EuroVisPosters2016

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https://diglib.eg.org/handle/10.2312/15276

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Coloring Interactive Compositional Dot Maps
(The Eurographics Association, 2016) Tennekes, Martijn; Jonge, Edwin de; Tobias Isenberg and Filip Sadlo
We propose an algorithmic color scheme for zoom-able compositional dot maps. Contrary to existing methods, it uses density, composition, and zoom level to color the pixels of the resulting dot map. We describe the method and its application.
Eurovis Posters 2016: Frontmatter
(Eurographics Association, 2016) Tobias Isenberg; Filip Sadlo;
Features vs Prototypes: Amplifying Cognition with Common Data Graphics
(The Eurographics Association, 2016) Migut, M. A.; Worring, M.; Tobias Isenberg and Filip Sadlo
The most common and important data visualizations, such as barcharts or scatterplots are typically feature-based. In this paper we question whether feature-based representations are favorable from the cognition point of view. We show through the examples how the notion of prototypes can be introduced and discuss based on Card's taxonomy how feature- and prototypebased representations amplify cognition.
Geometry-Aware Visualization of Performance Data
(The Eurographics Association, 2016) Vierjahn, Tom; Hentschel, Bernd; Kuhlen, Torsten W.; Tobias Isenberg and Filip Sadlo
Phenomena in the performance behaviour of high-performance computing (HPC) applications can stem from the HPC system itself, from the application's code, but also from the simulation domain. In order to analyse the latter phenomena, we propose a system that visualizes profile-based performance data in its spatial context, i.e., on the geometry, in the simulation domain. It thus helps HPC experts but also simulation experts understand the performance data better. In addition, our tool reduces the initially large search space by automatically labelling large-variation views on the data which require detailed analysis.
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data
(The Eurographics Association, 2016) Vogogias, Athanasios; Kennedy, Jessie; Archambault, Daniel; Tobias Isenberg and Filip Sadlo
Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for performing hierarchical clustering analysis of short time-series gene expression data. Dynamic sliders control parameters such as the similarity threshold at which clusters are merged and the level of relative intra-cluster distinctiveness, which can be used to identify "weak-edges" within clusters. An expert user can drill down to further explore the dendrogram and detect nested clusters and outliers. This is done by using the sliders and by pointing and clicking on the representation to cut the branches of the tree in multiple-heights. A prototype of this tool has been developed in collaboration with a small group of biologists for analysing their own datasets. Initial feedback on the tool has been positive.
Interactive Exploration of Student Generated Content presented in Blogs
(The Eurographics Association, 2016) Jusufi, Ilir; Milrad, Marcelo; Legaspi, Xurxo; Tobias Isenberg and Filip Sadlo
Nowadays blogs are regarded as tools for communication as well as an important source for spreading information in almost every subject. In recent years, school teachers have started to take advantage of this technology in order to support their educational practices. In this paper we focus on the data generated by a project involving more than 50 Swedish schools where teachers and pupils are posting content related to their astronomy class activities in their blogs with the aims of improving the teaching process. The challenge here is to find suitable methods to explore all these blogs in an interactive and discovery fashion. Our proposed solution to this challenge is to provide a visual and interactive tool for the exploration of blog corpora by teachers, pupils, project managers and parents.
InVITe - Towards Intuitive Visualization of Iterations over Text
(The Eurographics Association, 2016) Lamqaddam, Houda; Aerts, Jan; Tobias Isenberg and Filip Sadlo
With InVITe, we are working towards intuitive visualization to support review of iterative modifications on text documents. In order to accomplish this, we perform simple matching of text snippets between the two versions of text, across a large range of parameter settings. Next, an overview graphic indicating the effect of parameter space on the output allows the user to select those combinations that are of interest. Finally, such selection will display an alluvial diagram with annotations and covering different resolutions. With this tool, co-authors can keep an overview of changes made, both structural and local.
Large-scale Argument Visualization (LSAV)
(The Eurographics Association, 2016) Khartabil, Dana; Wells, S.; Kennedy, Jessie; Tobias Isenberg and Filip Sadlo
Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been developed that support argument analysts and help them to work with arguments. Until recently, arguments were manually analyzed from natural language text, or constructed from scratch, but new communication modes mean that increasing amounts of debate and the arguments therein can be captured digitally. Furthermore, new tools and techniques for argument mining are beginning to automate the process of extracting argument structure from natural language; leading to much larger argument datasets that present problems for the current generation of argument visualization tools. Additionally, individual argument analysts have different foci which can lead to increased complexity within datasets, and additional facets that argument visualizations should account for but do not. We propose a tool for interacting with argument corpora that enable users to explore and understand the reasoning structure of large-scale arguments. The tool will support a range of interactivity techniques and will help users to explore and analyse large-scale arguments, to more rapidly comprehend complex new problem domains.
MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization
(The Eurographics Association, 2016) Li, Wei; Elderman, Joep; Hoogerwoord, Erwin; Funk, Mathias; Brombacher, Aarnout C.; Tobias Isenberg and Filip Sadlo
Healthcare data is the emerging force to push ahead smarter clinical solutions. However, unforeseen challenges like unmanaged massive data and costly access to it make it difficult for domain experts to easily derive actionable insights. In collaboration with a local diagnostic service provider, we designed MetricScalpel, a web-based visualization tool to help people quickly look into the real-life diagnostic data in the local community. The tool enables swift exploration into the multivariate diagnostic data sets from different sources and facilitates data selection/subsetting for deeper analysis. It can be used to reveal overlooked health conditions on almost any level without the requirement of heavy technical knowledge. Such design makes it easier to be accepted by a wider user group in the healthcare related organizations. It was proven to well serve the domain experts in validating pre-exist hypotheses in cohort analysis as well as revealing undiscovered patterns of health conditions in the local community. External evaluation shows operation cost was remarkably confined as domain experts were assisted with direct and intuitive access to the relevant data in need.
Quantitative Evaluation for Edge Bundling Based on Structural Aesthetics
(The Eurographics Association, 2016) Saga, Ryosuke; Tobias Isenberg and Filip Sadlo
This study proposes a method to evaluate the efficiency of edge bundling. Edge bundling is important to improve visual clutter of edge visualization. However, the evaluation of edge bundling is based only on qualitative evaluations, and the evaluation cost is expensive. Therefore, this paper proposes three measurement strategies to evaluate edge bundling, namely, the edge lengths before and after edge bundling, occupation area, and edge density.
Query by Visual Words: Visual Search for Scatter Plot Visualizations
(The Eurographics Association, 2016) Shao, Lin; Schleicher, Timo; Schreck, Tobias; Tobias Isenberg and Filip Sadlo
Finding interesting views in large collections of data visualizations, e.g., scatter plots, is challenging. Recently, ranking views based on heuristic quality measures has been proposed. However, quality measures may fail to reflect given user interest, since interestingness is strongly dependent on the application domain and user context. As an alternative, interactive exploration in combination with example based user queries can be used to find patterns of interest. We introduce a novel approach for searching in large sets of scatter plot views based on a dictionary of frequent local scatter plot patterns. The dictionary is used for interactive construction of scatter plot queries, taking into account similarity of local scatter plot patterns as well as their approximate location in the plot. We introduce the overall approach, present a glyph design for visualization of dictionary entries, and illustrate the applicability of our implementation.
Styrian Diversity Visualisation: Visualising Statistical Open Data with a LeanWeb App and Data Server
(The Eurographics Association, 2016) Andrews, Keith; Traunmüller, Thomas; Wolkinger, Thomas; Goldgruber, Eva; Gutounig, Robert; Ausserhofer, Julian; Tobias Isenberg and Filip Sadlo
Statistical open data is usually provided only in the form of spreadsheets or CSV files. The developers of open data apps must either restrict themselves to managable bite-sized chunks of data, which can be consumed (read, parsed, and held in memory) in one go, or must install and maintain their own data server which the app can query on demand. The Styrian Diversity Visualisation (in German ''Steirische Vielfalt Visualisiert'' or SVV) project demonstrates the use of a dedicated data server (triple store) to host large amounts of statistical open data. The SVV web app queries the data server dynamically using SPARQL queries to obtain exactly the data required at that particular time, greatly simplifying its internal logic. There is no need to parse and store entire data sets in memory.
TaCo: Comparative Visualization of Large Tabular Data
(The Eurographics Association, 2016) Hourieh, Reem; Stitz, Holger; Gehlenborg, Nils; Streit, Marc; Tobias Isenberg and Filip Sadlo
Tabular data plays a vital role in many different domains. In the course of a project, changes to the structure and content of tables can result in multiple instances of a table. A challenging task when working with such derived tables is to understand what exactly has changed from one version to another. Traditional comparison tools assist users in inspecting differences between multiple table instances, however, the resulting visualizations are often hard to interpret or do not scale to large tables with thousands of rows and columns. To address these challenges, we developed TaCo, an interactive comparison tool that effectively visualizes the differences between multiple tables at various levels of granularity: (1) the aggregated differences between all table instances, (2) the differences between one table compared to all others, and (3) the detailed differences between two instances.
Towards Combining Attribute-based and Time Series-based Visual Querying
(The Eurographics Association, 2016) Sessler, David; Spott, Martin; Nauck, Detlef; Harmer, William; Kohlhammer, Jörn; Bernard, Jürgen; Tobias Isenberg and Filip Sadlo
We present a concept for the visual-interactive definition of meaningful subsets in data sets comprising multivariate attributes and time series data. Based on a generalization of requirements of a real-world user group, we propose a three-stage approach, combining visual-interactive querying, query filter analysis, and result exploration. The approach includes several design parameters that can easily be adapted in future design studies for alternative applications.
Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks
(The Eurographics Association, 2016) Ji, Chengtao; Gronde, J. J. van de; Maurits, N. M.; Roerdink, Jos B. T. M.; Tobias Isenberg and Filip Sadlo
An electroencephalography (EEG) coherence network represents functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of coherence networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists understand brain mechanisms. However, most studies have been limited to static EEG coherence networks or were focused on individual network nodes. In this poster, we consider groups of nodes for visualizing the evolution of network communities and their corresponding spatial location. We use a timeline-based representation to provide an overview of the evolution of functional units (FUs) and their corresponding spatial location over time. This representation can help the viewer identify functional units across the whole time window, as well as to identify relations between functional units and brain regions. In addition, a time-annotated FU map is provided to facilitate comparison of the behavior of the nodes between consecutive FU maps. This time-annotated FU map provides more detail about how the classification of electrodes into FUs changes over time. Our method is proposed as a first step towards a complete analysis of EEG coherence networks.
Tracking Space-Filling Features by Two-Step Optimization
(The Eurographics Association, 2016) Schnorr, Andrea; Freitag, Sebastian; Kuhlen, Torsten W.; Hentschel, Bernd; Tobias Isenberg and Filip Sadlo
We present a novel approach for tracking space-filling features, i.e., a set of features covering the entire domain. The assignment between successive time steps is determined by a two-step, global optimization scheme. First, a maximum-weight, maximal matching on a bi-partite graph is computed to provide one-to-one assignments between features of successive time steps. Second, events are detected in a subsequent step; here the matching step serves to restrict the exponentially large set of potential solutions. To this end, we compute an independent set on a graph representing conflicting event explanations. The method is evaluated by tracking dissipation elements, a structure definition from turbulent flow analysis.
Transfer Function Optimization Based on a Combined Model of Visibility and Saliency
(The Eurographics Association, 2016) Luo, Shengzhou; Dingliana, John; Tobias Isenberg and Filip Sadlo
We present an automated technique to optimize the clarity of features in visualizations of 3D volume datasets. By adjusting the opacity transfer function, we achieve user-specified target distributions of feature conspicuity. Unlike previous techniques our approach accounts for both the issues of view-dependent occlusion and visual saliency of features in volume data. We demonstrate how the automated approach is useful in particular for optimizing the visualization of time-varying volume datasets.
Understanding Networks beyond Overlapping Clusters
(The Eurographics Association, 2016) Guchev, Vladimir; Angelini, S.; Amati, G.; Tobias Isenberg and Filip Sadlo
Tasks associated with the investigation of large complex clustered networks are widespread in various research areas. Among the popular and common approaches to exploratory analysis, it is definitely worthwhile to underscore the node-link-based graph visualization. However, despite the prevalence of node-link-based tools, its graphic design and geometric representation of topology almost invariably formed by a spontaneous spatial structure, or on the contrary, by a too rigidly ordered arrangement. Transformation possibilities of multivariate data structures may allow finding a suitable graphic balance between optic chaos and visual primitiveness by the use of partially ordered sets for grouping. By taking the studying of Twitter communities as a task, the paper presents a data modelling method in conjunction with a set of visualization techniques, which implement a convenient and perceivable interactive toolset for analytical exploration of overlapping network clusters.
User Interaction Visualization for Design Synthesis
(The Eurographics Association, 2016) Aselmaa, Anet; Song, Yu; Goossens, Richard H. M.; Tobias Isenberg and Filip Sadlo
Through the synthesis of gathered user research data, interaction designers are able to generate design proposals. Logging user interactions with a software provides a rich set of data that can give further insights into users' behavior. We present a case study of visualizing interactions log files of the manual tumor contouring task. We identify two types of visualizations needed for comprehending the tumor contouring process. Based on these visualizations, designer was able to gain a holistic view of the process, detailed understanding of the different phases of the task, and identify re-occurring interaction patterns.
Visual Analysis of Text Annotations for Stance Classification with ALVA
(The Eurographics Association, 2016) Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus; Tobias Isenberg and Filip Sadlo
The automatic detection and classification of stance taking in text data using natural language processing and machine learning methods create an opportunity to gain insight about the writers' feelings and attitudes towards their own and other people's utterances. However, this task presents multiple challenges related to the training data collection as well as the actual classifier training. In order to facilitate the process of training a stance classifier, we propose a visual analytics approach called ALVA for text data annotation and visualization. Our approach supports the annotation process management and supplies annotators with a clean user interface for labeling utterances with several stance categories. The analysts are provided with a visualization of stance annotations which facilitates the analysis of categories used by the annotators. ALVA is already being used by our domain experts in linguistics and computational linguistics in order to improve the understanding of stance phenomena and to build a stance classifier for applications such as social media monitoring.

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