimension. The paper first proposes an overview of progress made in the last five years in 3D cadastral visualization. The authors then summarize discussions at the 2014 3D Cadastre workshop regarding future research and development on the topic. This synthesis is complemented by a broad review of the most recent advances in 3D visualization beyond the 3D cadastral domain, with the goal of providing a number of important directions for further work, allowing researchers, developers and users to consolidate their respective activities, and encouraging collaboration

Knowledge-based systems and geological survey

This personal and pragmatic review of the philosophy underpinning methods of geological surveying suggests that important influences of information technology have yet to make their impact. Early approaches took existing systems as metaphors, retaining the separation of maps, map explanations and information archives, organised around map sheets of fixed boundaries, scale and content. But system design should look ahead: a computer-based knowledge system for the same purpose can be built around hierarchies of spatial objects and their relationships, with maps as one means of visualisation, and information types linked as hypermedia and integrated in mark-up languages. The system framework and ontology, derived from the general geoscience model, could support consistent representation of the underlying concepts and maintain reference information on object classes and their behaviour. Models of processes and historical configurations could clarify the reasoning at any level of object detail and introduce new concepts such as complex systems. The up-to-date interpretation might centre on spatial models, constructed with explicit geological reasoning and evaluation of uncertainties. Assuming (at a future time) full computer support, the field survey results could be collected in real time as a multimedia stream, hyperlinked to and interacting with the other parts of the system as appropriate. Throughout, the knowledge is seen as human knowledge, with interactive computer support for recording and storing the information and processing it by such means as interpolating, correlating, browsing, selecting, retrieving, manipulating, calculating, analysing, generalising, filtering, visualising and delivering the results. Responsibilities may have to be reconsidered for various aspects of the system, such as: field surveying; spatial models and interpretation; geological processes, past configurations and reasoning; standard setting, system framework and ontology maintenance; training; storage, preservation, and dissemination of digital records

SPEET: visual data analysis of engineering students performance from academic data

This paper presents the steps conducted to design and develop an IT Tool for Visual Data Analysis within the SPEET (Student Profile for Enhancing Engineering Tutoring) ERASMUS+ project. The proposed goals are to provide insight into student behaviours, to identify patterns and relevant factors of academic success, to facilitate the discovery and understanding of profiles of engineering students, and to analyse the difierences across European institutions. For that purpose, the concepts and methods used for the visual analysis of educational data are reviewed and a tool is proposed, which implements approaches based on visual interaction.info:eu-repo/semantics/publishedVersio

Mining climate data for shire level wheat yield predictions in Western Australia

Climate change and the reduction of available agricultural land are two of the most important factors that affect global food production especially in terms of wheat stores. An ever increasing world population places a huge demand on these resources. Consequently, there is a dire need to optimise food production. Estimations of crop yield for the South West agricultural region of Western Australia have usually been based on statistical analyses by the Department of Agriculture and Food in Western Australia. Their estimations involve a system of crop planting recommendations and yield prediction tools based on crop variety trials. However, many crop failures arise from adherence to these crop recommendations by farmers that were contrary to the reported estimations. Consequently, the Department has sought to investigate new avenues for analyses that improve their estimations and recommendations. This thesis explores a new approach in the way analyses are carried out. This is done through the introduction of new methods of analyses such as data mining and online analytical processing in the strategy. Additionally, this research attempts to provide a better understanding of the effects of both gradual variation parameters such as soil type, and continuous variation parameters such as rainfall and temperature, on the wheat yields. The ultimate aim of the research is to enhance the prediction efficiency of wheat yields. The task was formidable due to the complex and dichotomous mixture of gradual and continuous variability data that required successive information transformations. It necessitated the progressive moulding of the data into useful information, practical knowledge and effective industry practices. Ultimately, this new direction is to improve the crop predictions and to thereby reduce crop failures. The research journey involved data exploration, grappling with the complexity of Geographic Information System (GIS), discovering and learning data compatible software tools, and forging an effective processing method through an iterative cycle of action research experimentation. A series of trials was conducted to determine the combined effects of rainfall and temperature variations on wheat crop yields. These experiments specifically related to the South Western Agricultural region of Western Australia. The study focused on wheat producing shires within the study area. The investigations involved a combination of macro and micro analyses techniques for visual data mining and data mining classification techniques, respectively. The research activities revealed that wheat yield was most dependent upon rainfall and temperature. In addition, it showed that rainfall cyclically affected the temperature and soil type due to the moisture retention of crop growing locations. Results from the regression analyses, showed that the statistical prediction of wheat yields from historical data, may be enhanced by data mining techniques including classification. The main contribution to knowledge as a consequence of this research was the provision of an alternate and supplementary method of wheat crop prediction within the study area. Another contribution was the division of the study area into a GIS surface grid of 100 hectare cells upon which the interpolated data was projected. Furthermore, the proposed framework within this thesis offers other researchers, with similarly structured complex data, the benefits of a general processing pathway to enable them to navigate their own investigations through variegated analytical exploration spaces. In addition, it offers insights and suggestions for future directions in other contextual research explorations