IVAPP 2016 Abstracts


Area 1 - Abstract Data Visualization

Full Papers
Paper Nr: 1
Title:

TagSpheres: Visualizing Hierarchical Relations in Tag Clouds

Authors:

Stefan Jänicke and Gerik Scheuermann

Abstract: Tag clouds are widely applied, popular visualization techniques as they illustrate summaries of textual data in an intuitive, lucid manner. Many layout algorithms for tag clouds have been developed in the recent years, but none of these approaches is designed to reflect the notion of hierarchical distance. For that purpose, we introduce a novel tag cloud layout called TagSpheres. By arranging tags on various hierarchy levels and applying appropriate colors, the importance of individual tags to the observed topic gets assessable. To explore relationships among various hierarchy levels, we aim to place related tags closely. Three usage scenarios from the digital humanities, sports and aviation, and an evaluation with humanities scholars exemplify the applicability and point out the benefit of TagSpheres.

Paper Nr: 2
Title:

Visual Analytics for Narrative Text - Visualizing Characters and their Relationships as Extracted from Novels

Authors:

Markus John, Steffen Lohmann, Steffen Koch, Michael Wörner and Thomas Ertl

Abstract: The study of novels and the analysis of their plot, characters and other entities are time-consuming and complex tasks in literary science. The digitization of literature and the proliferation of electronic books provide new opportunities to support these tasks with visual abstractions. Methods from the fields of computational linguistics can be used to automatically extract entities and their relations from digitized novels, which can then be visualized to ease exploration and analysis tasks. This paper presents a web-based approach that combines automatic analysis methods with effective visualization techniques. Different views on the extracted entities are provided and relations between them across the plot are indicated. Two usage scenarios show successful applications of the approach and demonstrate its benefits and limitations.

Paper Nr: 10
Title:

Content based Computational Chromatic Adaptation

Authors:

Fatma Kerouh, Djemel Ziou and Nabil Lahmar

Abstract: Chromatic adaptation is needed to accurately reproduce the color appearance of an image. Imaging systems have to apply a transform to convert a color of an image captured under an input illuminant to another output illuminant. This transform is called Chromatic Adaptation Transform (CAT). Different CATs have been proposed in the literature such as von Kries, Bradford and Sharp. Both these transforms consider the adjustment of all the image spatial contents (edges, texture and homogeneous area) in the same way. Our intuition is that, CATs behave differently on the image spatial content. To verify that, we prospect to study the well known CATs effect on the image spatial content, according to some objective criteria. Based on observations we made, a new CAT is derived considering the image spatial content. To achieve that, suitable requirements for CAT are revised and re-written in a variational formalism. Encouraging results are obtained while comparing the proposed CAT to some known ones.

Paper Nr: 18
Title:

VESPa: A Pattern-based Visual Query Language for Event Sequences

Authors:

Florian Haag, Robert Krüger and Thomas Ertl

Abstract: Movement data can often be enriched with additional information that enables analysts to ask new questions, for instance about POIs visited and meetings that imply interactions between persons. Information on spatio-temporal events such as visits or meetings can be especially valuable for digital forensics, marketing analysis, and urban planning. Most existing query languages for movement data, however, do not take that additional information into account. We address this gap by proposing VESPa, a pattern-based graphical query language to express, check, and refine hypotheses about spatio-temporal event sequences. Using VESPa, the analyst can sketch abstract assumptions and use the pattern to query the data for matches. The applicability of our approach is demonstrated in two case studies with different datasets. We also report on a small user study in which several construction and comprehension tasks were successfully solved in an interactive implementation of the concept.

Paper Nr: 20
Title:

Improved Identification of Data Correlations through Correlation Coordinate Plots

Authors:

Hoa Nguyen and Paul Rosen

Abstract: Correlation is a powerful relationship measure used in science, engineering, and business to estimate trends and make forecasts. Visualization methods, such as scatterplots and parallel coordinates, are designed to be general, supporting many visualization tasks, including identifying correlation. However, due to their generality, they do not provide the most efficient interface, in terms of speed and accuracy. This can be problematic when a task needs to be repeated frequently. To address this shortcoming, we propose a new correlation task-specific visualization method called Correlation Coordinate Plots (CCPs). CCPs transform data into a powerful coordinate system for estimating the direction and strength of correlation. To support multiple attributes, we propose 2 additional interfaces. The first is the Snowflake Visualization, a focus+context layout for exploring all pairwise correlations. The second enhances the basic CCP by using principal component analysis to project multiple attributes. We validate CCP performance in correlation-specific tasks through an extensive user study that shows improvement in both accuracy and speed.

Paper Nr: 23
Title:

A Directed Concept Search Environment to Visually Explore Texts Related to User-defined Concept Models

Authors:

Muhammad Faisal Cheema, Stefan Jänicke, Judith Blumenstein and Gerik Scheuermann

Abstract: We introduce a concept search environment that caters for the needs of humanities scholars who want to improve the accuracy of search results when querying historical text corpora. For this purpose, we designed a so-called Concept Editor that allows to model historical concepts in a diagram style according to the imaginations of the humanities scholar. For the inspection of results determined in the proposed concept search, we provide a Concept Search Results Viewer that uses the existent layout of the underlying concept model to visualize related texts according to the relevance to the given concept. We further designed the overall system the way that the humanities scholar can iteratively refine the concept idea, which leads to a gradual improvement of search results. To illustrate the whole development pipeline, we provide a usage scenario on modeling the concept epilepsy with the purpose of improving the accuracy of results compared to usual applied keyword-based search methods.

Paper Nr: 27
Title:

StreetExplorer: Visual Exploration of Feature-based Patterns in Urban Street Networks

Authors:

Lin Shao, Sebastian Mittelstädt, Ran Goldblatt, Itzhak Omer, Peter Bak and Tobias Schreck

Abstract: The analysis of street networks is an important problem in applications like city planning, comparison of urban street properties, or transportation network analysis. Graph-theoretic computation schemes today provide street network analysts with a range of topological features relating e.g., to connectivity properties of street networks. Typically, an abundance of different network features is available, and some or all of these features may be relevant for within- and between comparison tasks at different scales across the network. Therefore, it is desirable to interactively explore the large segment feature space, with the goal of finding interesting patterns based on extracted features, taking into account also the geospatial properties of a given network. We introduce StreetExplorer, an interactive visualization system for the exploration of global and local properties of urban street networks. The system is based on a set of appropriate similarity functions, which take into account both topological and geometric features of a street network. Together with a set of suitable interaction functions that allow the selection of portions of a given street network, we support the analysis and comparison of street network properties between and across features and areas. We enhance the visual comparison of street network patterns by a suitable color-mapping and boosting scheme to visualize both the similarity between street network portions as well as the distribution of network features on the segment level. Together with experts from the urban morphology analysis domain, we apply our approach to analyze and compare two urban street networks, identifying patterns of historic development and modern planning approaches, demonstrating the usefulness of StreetExplorer.

Short Papers
Paper Nr: 3
Title:

Visualizing Network Flows and Related Anomalies in Industrial Networks using Chord Diagrams and Whitelisting

Authors:

Mikel Iturbe, Iñaki Garitano, Urko Zurutuza and Roberto Uribeetxeberria

Abstract: Industrial Control Systems are the set of specialized elements that monitor and control physical processes. Those systems are normally interconnected forming environments known as industrial networks. The particularities of these networks disallow the usage of traditional IT security mechanisms, while allowing other security strategies not suitable for IT networks. As industrial network traffic flows follow constant and repetitive patterns, whitelisting has been proved a viable approach for anomaly detection in industrial networks. In this paper, we present a network flow and related alert visualization system based on chord diagrams. The system represents the detected network flows within a time interval, highlighting the ones that do not comply the whitelisting rules. Moreover, it also depicts the network flows that, even if they are registered in the whitelist, have not been detected on the selected time interval (e.g. a host is down). Finally, the visualization system is tested with network data coming from a real industrial network.

Paper Nr: 7
Title:

Schematization of Clutter Reduction Techniques in Geographic Node-link Diagrams using Task-based Criteria

Authors:

Alberto Debiasi, Bruno Simões and Raffaele De Amicis

Abstract: Visual clutter is a hot topic in the domain of node-link diagrams as it negatively affects usability, aesthetics and data interpretation. The organization of items, i.e. the way nodes and links are positioned in the display, is one problem among many that leads to visual clutter. In previous work, different techniques were proposed to reduce the clutter that depends on the organization of nodes and links. However, a schematization of such techniques by task was never considered. Approaching the problem by task would be more efficient since visual clutter, by definition, depends on the task to be performed. In this paper, we propose a solution to visual clutter driven by the type of task. In particular, the aim of our work is to provide an answer to the following question: Given a task and a geographic node-link diagram, which are the appropriated techniques to reduce the visual clutter that depends on the spatial organization of nodes and links. In our solution, we have classified tasks into a limited number of task groups. For each tasks group, we have identified and analyzed issues leading to a performance degradation. The final outcome consists on a list of good candidate techniques for each task group. The selected techniques are the results of a survey that selects only approaches that act on the position of nodes and links.

Paper Nr: 24
Title:

Visual Analytics Towards Tool Interoperabilty - A Position Paper

Authors:

Didem Gürdür, Fredrik Asplund, Jad El-khoury, Frederic Loiret and Martin Törngren

Abstract: Complex-engineering projects include artefacts from several engineering disciplines such as mechanical, electrical, software components, processes and plans. While software tools can be powerful in each individual discipline, it is difficult to build integrated tool chains. Moreover, it is challenging to evaluate and update existing tool chains. At the same time, the field of visualization is getting mature and visual analytics promises an opportunity to develop knowledge, methods, technologies and practice for exploiting and combining the strengths of human and data. We consider this as a potential to evaluate current tool chains. This position paper discusses the visualization and visual analytics practices to assess existing tool chains performance.

Paper Nr: 32
Title:

Software Visualization via Hierarchic Micro/Macro Layouts

Authors:

Martin Nöllenburg, Ignaz Rutter and Alfred Schuhmacher

Abstract: We propose a system for visualizing the structure of software in a single drawing. In contrast to previous work we consider both the dependencies between different entities of the software and the hierarchy imposed by the nesting of classes and packages. To achieve this, we generalize the concept of micro/macro layouts introduced by Brandes and Baur (Baur and Brandes, 2008) to graphs that have more than two hierarchy levels. All entities of the software (e.g., attributes, methods, classes, packages) are represented as disk-shaped regions of the plane. The hierarchy is expressed by containment, all other relations, e.g., inheritance, functions calls and data access, are expressed by directed edges. As in the micro/macro layouts of Brandes and Baur, edges that “traverse” the hierarchy are routed together in channels to enhance the clarity of the layout. The resulting drawings provide an overview of the coarse structure of the software as well as detailed information about individual components.

Posters
Paper Nr: 9
Title:

Gaining Insight from Physical Activity Data using a Similarity-based Interactive Visualization

Authors:

Arkaitz Artetxe, Gorka Epelde, Andoni Beristain, Ane Murua and Roberto Álvarez

Abstract: This paper presents a new interactive visualization approach which aims to help and support the user in gaining insight over his physical activity data. The main novelty of the proposed visualization approach is the representation of similarities in the physical activity patterns in time using data clustering techniques, in addition to the continuous physical activity representation over a circular chart. This grouping of similar activity patterns helps identifying meaningful events or behaviors, combined with the periodicity highlighting circular charts. The user is able to interact with the visualization during the knowledge discovery process by changing the represented time-scale, time-frame and the number of clusters used for the user’s physical activity pattern categorization. Additionally, the proposed visualization approach allows to easily report and store the insights gained during the visual data analysis process, by adding a textual description linked to the particular user tailored visualization configuration which led to that insight.

Paper Nr: 14
Title:

Acquisition of Scientific Literatures based on Citation-reason Visualization

Authors:

Dongli Han, Hiroshi Koide and Ayato Inoue

Abstract: When carrying out scientific research, the first step is to acquire relevant papers. It is easy to grab vast numbers of papers by inputting a keyword into a digital library or an online search engine. However, reading all the retrieved papers to find the most relevant ones is agonizingly time-consuming. Previous works have tried to improve paper search by clustering papers with their mutual similarity based on reference relations, including limited use of the type of citation (e.g. providing background vs. using specific method or data). However, previously proposed methods only classify or organize the papers from one point of view, and hence not flexible enough for user or context-specific demands. Moreover, none of the previous works has built a practical system based on a paper database. In this paper, we first establish a paper database from an open-access paper source, then use machine learning to automatically predict the reason for each citation between papers, and finally visualize the resulting information in an application system to help users more efficiently find the papers relevant to their personal uses. User studies employing the system show the effectiveness of our approach.

Paper Nr: 15
Title:

Interactive Revision Exploration using Small Multiples of Software Maps

Authors:

Willy Scheibel, Matthias Trapp and Jürgen Döllner

Abstract: To explore and to compare different revisions of complex software systems is a challenging task as it requires to constantly switch between different revisions and the corresponding information visualization. This paper proposes to combine the concept of small multiples and focus+context techniques for software maps to facilitate the comparison of multiple software map themes and revisions simultaneously on a single screen. This approach reduces the amount of switches and helps to preserve the mental map of the user. Given a software project the small multiples are based on a common dataset but are specialized by specific revisions and themes. The small multiples are arranged in a matrix where rows and columns represents different themes and revisions, respectively. To ensure scalability of the visualization technique we also discuss two rendering pipelines to ensure interactive frame-rates. The capabilities of the proposed visualization technique are demonstrated in a collaborative exploration setting using a high-resolution, multi-touch display.

Paper Nr: 29
Title:

Exploration of Component Diagrams with Multifocal Highlighting

Authors:

Ladislav Cmolik and Lukas Holy

Abstract: In the paper we present multifocal highlighting in reverse engineered component diagrams to support software engineers in answering questions on relations between a number of components. With component oriented systems such questions arise quite often. We use color to highlight all components relevant to selected focus components. Further, we allow the users to filter the diagram. Our approach, unlike the state-of-the-art methods allows analysis of relations between dozens of components. We have performed an user study to evaluate our multifocal highlighting. The results of the subjective evaluation show that the multifocal highlighting supports software engineers in answering questions on relations between components.

Area 2 - General Data Visualization

Full Papers
Paper Nr: 22
Title:

MUVTIME: A Multivariate Time Series Visualizer for Behavioral Science

Authors:

Emanuel Sousa, Tiago Malheiro, Estela Bicho, Wolfram Erlhagen, Jorge Santos and Alfredo Pereira

Abstract: As behavioral science becomes progressively more data driven, the need is increasing for appropriate tools for visual exploration and analysis of large datasets, often formed by multivariate time series. This paper describes MUVTIME, a multimodal time series visualization tool, developed in Matlab that allows a user to load a time series collection (a multivariate time series dataset) and an associated video. The user can plot several time series on MUVTIME and use one of them to do brushing on the displayed data, i.e. select a time range dynamically and have it updated on the display. The tool also features a categorical visualization of two binary time series that works as a high-level descriptor of the coordination between two interacting partners. The paper reports the successful use of MUVTIME under the scope of project TURNTAKE, which was intended to contribute to the improvement of human-robot interaction systems by studying turn-taking dynamics (role interchange) in parent-child dyads during joint action.

Paper Nr: 34
Title:

Flow Map of Products Transported among Warehouses and Supermarkets

Authors:

Evgheni Polisciuc, Pedro Cruz, Hugo Amaro, Catarina Maçãs and Penousal Machado

Abstract: Representing large amounts of data using flow maps involves dealing with the reduction of visual cluttering. This article presents a method for generating flow maps and visualizing products being transported from warehouse to supermarkets in a major retail company in Portugal. Our approach uses a swarm-based system to reduce visual clutter, bundling edges in an organic fashion and improving clarity. Additionally, the Dorling cartograms technique is applied to reduce overlapping of graphical elements that render locations in geographic space. Finally, different design decisions enable a multi-perspective visualization of the same dataset.

Short Papers
Paper Nr: 13
Title:

The Eye-tracking Study of the Line Charts in Dashboards Design

Authors:

Pavel A. Orlov, Tatiana Ermolova, Vladimir Laptev, Alexey Mitrofanov and Vladimir Ivanov

Abstract: Dashboards are an important field for an investigation as they are the visual part of the management information systems. Our study aimed to find out the effects of the changes in the types and numbers of line graphs that can be displayed on a single screen simultaneously. Two laboratory experiments were conducted using an eye-tracker to find out how subjects' perception of line graphs on dashboards changes with increase in graph numbers, changes in sizes and increase of the overall area taken up by the graphs on the screen. We show that if the graphs take up the same area, the subjects perceive the line graphs displayed simultaneously in a similar manner. If the subjects are shown an increasing number of graphs of the same size, the subjects take longer to respond to tasks and have higher fixation count per each stimuli. The study revealed that there is no correlation between graph's slope (trend) and subjects' perception.

Paper Nr: 16
Title:

Healthcare Data Visualization: Geospatial and Temporal Integration

Authors:

Shenhui Jiang, Shiaofen Fang, Sam Bloomquist, Jeremy Keiper, Mathew Palakal, Yuni Xia and Shaun Grannis

Abstract: Healthcare data visualization is challenging due to the needs for integrating geospatial information, temporal information, text information, and heterogenious health attributes within a common visual context. We recently developed a web-based healthcare data visualization system, Health-Terrain, based on a Notifiable Condition Detector (NCD) use case. In this paper, we will describe this system, with emphasis on the visualization techniques developed specifically for healthcare data. Two new visualization techniques will be described: (1) A spatial texture based visualization approach for multi-dimensional attributes and time-series data; (2) A spiral theme plot technique for visualizing time-variant patient data.

Posters
Paper Nr: 6
Title:

ShaderBase: A Processing Tool for Shaders in Computational Arts and Design

Authors:

Andrés Felipe Gomez, Jean Pierre Charalambos and Andrés Colubri

Abstract: We introduce a new software tool called ShaderBase that facilitates using, sharing, and curating GLSL shaders in computational design, interactive arts, and data visualization. This tool is part of the Processing programming environment, an open-source project widely used for teaching and production in the context of media arts and design. Shaders are a crucial component in the development of large-scale data visualizations, interactive installations, real-time rendering tools, videogames, virtual reality applications, etc. However, their use requires advanced shader programming skills, and the creation of new shader-based effects demands a deep understanding of the graphics pipeline in modern Graphics Processing Units (GPUs). ShaderBase uniquely addresses these issues by allowing Processing users to easily upload and share shaders via an underlying Git repository. ShaderBase operates in close integration with Processing’s interface, so that users can incorporate shaders into their programs with minimal effort. Furthermore, the shaders indexed in ShaderBase take advantage of Processing’s drawing API, and incentives the use of shaders among artists and designers who might not be able to do so otherwise

Paper Nr: 12
Title:

The Challenges of Designing Metro Maps

Authors:

Michael Burch, Robin Woods, Rudolf Netzel and Daniel Weiskopf

Abstract: Metro maps can be regarded as a particular version of information visualization. The goal is to produce readable and effective map designs. In this paper, we combine the expertise of design experts and visualization researchers to achieve this goal. The aesthetic design of the maps should play a major role as the intention of the designer is to make them attractive for the human viewer in order to use the designs in a way that is the most efficient. The designs should invoke accurate actions by the user—in the case of a metro map, the user would be making journeys. We provide two views on metro map designs: one from a designer point of view and one from a visualization expert point of view. The focus of this work is to find a combination of both worlds from which the designer as well as the visualizer can benefit. To reach this goal we first describe the designer’s work when designing metro maps, then we take a look at how a visualizer measures performance from an end user perspective by tracking people’s eyes when working with the formerly designed maps while answering a route finding task.

Paper Nr: 31
Title:

Iso-edges for the Geovisualization of Consumptions

Authors:

Catarina Maçãs, Pedro Cruz, Evgheni Polisciuc, Hugo Amaro and Penousal Machado

Abstract: Data Visualization is emerging as a tool to understand and explore data in various ways. It enables us to interpret, synthesise, and present complex and vast amounts of information. We use Data Visualization to represent the evolution of consumptions in 729 hypermarkets and supermarkets of the biggest Portuguese retail company, for a time span of two years. We aim to apply an Information Visualization technique in order to study how, through Data Visualization, we can represent, synthesize, and interpret consumptions’ data. The geospatial data enables us to represent the consumptions in the different municipal districts and to analyze how consumptions evolve over time. To present this data, we apply an isoline approach, introducing a new technique called iso-edges. We also implement an interface for the exploration and analysis of the data.

Area 3 - Spatial Data Visualization

Full Papers
Paper Nr: 21
Title:

Flattening of the Lung Surface with Temporal Consistency for the Follow-Up Assessment of Pleural Mesothelioma

Authors:

Peter Faltin, Thomas Kraus, Marcin Kopaczka and Dorit Merhof

Abstract: Malignant pleural mesothelioma is an aggressive tumor of the lung surrounding membrane. The standardized workflow for the assessment comprises an inspection of 3D CT images to detect pleural thickenings which act as indicators for this tumor. Up to now, the visualization of relevant information from the pleura has only been superficially addressed. Current approaches still utilize a slice-wise visualization which does not allow a global assessment of the lung surface. In this publication, we present an approach which enables a planar 2D visualization of the pleura by flattening its surface. A distortion free mapping to a planar representation is generally not possible. The present method determines a planar representation with low distortions directly from a voxel-based surface. For a meaningful follow-up assessment, the consistent representation of a lung from different points in time is highly important. Therefore, the main focus in this publication is to guarantee a consistent representation of the pleura from the same patient extracted from images taken at two different points in time. This temporal consistency is achieved by our newly proposed link of both surfaces during the flattening process. Additionally, a new initialization method which utilizes a flattened lung prototype speeds up the flattening process.

Short Papers
Paper Nr: 4
Title:

RSViewer: An Efficient Video Viewer for Racquet Sports Focusing on Rally Scenes

Authors:

Shunya Kawamura, Tsukasa Fukusato, Tatsunori Hirai and Shigeo Morishima

Abstract: This paper presents RSViewer, a video browsing system specialized for racquet sports, which reflects users’ interests. Methods to support users in browsing racquet sports matches by summarizing video composed of important rally shots have been discussed in a previous study. However, the method is not practical enough because the auditory events should be manually annotated in advance to detect such scenes. Therefore, we propose an automatic rally shot detection based on shot clustering method using white line detection. Our system calculates the importance of rally shots based on audio features. As the result, the summarized video can facilitate users find and review the information they need. The result of experiments shows that our method is effective in an aspect of efficient video browsing experience. Furthermore, we propose a high-speed playback method customized to racquet sports video and realize more efficient video browsing experience.