IVAPP 2015 Abstracts


Area 1 - Abstract Data Visualization

Full Papers
Paper Nr: 10
Title:

A Linear Time Algorithm for Visualizing Knotted Structures in 3 Pages

Authors:

Vitaliy Kurlin

Abstract: We introduce simple codes and fast visualization tools for knotted structures in molecules and neural networks. Knots, links and more general knotted graphs are studied up to an ambient isotopy in Euclidean 3-space. A knotted graph can be represented by a plane diagram or by an abstract Gauss code. First we recognize in linear time if an abstract Gauss code represents an actual graph embedded in 3-space. Second we design a fast algorithm for drawing any knotted graph in the 3-page book, which is a union of 3 half-planes along their common boundary line. The running time of our drawing algorithm is linear in the length of a Gauss code of a given graph. Three-page embeddings provide simple linear codes of knotted graphs so that the isotopy problem for all graphs in 3-space completely reduces to a word problem in finitely presented semigroups.

Paper Nr: 14
Title:

Supporting Event-based Geospatial Anomaly Detection with Geovisual Analytics

Authors:

Orland Hoeber and Monjur Ul Hasan

Abstract: Collecting multiple geospatial datasets that describe the same real-world events can be useful in monitoring and enforcement situations (e.g., independently tracking where a fishing vessel travelled and where it reported to have fished). While finding the obvious anomalies between such datasets may be a simple task, discovering more subtle inconsistencies can be challenging when the datasets describe many events that cover large geographic and temporal ranges. This paper presents a geovisual analytics approach to this problem domain, automatically extracting potential event anomalies from the data, visualizing these on a map, and providing interactive filtering tools to allow expert analysts to discover and analyze patterns that are of interest. A case study is presented, illustrating the value of the approach for discovering anomalies between commercial fishing vessel movement data and their reported fishing locations. Field trial evaluations confirm the benefits of this geovisual analytics approach for supporting real-world data analyst needs.

Paper Nr: 20
Title:

The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams

Authors:

Andreas Weiler, Michael Grossniklaus and Marc H. Scholl

Abstract: Nowadays, there are plenty of sources generating massive amounts of text data streams in a continuous way. For example, the increasing popularity and the active use of social networks result in voluminous and fast-flowing text data streams containing a large amount of user-generated data about almost any topic around the world. However, the observation and tracking of the ongoing evolution of topics in these unevenly distributed text data streams is a challenging task for analysts, news reporters, or other users. This paper presents “Stor-e- Motion” a shape-based visualization to track the ongoing evolution of topics’ frequency (i.e., importance), sentiment (i.e., emotion), and context (i.e., story) in user-defined topic channels over continuous flowing text data streams. The visualization supports the user in keeping the overview over vast amounts of streaming data and guides the perception of the user to unexpected and interesting points or periods in the text data stream. In this work, we mainly focus on the visualization of text streams from the social microblogging service Twitter, for which we present a series of case studies (e.g., the observation of cities, movies, or natural disasters) applied on real-world data streams collected from the public timeline. However, to further evaluate our visualization, we also present a baseline case study applied on the text stream of a fantasy book series.

Paper Nr: 26
Title:

The Visual Exploration of Aggregate Similarity for Multi-dimensional Clustering

Authors:

James Twellmeyer, Marco Hutter, Michael Behrisch, Jörn Kohlhammer and Tobias Schreck

Abstract: We present a visualisation prototype for the support of a novel approach to clustering called TRIAGE. TRIAGE uses aggregation functions which are more adaptable and flexible than the weighted mean for similarity modelling. While TRIAGE has proven itself in practice, the use of complex similarity models makes the interpretation of TRIAGE clusterings challenging. We address this challenge by providing analysts with a linked, matrix-based visualisation of all relevant data attributes. We employ data sampling and matrix seriation to support both effective overviews and fluid, interactive exploration using the same visual metaphor for heterogeneous attributes. The usability of our prototype is demonstrated and assessed with the help of real-world usage scenarios from the cyber-security domain.

Paper Nr: 36
Title:

A User-centric Taxonomy for Multidimensional Data Projection Tasks

Authors:

Ronak Etemadpour, Lars Linsen, Christopher Crick and Angus Forbes

Abstract: When investigating multidimensional data sets with very large numbers of objects and/or a very large number of dimensions, a variety of visualization methods can be employed in order to represent the data effectively and to enable the user to explore the data at different levels of detail. A common strategy for encoding multidimensional data for visual analysis is to use dimensionality reduction techniques that project data from higher dimensions onto a lower-dimensional space. In this paper, we focus on projection techniques that output 2D or 3D scatterplots which can then be used for a range of data analysis tasks. Existing taxonomies for multidimensional data projections focus primarily on tasks in order to evaluate the human perception of class or cluster separation and/or preservation. However, real-world data analysis of complex data sets often includes other tasks besides cluster separation, such as: cluster identification, similarity seeking, cluster ranking, comparisons, counting objects, etc. A contribution of this paper is the identification of subtasks grouped into four main categories of data analysis tasks. We believe that this user-centric task categorization can be used to guide the organization of multidimensional data projection layouts. Moreover, this taxonomy can be used as a guideline for visualization designers when faced with complex data sets requiring dimensionality reduction. Our taxonomy aims to help designers evaluate the effectiveness of a visualization system by providing an expanded range of relevant tasks. These tasks are gathered from an extensive study of visual analytics projects across real-world application domains, all of which involve multidimensional projection. In addition to our survey of tasks and the creation of the task taxonomy, we also explore in more detail specific examples of how to represent data sets effectively for particular tasks. These case studies, while not exhaustive, provide a framework for how specifically to reason about tasks and to decide on visualization methods. That is, we believe that this taxonomy will help visualization designers to determine which visualization methods are appropriate for specific multidimensional data projection tasks.

Paper Nr: 41
Title:

Past, Present, and Future of 3D Software Visualization - A Systematic Literature Analysis

Authors:

Richard Müller and Dirk Zeckzer

Abstract: The ongoing 2D vs. 3D research debate from information visualization also affects software visualization. There are many 2D, 3D, and combinations of 2D and 3D visualizations for software representing its structure, behavior, or evolution. This study contributes findings to this debate and presents the results of analyzing the applications of 3D in software visualization with the objectives to outline the state-of-the-art, to reveal trends, and to identify research gaps. The analysis combined a systematic mapping study to get an overview and a systematic literature review to gain deeper insights. The relevant papers were identified by three different search strategies (manual browsing, keyword, and backward search). Starting with a set of 4386 publications from the fields of information and software visualization 155 relevant papers dealing with 2D & 3D or 3D software visualizations were identified. These papers were analyzed according to dimensionality, aspect, year, evaluation method, and application of the third dimension. In a nutshell, the majority of 3D software visualizations represents the structural aspect, is either evaluated using case studies showing working examples or not evaluated at all, and applies a 2D layout using the third dimension for displaying software metrics.

Short Papers
Paper Nr: 2
Title:

A Time-location-Based Itinerary Visualization

Authors:

Florian Haag, Thomas Schlegel and Thomas Ertl

Abstract: With the advent of linked data sources, transportation information systems are no longer limited to indicating how to get from one location to another. They can suggest where to go shopping on the way or plan several synchronized itineraries for groups of travelers. Along with these developments, information about stopovers evolves from mere additional data to a crucial part of the itinerary. However, current time-based visualizations of itineraries cannot adequately convey the stopovers contained in an itinerary. We propose a time-location based itinerary visualization that can be used when planning trips, which allows for the easy comparison of itineraries with different routes, and for aligning itineraries of several travelers in collaborative scenarios. We describe the visualization concept and report on a user study that confirms the basic ideas and provides a number of insights on how the visualization can be developed further.

Paper Nr: 3
Title:

Interactive Visual Analysis of Lumbar Back Pain - What the Lumbar Spine Tells About Your Life

Authors:

Paul Klemm, Sylvia Glaßer, Kai Lawonn, Marko Rak, Henry Völzke, Katrin Hegenscheid and Bernhard Preim

Abstract: Epidemiology aims to provide insight into disease causations. Hence, subject groups (cohorts) are analyzed to correlate the subjects’ varying lifestyles, their medical properties and diseases. Recently, these cohort studies comprise medical image data. We assess potential relations between image-derived variables of the lumbar spine with lower back pain in a cross-sectional study. Therefore, an Interactive Visual Analysis (IVA) framework was created and tested with 2,540 segmented lumbar spine data sets. The segmentation results are evaluated and quantified by employing shape-describing variables, such as spine canal curvature and torsion. We analyze mutual dependencies among shape-describing variables and non-image variables, e.g., pain indicators. Therefore, we automatically train a decision tree classifier for each non-image variable. We provide an IVA technique to compare classifiers with a decision tree quality plot. As a first result, we conclude that image-based variables are only sufficient to describe lifestyle factors within the data. A correlation between lumbar spine shape and lower back pain could not be found with the automatically trained classifiers. However, the presented approach is a valuable extension for the IVA of epidemiological data. Hence, relations between non-image variables were successfully detected and described.

Paper Nr: 9
Title:

Edge-stacked Timelines for Visualizing Dynamic Weighted Digraphs

Authors:

Michael Burch, Tanja Munz and Daniel Weiskopf

Abstract: We investigate the problem of visually encoding time-varying weighted digraphs to provide an overview about dynamic graphs. Starting from a rough overview of dynamic relational data an analyst can subsequently explore the data in more detail to gain further insights. To reach this goal we first map the graph vertices in the graph sequence to a common horizontal axis. Edges between vertices are represented as stacked horizontal and color-coded links starting and ending at their corresponding start and end vertex positions. The direction of each edge is indicated by placing it either above or below the horizontal vertex line. We attach a vertically aligned timeline to each link to show the weight evolution for those links. The order of the vertices and stacked edges is important for the readability of the visualization. We support interactive reordering and sorting in the vertex, edge, and timeline representations. The usefulness of our edge-stacked timelines is illustrated in a case study showing dynamic call graph data from software development.

Paper Nr: 11
Title:

Information Visualization for CSV Open Data Files Structure Analysis

Authors:

Paulo Carvalho, Patrik Hitzelberger, Benoît Otjacques, Fatma Bouali and Gilles Venturini

Abstract: New and different information sources have appeared over the past years (e.g. Blogs, Media, Open Data, Scientific Data and Social Networks). The variety of these sources is growing and the related data volume increases exponentially. Open Data (OD) initiatives and platforms are one of the current major data producers, also because the topic seems to be important for many governments world-wide. Given the many fields and sectors involved, OD brings high business and societal potential. The amount and diversity of available information is high. However, analysing and understanding OD in order to exploit is far from being an easy task. Several problems and constraints must be solved. Information Visualization (InfoVis) can help to give a graphical idea of the processed files structure. Given that OD is provided very often as tabular data, this paper focuses on OD CSV files. It presents an overview on the analysis of tabular information. Finally, the paper describes the role of Information Visualization and the way it may help the end-user to understand quickly the structure and issues of OD CSV files.

Paper Nr: 12
Title:

Drawing Georeferenced Graphs - Combining Graph Drawing and Geographic Data

Authors:

Giordano Da Lozzo, Marco Di Bartolomeo, Maurizio Patrignani, Giuseppe Di Battista, Davide Cannone and Sergio Tortora

Abstract: We consider the task of visually exploring relationships (such as established connections, similarity, reachability, etc) among a set of georeferenced entities, i.e., entities that have geographic data associated with them. A novel 2.5D paradigm is proposed that provides a robust and practical solution based on separating and then integrating back again the networked and geographical dimensions of the input dataset. This allows us to easily cope with partial or incomplete geographic annotations, to reduce cluttering of close entities, and to address focus-plus-context visualization issues. Typical application domains include, for example, coordinating search and rescue teams or medical evacuation squads, monitoring ad-hoc networks, exploring location-based social networks and, more in general, visualizing relational datasets including geographic annotations.

Paper Nr: 25
Title:

Visualizing DynamicWeighted Digraphs with Partial Links

Authors:

Hansjörg Schmauder, Michael Burch and Daniel Weiskopf

Abstract: Graphs are traditionally represented as node-link diagrams, but these typically suffer from visual clutter when they become denser, i.e. more vertices and edges are present in the data set. Partial link drawings have been introduced for node-link diagrams aiming at reducing visual clutter caused by link crossings. Although this concept was shown to perform well for some parameter settings, it has not been used for visually encoding dynamic weighted digraphs. In this paper we investigate the problem of visualizing time-varying graphs as one node-link diagram in a specific layout by exploiting the links as timelines. Partially drawn links are used to show the graph dynamics by splitting each link into as many segments as time steps have to be represented. Conventional 2D layout algorithms can be applied while simultaneously showing the evolution over time. Color-coded links represent the changing weights. We use tapered links to reduce possible overlaps at the link target nodes that would occur when using traditional arrow-based directed links. We experiment with different graph layouts and different numbers of data dimensions, i.e. number of vertices, edges, and time steps. We illustrate the usefulness of the technique in a case study investigating dynamic migration data.

Paper Nr: 34
Title:

Performance Assessment and Interpretation of Random Forests by Three-dimensional Visualizations

Authors:

Ronny Hänsch and Olaf Hellwich

Abstract: Ensemble learning techniques and in particular Random Forests have been one of the most successful machine learning approaches of the last decade. Despite their success, there exist barely suitable visualizations of Random Forests, which allow a fast and accurate understanding of how well they perform a certain task and what leads to this performance. This paper proposes an exemplar-driven visualization illustrating the most important key concepts of a Random Forest classifier, namely strength and correlation of the individual trees as well as strength of the whole forest. A visual inspection of the results enables not only an easy performance evaluation but also provides further insights why this performance was achieved and how parameters of the underlying Random Forest should be changed in order to further improve the performance. Although the paper focuses on Random Forests for classification tasks, the developed framework is by no means limited to that and can be easily applied to other tree-based ensemble learning methods.

Paper Nr: 37
Title:

The Visualization of Drama Hierarchies

Authors:

Vincenzo Lombardo and Antonio Pizzo

Abstract: Drama, the art that displays characters performing live actions in telling a story, is pervasive in cultures and media. The study of drama often resorts to hierarchical structures to explain the sequences of incidents that occur. Hierarchies provide an explanation of why incidents are in the sequence or cluster elements into subsequences that form a meaningful structure. This paper addresses the visualization of drama hierarchies. The paper inspects the peculiar features of drama hierarchies and proposes a visualization built upon the metaphors of tree mapping and timeline, respectively. The visualizations are preliminarily applied in tasks of analysis and interpretation in supporting teaching and research of drama scholars.

Paper Nr: 42
Title:

The Recursive Disk Metaphor - A Glyph-based Approach for Software Visualization

Authors:

Richard Müller and Dirk Zeckzer

Abstract: In this paper, we present the recursive disk metaphor, a glyph-based visualization for software visualization. The metaphor represents all important structural aspects and relations of software using nested circular glyphs. The result is a shape with an inner structural consistency and a completely defined orientation. We compare the recursive disk metaphor to other state-of-the-art 2D approaches that visualize structural aspects and relations of software. Further, a case study shows the feasibility and scalability of the approach by visualizing an open source software system in a browser.

Posters
Paper Nr: 24
Title:

Visualization of Large Scientific Datasets - Analysis of Numerical Simulation Data and Astronomical Surveys Catalogues

Authors:

Bruno Thooris and Daniel Pomarède

Abstract: In the context of our project COAST (for Computational Astrophysics), a program of massively parallel numerical simulations in astrophysics involving astrophysicists and software engineers, we have developed visualization tools to analyse the massive amount of data produced in these simulations. We present in this paper the SDvision code capabilities with examples of visualization of cosmology and astrophysical simulations realized with hydrodynamics codes, and more results in other domains of physics, like plasma or particles physics. Recently, the SDvision 3D visualization software has been improved to cope with the analysis of astronomical surveys catalogues, databases of multiple data products including redshifts, peculiar velocities, reconstructed density and velocity fields. On the basis of the various visualization techniques offered by the SDvision software, that rely on multicore computing and OpenGL hardware acceleration, we have created maps displaying the structure of the Local Universe where the most prominent features such as voids, clusters of galaxies, filaments and walls, are identified and named.

Paper Nr: 29
Title:

CereVA - Visual Analysis of Functional Brain Connectivity

Authors:

Michael de Ridder, Karsten Klein and Jinman Kim

Abstract: We present CereVA, a web-based interface for the visual analysis of brain activity data. CereVA combines 2D and 3D visualizations and allows the user to interactively explore and compare brain activity data sets. The web-based interface combines several linked graphical representations of the network data, allowing for tight integration of different visualizations. The data is presented in the anatomical context within a 3D volume rendering, by node-link visualizations of connectivity networks, and by a matrix view of the data. In addition, our approach provides graph-theoretical analysis of the connectivity networks. Our solution supports several analysis tasks, including the comparison of connectivity networks, the analysis of correlation patterns, and the aggregation of networks, e.g. over a population.

Paper Nr: 31
Title:

Automatic Illustration of Short Texts via Web Images

Authors:

Sandro Aldo Aramini, Edoardo Ardizzone and Giuseppe Mazzola

Abstract: In this paper we propose a totally unsupervised and automatic illustration method, which aims to find onto the Web a set of images to illustrate the content of an input short text. The text is modelled as a semantic space and a set of relevant keywords is extracted. We compare and discuss different methods to create semantic representations by keyword extraction. Keywords are used to query Google Image Search engine for a list of relevant images. We also extract information from the Web pages that include the retrieved images, to create an Image Semantic Space, which is compared to the Text Semantic Space in order to rank the list of retrieved images. Tests showed that our method achieves very good results, which overcome those obtained by using a state-of-the-art application. Furthermore we developed a Web tool to test our system and evaluate results within the Internet community.

Paper Nr: 35
Title:

MTTV - An Interactive Trajectory Visualization and Analysis Tool

Authors:

Fabio Poiesi and Andrea Cavallaro

Abstract: We present an interactive visualizer that enables the exploration, measurement, analysis and manipulation of trajectories. Trajectories can be generated either automatically by multi-target tracking algorithms or manually by human annotators. The visualizer helps understanding the behavior of targets, correcting tracking results and quantifying the performance of tracking algorithms. The input video can be overlaid to compare ideal and estimated target locations. The code of the visualizer (C++ with openFrameworks) is open source.

Paper Nr: 47
Title:

A Visual Analytics based Investigation on the Authorship of the Holy Quran

Authors:

Halim Sayoud

Abstract: In this paper, we present a visual analytics based investigation for the task of authorship attribution of the holy Quran with regards to the Hadith Author (the Prophet). This can be seen as an authorship discrimination task between the two religious books: Quran vs Hadith. The first book represents the Divine book written by Allah (God) as claimed by the Prophet Muhammad, whereas the second one represents a collection of certified Prophet’s statements. Two visual analytics clustering methods are employed, namely: a Hierarchical Clustering and Fuzzy C-mean Clustering. On the other hand, seven types of NLP features are combined and normalized by PCA reduction before the classification process. The visual analytics results have revealed interesting results in 2D and 3D disposition. In summary, they show two main clusters in both experiments: Quran cluster and Hadith cluster; and the disposition of the resulting clusters corresponds to a clear authorship distinction between the two religious books.

Paper Nr: 50
Title:

Convex Hull Brushing in Scatter Plots - Multi-dimensional Correlation Analysis

Authors:

Miguel Nunes, Kresimir Matkovic and Katja Bühler

Abstract: Interactive Visual Analysis has been widely used for the reason that it allows users to investigate highly complex data in coordinated multiple views, showing different perspectives over data. In order to relate data, multiple techniques of brushing have been introduced. This work extends the state of the art by introducing the Convex Hull (CH) Brush, which is a new way of selecting and interpreting high dimensional data in scatter plot (SP) views. By using a combination of brushes through linked views, the CH-Brush allows the selection and clustering of values that are not typically defined by SP ranges, in spite of sharing similarities. In CHBrushing is also able to visually report the existence of correlation between variables. Furthermore, we discuss CH-Brushing sensitivity and the application of smoothness. We use synthetic data to support our rationale and clarify the intrinsic meanings of CH-Brushing in scatter plots. We also report on the first experience on using the CH-Brush in a real-world medical case.

Area 2 - General Data Visualization

Full Papers
Paper Nr: 19
Title:

Leaf Glyph - Visualizing Multi-dimensional Data with Environmental Cues

Authors:

Johannes Fuchs, Dominik Jäckle, Niklas Weiler and Tobias Schreck

Abstract: In exploratory data analysis, important analysis tasks include the assessment of similarity of data points, labeling of outliers, identifying and relating groups in data, and more generally, the detection of patterns. Specifically, for large data sets, such tasks may be effectively addressed by glyph-based visualizations. Appropriately defined glyph designs and layouts may represent collections of data to address these aforementioned tasks. Important problems in glyph visualization include the design of compact glyph representations, and a similarity or structure-preserving 2D layout. Projection-based techniques are commonly used to generate layouts, but often suffer from over-plotting in 2D display space, which may hinder comparing and relating tasks. We introduce a novel glyph design for visualizing multi-dimensional data based on an environmental metaphor. Motivated by the humans ability to visually discriminate natural shapes like trees in a forest, single flowers in a flower-bed, or leaves at shrubs, we design a leaf-shaped data glyph, where data controls main leaf properties including leaf morphology, leaf venation, and leaf boundary shape. We also define a custom visual aggregation scheme to scale the glyph for large numbers of data records. We show by example that our design is effectively interpretable to solve multivariate data analysis tasks, and provides effective data mapping. The design also provides an aesthetically pleasing appearance, which may help spark interest in data visualization by larger audiences, making it applicable e.g., in mass media.

Short Papers
Paper Nr: 23
Title:

Effect of Displaying Uncertainty in Line and Bar Charts - Presentation and Interpretation

Authors:

D. van der Laan, Edwin de Jonge and Jessica Solcer

Abstract: This paper investigates the effect of presenting uncertainty in bar and line charts in trend-finding and comparison tasks. Different options for presenting uncertainty were investigated in a carefully designed user evaluation that was conducted on statistical analysts, policy makers and journalists (N = 108). The study includes exploring several options for displaying interval estimates with and without point estimates in line and bar charts. We discuss the results for all options and derive presentation suggestions. Our study indicates that showing uncertainty improves the validity of user statements and that data without point estimates have different display needs.

Paper Nr: 28
Title:

Visualisation of Heterogeneous Data with the Generalised Generative Topographic Mapping

Authors:

Michel F. Randrianandrasana, Shahzad Mumtaz and Ian T. Nabney

Abstract: Heterogeneous and incomplete datasets are common in many real-world visualisation applications. The probabilistic nature of the Generative Topographic Mapping (GTM), which was originally developed for complete continuous data, can be extended to model heterogeneous (i.e. containing both continuous and discrete values) and missing data. This paper describes and assesses the resulting model on both synthetic and real-world heterogeneous data with missing values.

Paper Nr: 45
Title:

Visual Recommendations for Scientific and Cultural Content

Authors:

Eduardo Veas, Belgin Mutlu, Cecilia di Sciascio, Gerwald Tschinkel and Vedran Sabol

Abstract: Supporting individuals who lack experience or competence to evaluate an overwhelming amout of information such as from cultural, scientific and educational content makes recommender system invaluable to cope with the information overload problem. However, even recommended information scales up and users still need to consider large number of items. Visualization takes a foreground role, letting the user explore possibly interesting results. It leverages the high bandwidth of the human visual system to convey massive amounts of information. This paper argues the need to automate the creation of visualizations for unstructured data adapting it to the user’s preferences. We describe a prototype solution, taking a radical approach considering both grounded visual perception guidelines and personalized recommendations to suggest the proper visualization.

Paper Nr: 51
Title:

The Aesthetics of Diagrams

Authors:

Michael Burch

Abstract: Diagrammatic representations are omnipresent and are used in various application domains. One of their major goal, in particular for information visualization, is to make data visual in a way that a spectator can easily understand the graphical encoding to finally derive insights from the data. As we see, there are various different ways to visually depict data by using visual features in various combinations. In this paper we come up with some thoughts about existing diagram styles, for which we first discuss the benefits and drawbacks of each of them focusing on aesthetics based on readability. Additionally, we describe some initial results on the aesthetics of diagrams which we recorded in a web-based experiment. In this, we asked participants to vote for one of two given diagrams of a given repertoire of 70 of them covering all examined aspects which focuses more on aesthetics in the sense of beauty, not readability. The major result of this experiment unhides a trend towards colored, 3D, and radial diagrams which stands somewhat in contrast to readability user studies in information visualization oftentimes tending towards 2D and Cartesian diagrams for data exploration.

Paper Nr: 53
Title:

A Concept for the Exploratory Visualization of Patent Network Dynamics

Authors:

Florian Windhager, Albert Amor-Amorós, Michael Smuc, Paolo Federico, Lukas Zenk and Silvia Miksch

Abstract: Patents, archived as large collections of semi-structured text documents, contain valuable information about historical trends and current states of R&D fields, as well as performances of single inventors and companies. Specific methods are needed to unlock this information and enable its insightful analysis by investors, executives, funding agencies, and policy makers. In this position paper, we propose an approach based on modelling patent repositories as multivariate temporal networks, and examining them by the means of specific visual analytics methods. We illustrate the potential of our approach by discussing two use-cases: the determination of emerging research fields in general and within companies, as well as the identification of inventors characterized by different temporal paths of productivity.

Posters
Paper Nr: 5
Title:

Report Optimization using Visual Search Strategies - An Experimental Study with Eye Tracking Technology

Authors:

Lisa Falschlunger, Christoph Eisl, Heimo Losbichler and Elisabeth Grabmann

Abstract: The success of visualisations is determined by the ability of users to retrieve relevant information in an effective and efficient way. The way in which information is perceived can be analysed by examining visual search strategies of users. Visual search strategies in graphical representations however, are individual and have not been well explored up to now. Recent studies show that eye tracking experiments help in gaining new insights into these strategies. Apart from error rates and task completion times, eye tracking focuses on the way observers of visualisations read and make sense of the presented stimulus. In this way sequential strategies can be analysed, compared and used in order to optimize graphical layouts. In this study we use the approach of Parallel Scan Path visualisation in combination with Levenshtein Distance to determine similarities between search strings when viewing graphical representations in standardized business communication. This study shows a positive correlation between search strategies and task completion time and allows the evaluation of different design layouts. Positive significant effects can be detected when examining experience (with respect to standardized and repetitive reporting) and layout optimization (with respect to graphical representations and page layout). Optimal search strategies can be identified when users are experienced and using an optimized layout.

Paper Nr: 22
Title:

Geometric Encoding, Filtering, and Visualization of Genomic Sequences

Authors:

Helena Cristina da Gama Leitão, Rafael Felipe Veiga Saracchini and Jorge Stolfi

Abstract: This article describes a three-channel encoding of nucleotide sequences, and proper formulas for filtering and downsampling such encoded sequences for multi-scale signal analysis. With proper interpolation, the encoded sequences can be visualized as curves in three-dimensional space. The filtering uses Gaussian-like smoothing kernels, chosen so that all levels of the multi-scale pyramid (except the original curve) are practically free from aliasing artifacts and have the same degree of smoothing. With these precautions, the overall shape of the space curve is robust under small changes in the DNA sequence, such as single-point mutations, insertions, deletions, and shifts.

Paper Nr: 32
Title:

Time-series Application on Big Data - Visualization of Consumption in Supermarkets

Authors:

Catarina Maçãs, Pedro Cruz, Hugo Amaro, Evgheni Polisciuc, Tiago Carvalho, Frederico Santos and Penousal Machado

Abstract: The evolution of technology is changing how people work within organizations. Information about customer consumption leads to a new era of business intelligence, wherein Big Data is analyzed to improve business. In this project we apply information visualization in the context of Big Data for product’s consumption. The aim of this project is to visualize the evolution of consumption, to detect typical and periodic behaviors and emphasize the atypical ones. In this article we present our workflow—from finding periodic behaviors to create a final visualization using time-series and small-multiples techniques. With the final visualization we are able to show consumption behaviors and highlight the deviations from typical consumption days.

Paper Nr: 38
Title:

Towards Highly Affine Visualizations of Consumption Data from Buildings

Authors:

Matthias Nielsen and Kaj Grønbæk

Abstract: This paper presents a novel approach AffinityViz to visualize live and aggregated consumption data from multistory buildings. The objective of the approach is to provide a generic but high affinity relation between real buildings’ spatial layouts and the consumption data visualizations. Current approaches come short on maintaining such affinity. This implies an avoidable cognitive load on users such as energy managers and facility managers who need to monitor consumption and make decisions from consumption data. To alleviate this we have transformed three conventional types of visualizations into highly affine visualizations lowering the cognitive load for users. The contributions are: 1) Development of the AffinityViz techniques featuring three generic designs of highly affine visualizations of consumption data. 2) Comparison of the affine visualizations with the conventional visualizations. 3) Initial evaluation of the AffinityViz designs by expert users on real world data. Finally, the design challenges of AffinityViz are discussed, including prospects for AffinityViz as a future tool for visual analysis of data from buildings.

Area 3 - Spatial Data Visualization

Full Papers
Paper Nr: 30
Title:

Analyzing the Effect of Lossy Compression on Particle Traces in Turbulent Vector Fields

Authors:

Marc Treib, Kai Bürger, Jun Wu and Rüdiger Westermann

Abstract: We shed light on the accuracy of particle trajectories in turbulent vector fields when lossy data compression is used. So far, data compression has been considered rather hesitantly due to supposed accuracy issues. Motivated by the observation that particle traces are always afflicted with inaccuracy, we quantitatively analyze the additional inaccuracies caused by lossy compression. In some experiments we confirm that the compression has only minor impact on the accuracy of the trajectories. Even though our experiments are not generally valid, they indicate that a more thorough analysis of the error in particle integration due to compression is necessary, and that in some cases lossy compression is valid and can significantly reduce performance limitations due to memory and communication bandwidth.

Short Papers
Paper Nr: 8
Title:

3DArcLens: Interactive Network Analysis on Geographic Surfaces

Authors:

Alberto Debiasi, Bruno Simões and Raffaele De Amicis

Abstract: Geographic datasets such as international telecommunications traffic, financial flows, trading patterns, and national migration patterns describe the movement of entities between geographical locations. In spatial relations analyses the exact route of the connections is not important. Hence, one of the most preferred methods for its depiction is a graph representation with data nodes layered over a geographical surface (such as a flat map or a virtual globe). However, a large number of arcs can produce dense visual clutters that make difficult the extraction of information from: occluded geographical surfaces, occluded nodes and occluded arcs. In this work we present a novel focus+context technique for 3D virtual environments that interactively distorts and filters arcs layouts, revealing underneath information about the three aforementioned visual elements: nodes, arcs and geographical surface. Moreover, changing the camera does not affect the geographical focus of the lens. In our use cases, we observed that such technique is an advantage for tasks that include the exploration of geographical networks.

Paper Nr: 52
Title:

Web-based Visualization Platform for Geospatial Data

Authors:

Martin Hecher, Christoph Traxler, Gerd Hesina, Anton Fuhrmann and Dieter Fellner

Abstract: This paper describes a new platform for geospatial data analysis. The main purpose is to explore new ways to visualize and interact with multidimensional satellite data and computed models from various Earth Observation missions. The new V-MANIP platform facilitates a multidimensional exploring approach that allows to view the same dataset in multiple viewers at the same time to efficiently find and explore interesting features within the shown data. The platform provides visual analytics capabilities including viewers for displaying 2D or 3D data representations, as well as for volumetric input data. Via a simple configuration file the system can be configured for different stakeholder use cases, by defining desired data sources and available viewer modules. The system architecture, which will be discussed in this paper in detail, uses Open Geospatial Consortium web service interfaces to allow an easy integration of new visualization modules. The implemented software is based on open source libraries and uses modern web technologies to provide a platform-independent, plugin free user experience.

Posters
Paper Nr: 39
Title:

Arc and Swarm-based Representations of Customer’s Flows among Supermarkets

Authors:

Evgheni Polisciuc, Pedro Cruz, Hugo Amaro, Catarina Maçãs, Tiago Carvalho, Frederico Santos and Penousal Machado

Abstract: Representing large amounts of flows involves dealing with the representation of directionality and the reduction of visual cluttering. This article describes the application of two flow representation techniques to the visualization of transitions of customers among supermarkets over time. The first approach relies in arc representations together with a combination of methods to represent directionality of transitions. The other approach uses a swarm-based system in order to reduce visual clutter, bundling edges in an organic fashion and improving clarity.

Paper Nr: 44
Title:

OpenGLSL-based Raycasting - Comparison of Execution Durations of Multi-pass vs. Single-pass Technique

Authors:

Stefan Maas and Heinrich Martin Overhoff

Abstract: Real time volume rendering of medical datasets using raycasting on graphics processing units (GPUs) is a common technique. Since more than 10 years there are two established approaches for realizing GPU ray casting: multi-pass (Kruger and Westermann, 2003) and single-pass (Röttger, et al., 2003). But the required parameters to choose the optimal raycasting technique for a given application are still unknown. To solve this issue both raycasting techniques were implemented for different raycasting types using OpenGLSL vertex and fragment shaders. The different techniques and types were compared regarding execution times. The results of this comparison show that there is no technique faster in general. The higher the computational load the more indicates the use of the multi-pass technique.