TBA

TBA

TBA

TBA

This talk will describe work aimed at the combined problem of collection, management, visualisation, search and analysis of large amounts of complex uncertain data. Our aim has been to deliver value to users from large and complex data sets, based on our background in neural network based pattern analysis methods. Our initial focus was in the engineering field undertaken in the DAME project on the analysis of Rolls-Royce engine data. That work developed a distributed search engine (PMC) and a signal data search and analysis system (Signal Data Explorer) which has now been commercialised by Cybula and sold to customers such as Bombardier (for rail) and Scottish and Southern Energy. More recently we have transferred the methods into the scientific medical field within the £4.5M CARMEN project, which has explored the problems of distributing analytical services and data within a distributed computing infrastructure. The project has just launched the CARMEN portal (www.carmen.org.uk) for use by neuroscientists to share and analyse electrophysiology data. The talk will describe the challenges faced by the end users, and how the methods developed under these projects are helping them, and what issues remain to be addressed.

Information spaces such the WWW are the most challenging type of space that many people navigate during everyday life. Unlike the real world, there are no effective maps of information spaces, so people are forced to rely on search engines which are only suited to some types of retrieval task. As a result, knowledge workers spent a substantial amount of time trying unsuccessfully to find information that they know exists. The present paper describes a new method for creating maps of large information spaces. The maps use a city metaphor, comprised of streets (branch nodes) and buildings (leaf nodes), which are generated entirely automatically from webcrawl data. A technical evaluation was carried out using data from 112 universities, which had up to 485,775 pages on their websites. The effect of different layout rules on INSIGHT maps is presented, showing how they are more compact than radial graphs such as the Bubble Tree

Sophisticated methods of visualisation allow a user to explore datasets and gain insight from the information being displayed, but are often difficult for non expert users interact with. One such method is volume rendering which creates composite images using a transfer function which maps different optical properties to a given input. Previous work used the contour tree, which represents topological features of a dataset as branches of a tree, to apply different transfer functions to different aspects of the data. While this allows for individual features to be highlighted and explored, it suffers from a usability standpoint. The user is required to have knowledge of the mechanics of the contour tree, instead of using the data structure purely as an abstraction of the data. We therefore propose to combine the principle of this previous work with the idea of a thumbnail gallery and the hierarchy of topological features to give non expert users a simpler interface.

Hamish returns from VisWeek 20009 in Atlantic City to give us a report on the conference.

Most previous research into the effect of body-based (proprioceptive & vestibular) information on navigation has used basic spatial tasks such as path integration. However, key findings from that work (specifically, the importance of rotational body-based cues) do not seem to apply to "everyday" tasks performed in large-scale spaces. I will describe my recent research that has investigated the effect of rotational vs. translational body-based information when participants learned routes and developed survey knowledge in large-scale virtual worlds. Some of these worlds were shrunk to fit within a 12 x 13 meter tracking laboratory, but in the full-sized versions of the worlds participants walked hundreds of metres on an omni-directional treadmill. The most important factor was proprioceptive cues for translationary movement, which produced a large, significant improvement in the rate at which participants developed both route and survey knowledge.

- Welcome new members and introduce ourselves;

- Discuss role and operation of the VVR group meetings

- Discuss strategic issues