Providing visualisation support for the analysis of anatomy ontology data

BACKGROUND: Improvements in technology have been accompanied by the generation of large amounts of complex data. This same technology must be harnessed effectively if the knowledge stored within the data is to be retrieved. Storing data in ontologies aids its management; ontologies serve as controlled vocabularies that promote data exchange and re-use, improving analysis. The Edinburgh Mouse Atlas Project stores the developmental stages of the mouse embryo in anatomy ontologies. This project is looking at the use of visual data overviews for intuitive analysis of the ontology data. RESULTS: A prototype has been developed that visualises the ontologies using directed acyclic graphs in two dimensions, with the ability to study detail in regions of interest in isolation or within the context of the overview. This is followed by the development of a technique that layers individual anatomy ontologies in three-dimensional space, so that relationships across multiple data sets may be mapped using physical links drawn along the third axis. CONCLUSION: Usability evaluations of the applications confirmed advantages in visual analysis of complex data. This project will look next at data input from multiple sources, and continue to develop the techniques presented to provide intuitive identification of relationships that span multiple ontologies

A study of image quality, authenticity, and metadata characteristics of photogrammetric three-dimensional data in cultural heritage domain

This study aims to provide a deeper understanding of digital image quality, authenticity, and metadata issues of photogrammetry as a three-dimensional (3D) digitization technique in the cultural heritage domain. Photogrammetric image data characteristics are introduced for information professionals by analyzing features leading to the high-quality, accurate and welldefined three-dimensional data. Qualitative methodology was employed based on an interpretivist approach. Both synchronous and asynchronous semi-structured interviews with open-ended questions were carried out with seven professionals in the field of photogrammetry, using chat and email as data collection techniques. The findings of this study suggest that photogrammetry seems to be effective in reconstruction, preservation and visualization of cultural heritage objects because it can acquire the accurate 3D models in a cost effective way. It is shown that photogrammetry is an effective way to present a photo-realistic view for 3D architectures and artifacts. Moreover, metadata usage in the cultural heritage photogrammetric data is beginning to emerge. In photogrammetry process, image metadata can preserve the original data which is used in the process of camera calibration and consequently building the 3D model.Joint Master Degree in Digital Library Learning (DILL

Adding imageability features to information displays

Techniques for improving the imageability of an existing data visualisation are described. The aim is to make the visualisation more easily explored, navigated and remembered. Starting from a relatively sparse landscape– like representation of a set of objects, we selectively add to the visualisation static features such as clusters, and dynamic features such as view–specific sampling of object detail. Information on past usage is used in this process, making manifest an aspect of interaction which is often neglected. Issues arising from the use of such features in a shared virtual environment are discussed

Generalizing abstractions in form-based visual programming languages : from direct manipulation to static representation

We believe concreteness, direct manipulation and responsiveness in a visual programming language increase its usefulness. However, these characteristics present a challenge in generalizing programs for reuse, especially when concrete examples are used as one way of achieving concreteness. In this thesis, we present a technique to solve this problem by deriving generality automatically through the analysis of logical relationships among concrete program entities from the perspective of a particular computational goal. Use of this technique allows a fully general form-based program with reusable abstractions to be derived from one that was specified in terms of concrete examples and direct manipulation. Also addressed in this thesis is how to statically represent the generalized programs. In general, we address how to design better static representations. A weakness of many interactive visual programming languages is their static representations. Lack of an adequate static representation places a heavy cognitive burden on a VPL's programmers, because they must remember potentially long dynamic sequences of screen displays in order to understand a previously-written program. However, although this problem is widely acknowledged, research on how to design better static representations for interactive VPLs is still in its infancy. Building upon the cognitive dimensions developed for programming languages by cognitive psychologists Green and others, we have developed a set of concrete benchmarks for VPL designers to use when designing new static representations. These benchmarks provide design-time information that can be used to improve a VPL's static representation

An algorithmic framework for visualising and exploring multidimensional data

To help understand multidimensional data, information visualisation techniques are often applied to take advantage of human visual perception in exposing latent structure. A popular means of presenting such data is via two-dimensional scatterplots where the inter-point proximities reflect some notion of similarity between the entities represented. This can result in potentially interesting structure becoming almost immediately apparent. Traditional algorithms for carrying out this dimension reduction tend to have different strengths and weaknesses in terms of run times and layout quality. However, it has been found that the combination of algorithms can produce hybrid variants that exhibit significantly lower run times while maintaining accurate depictions of high-dimensional structure. The author's initial contribution in the creation of such algorithms led to the design and implementation of a software system (HIVE) for the development and investigation of new hybrid variants and the subsequent analysis of the data they transform. This development was motivated by the fact that there are potentially many hybrid algorithmic combinations to explore and therefore an environment that is conductive to their development, analysis and use is beneficial not only in exploring the data they transform but also in exploring the growing number of visualisation tools that these algorithms beget. This thesis descries three areas of the author's contribution to the field of information visualisation. Firstly, work on hybrid algorithms for dimension reduction is presented and their analysis shows their effectiveness. Secondly, the development of a framework for the creation of tailored hybrid algorithms is illustrated. Thirdly, a system embodying the framework, providing an environment conductive to the development, evaluation and use of the algorithms is described. Case studies are provided to demonstrate how the author and others have used and found value in the system across areas as diverse as environmental science, social science and investigative psychology, where multidimensional data are in abundance