Fast Algorithms for Constructing Maximum Entropy Summary Trees

Karloff? and Shirley recently proposed summary trees as a new way to visualize large rooted trees (Eurovis 2013) and gave algorithms for generating a maximum-entropy k-node summary tree of an input n-node rooted tree. However, the algorithm generating optimal summary trees was only pseudo-polynomial (and worked only for integral weights); the authors left open existence of a olynomial-time algorithm. In addition, the authors provided an additive approximation algorithm and a greedy heuristic, both working on real weights. This paper shows how to construct maximum entropy k-node summary trees in time O(k^2 n + n log n) for real weights (indeed, as small as the time bound for the greedy heuristic given previously); how to speed up the approximation algorithm so that it runs in time O(n + (k^4/eps?) log(k/eps?)), and how to speed up the greedy algorithm so as to run in time O(kn + n log n). Altogether, these results make summary trees a much more practical tool than before.Comment: 17 pages, 4 figures. Extended version of paper appearing in ICALP 201

The generalized Robinson-Foulds metric

The Robinson-Foulds (RF) metric is arguably the most widely used measure of phylogenetic tree similarity, despite its well-known shortcomings: For example, moving a single taxon in a tree can result in a tree that has maximum distance to the original one; but the two trees are identical if we remove the single taxon. To this end, we propose a natural extension of the RF metric that does not simply count identical clades but instead, also takes similar clades into consideration. In contrast to previous approaches, our model requires the matching between clades to respect the structure of the two trees, a property that the classical RF metric exhibits, too. We show that computing this generalized RF metric is, unfortunately, NP-hard. We then present a simple Integer Linear Program for its computation, and evaluate it by an all-against-all comparison of 100 trees from a benchmark data set. We find that matchings that respect the tree structure differ significantly from those that do not, underlining the importance of this natural condition.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Designing an Exploratory Visual Interface to the Results of Citizen Surveys

Surveys are used by public authorities to monitor the quality and reach of public services and provide information needed to help improve them. The results of such surveys tend to be used in internal reports, with highly-aggregated summaries being released to the public. Even where data are released, many citizens do not have the capability to explore and interpret them. This o ffers limited scope for citizens to explore the results and use them to help hold service providers to account - objectives that are increasingly important in public service provision. We work closely with an English local authority to develop an innovative interactive interface to a citizen survey to demonstrate what can be achieved by applying a visual approach to the exploration of such data. In so doing we (a) make a case for web-based interactive visualisation to make this kind of information accessible both internally to those working in local government and externally to citizens in a way that is not achieved through a regular Open Data release or existing applications; (b) use techniques from both cartography and information visualization to inform the design of fluid visual interactions that enable diverse users - from the casual citizen browser to those interested in more in-depth analysis - to view, compare and interpret the survey outputs from a wide variety of perspectives; and (c) document experiences and reactions to the provision of information in this form, with log analysis playing a role in this exercise. Our reflections on our successes and otherwise will inform future exploratory interface design to help citizens access information and hold public service providers to account

Visualizing Multivariate Hierarchic Data Using Enhanced Radial Space-Filling Layout

Currently, visualization tools for large ontologies (e.g., pathway and gene ontologies) result in a very flat wide tree that is difficult to fit on a single display. This paper develops the concept of using an enhanced radial space-filling (ERSF) layout to show biological ontologies efficiently. The ERSF technique represents ontology terms as circular regions in 3D. Orbital connections in a third dimension correspond to non-tree edges in the ontology that exist when an ontology term belongs to multiple categories. Biologists can use the ERSF layout to identify highly activated pathway or gene ontology categories by mapping experimental statistics such as coefficient of variation and overrepresentation values onto the visualization. This paper illustrates the use of the ERSF layout to explore pathway and gene ontologies using a gene expression dataset from E. coli

Visual Analysis of Multi-Joint Kinematic Data

Abstract Kinematics is the analysis of motions without regarding forces or inertial effect

What Google Maps can do for biomedical data dissemination: examples and a design study

BACKGROUND: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. RESULTS: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. CONCLUSIONS: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations

The Virtual-Spine Platform—Acquiring, visualizing, and analyzing individual sitting behavior

Back pain is a serious medical problem especially for those people sitting over long periods during their daily work. Here we present a system to help users monitoring and examining their sitting behavior. The Virtual-Spine Platform (VSP) is an integrated system consisting of a real-time body position monitoring module and a data visualization module to provide individualized, immediate, and accurate sitting behavior support. It provides a comprehensive spine movement analysis as well as accumulated data visualization to demonstrate behavior patterns within a certain period. The two modules are discussed in detail focusing on the design of the VSP system with adequate capacity for continuous monitoring and a web-based interactive data analysis method to visualize and compare the sitting behavior of different persons. The data was collected in an experiment with a small group of subjects. Using this method, the behavior of five subjects was evaluated over a working day, enabling inferences and suggestions for sitting improvements. The results from the accumulated data module were used to elucidate the basic function of body position recognition of the VSP. Finally, an expert user study was conducted to evaluate VSP and support future developments

Information Visualisation for Project Management: Case Study of Bath Formula Student Project

This paper contributes to a better understanding and design of dashboards for monitoring of engineering projects based on the projects’ digital footprint and user-centered design approach. The paper presents an explicit insight-based framework for the evaluation of dashboard visualisations and compares the performance of two groups of student engineering project managers against the framework: a group with the dashboard visualisations and a group without the dashboard. The results of our exploratory study demonstrate that student project managers who used the dashboard generated more useful information and exhibited more complex reasoning on the project progress, thus informing knowledge of the provision of information to engineers in support of their project understanding