07291 Abstracts Collection -- Scientific Visualization

From 15.07. to 20.07.07, the Dagstuhl Seminar 07291 ``Scientific Visualization\u27\u27 was held in the International Conference and Research Center (IBFI),Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Visualisation of Large-Scale Call-Centre Data

The contact centre industry employs 4% of the entire United King-dom and United States’ working population and generates gigabytes of operational data that require analysis, to provide insight and to improve efficiency. This thesis is the result of a collaboration with QPC Limited who provide data collection and analysis products for call centres. They provided a large data-set featuring almost 5 million calls to be analysed. This thesis utilises novel visualisation techniques to create tools for the exploration of the large, complex call centre data-set and to facilitate unique observations into the data.A survey of information visualisation books is presented, provid-ing a thorough background of the field. Following this, a feature-rich application that visualises large call centre data sets using scatterplots that support millions of points is presented. The application utilises both the CPU and GPU acceleration for processing and filtering and is exhibited with millions of call events.This is expanded upon with the use of glyphs to depict agent behaviour in a call centre. A technique is developed to cluster over-lapping glyphs into a single parent glyph dependant on zoom level and a customizable distance metric. This hierarchical glyph repre-sents the mean value of all child agent glyphs, removing overlap and reducing visual clutter. A novel technique for visualising individually tailored glyphs using a Graphics Processing Unit is also presented, and demonstrated rendering over 100,000 glyphs at interactive frame rates. An open-source code example is provided for reproducibility.Finally, a novel interaction and layout method is introduced for improving the scalability of chord diagrams to visualise call transfers. An exploration of sketch-based methods for showing multiple links and direction is made, and a sketch-based brushing technique for filtering is proposed. Feedback from domain experts in the call centre industry is reported for all applications developed

Visual Encodings for Networks with Multiple Edge Types

This paper reports on a formal user study on visual encodings ofnetworks with multiple edge types in adjacency matrices. Our tasksand conditions were inspired by real problems in computationalbiology. We focus on encodings in adjacency matrices, selectingfour designs from a potentially huge design space of visual encodings.We then settle on three visual variables to evaluate in acrowdsourcing study with 159 participants: orientation, positionand colour. The best encodings were integrated into a visual analyticstool for inferring dynamic Bayesian networks and evaluated bycomputational biologists for additional evidence.We found that theencodings performed differently depending on the task, however,colour was found to help in all tasks except when trying to find theedge with the largest number of edge types. Orientation generallyoutperformed position in all of our tasks

Improving memorability in fisheye views

Interactive fisheye views use distortion to show both local detail and global context in the same display space. Although fisheyes allow the presentation and inspection of large data sets, the distortion effects can cause problems for users. One such problem is lack of memorability – the ability to find and go back to objects and features in the data. This thesis examines the possibility of improving the memorability of fisheye views by adding historical information to the visualization. The historical information is added visually through visit wear, an extension of the concepts of edit wear and read wear. This will answer the question “Where have I been?” through visual instead of cognitive processing by overlaying new visual information on the data to indicate a user’s recent interaction history. This thesis describes general principles of visibility in a space that is distorted by a fisheye lens and defines some parameters of the design space of visit wear. Finally, a test system that applied the principles was evaluated, and showed that adding visit wear to a fisheye system improved the memorability of the information space

Joint Contour Net Analysis for Feature Detection in Lattice Quantum Chromodynamics Data

In this paper we demonstrate the use of multivariate topological algorithms to analyse and interpret Lattice Quantum Chromodynamics (QCD) data. Lattice QCD is a long established field of theoretical physics research in the pursuit of understanding the strong nuclear force. Complex computer simulations model interactions between quarks and gluons to test theories regarding the behaviour of matter in a range of extreme environments. Data sets are typically generated using Monte Carlo methods, providing an ensemble of configurations, from which observable averages must be computed. This presents issues with regard to visualisation and analysis of the data as a typical ensemble study can generate hundreds or thousands of unique configurations. We show how multivariate topological methods, such as the Joint Contour Net, can assist physicists in the detection and tracking of important features within their data in a temporal setting. This enables them to focus upon the structure and distribution of the core observables by identifying them within the surrounding data. These techniques also demonstrate how quantitative approaches can help understand the lifetime of objects in a dynamic system.Comment: 30 pages, 19 figures, 4 table

Perceptual multivariate visualisation of volumetric Lagrangian fluid-flow processes

Lagrangian flow data in oceanography are highly complex, encompassing not only the underpinning Eulerian, advective, vectorial flow fields and the three-dimensional position coordinates of tracer particles but also supplementary trajectory information such as interaction radii of particles, lifecycle source-to-sink information and biochemical process data. Visualising all those data cooperatively in its three-dimensional context is a prime challenge, as it demands to present all relevant information to enable a contextual analysis of the flow process while preventing the most commonly-occurring perceptual issues of clutter, colourisation conflicts, artefacts and the lack of spatial references in fluid-flow applications. In this article, we present visualisation design approaches for 4D spatio-temporal data in their context and introduce a novel colour-mapping approach for 3D velocity tensors. The employed visualisation approach is evaluated towards perceptual adequacy and efficacy with respect to algebraic visualisation design and on an oceanographic case study. The technical and perceptual elements have further implications and applications for still-picture and animated volumetric visualisation design in related applications of the natural sciences, such as geological flow mapping

A semi-supervised approach to visualizing and manipulating overlapping communities

When evaluating a network topology, occasionally data structures cannot be segmented into absolute, heterogeneous groups. There may be a spectrum to the dataset that does not allow for this hard clustering approach and may need to segment using fuzzy/overlapping communities or cliques. Even to this degree, when group members can belong to multiple cliques, there leaves an ever present layer of doubt, noise, and outliers caused by the overlapping clustering algorithms. These imperfections can either be corrected by an expert user to enhance the clustering algorithm or to preserve their own mental models of the communities. Presented is a visualization that models overlapping community membership and provides an interactive interface to facilitate a quick and efficient means of both sorting through large network topologies and preserving the user's mental model of the structure. © 2013 IEEE