IVAPP 2018 Abstracts


Area 1 - Abstract Data Visualization

Full Papers
Paper Nr: 7
Title:

TagPies: Comparative Visualization of Textual Data

Authors:

Stefan Jänicke, Judith Blumenstein, Michaela Rücker, Dirk Zeckzer and Gerik Scheuermann

Abstract: A TagPie is a novel tag cloud layout that arranges the tags belonging to multiple data categories in a pie chart manner. Motivated from research in classical philology, TagPies were designed to support the comparative analysis of classical terminology. In this scenario, the data categories represent the co-occurrences of different searched keywords, so that the comparison of the contexts in which these keywords were used becomes possible using TagPies. This paper illustrates the iterative development of TagPies, which aid as a distant reading view on a text corpus for humanities scholars. We outline various steps of our collaborative digital humanities project, and we emphasize the utility of the proposed design by outlining various usage scenarios representing current research questions in classical philology.

Paper Nr: 8
Title:

Exploring Flow Metrics in Dense Geographical Networks

Authors:

Valentino Di Donato, Maurizio Patrignani and Claudio Squarcella

Abstract: We present FLOWMATRIX, a system for the interactive exploration of time-labeled multivariate flows between pairs of geographic locations. FLOWMATRIX offers a coordinated visualization based on the interplay between a geographic map and a matrix that allow to discover trends tied to specific locations while offering an overview of metrics of the flows between all pairs of locations. The input data is clustered following a geographic hierarchy and the user can navigate between different levels of detail. The design of our system privileges the execution of simple tasks like assessing the volume and features of the flows between pairs of locations, enumerating destinations with poor performance, and sorting flow streams based on their volume.

Paper Nr: 18
Title:

A Visual Analytics Framework for Exploring Uncertainties in Reservoir Models

Authors:

Zahra Sahaf, Hamidreza Hamdi, Roberta Cabral Ramos Mota, Mario Costa Sousa and Frank Maurer

Abstract: Geological uncertainty is an essential element that affects the prediction of hydrocarbon production. The standard approach to address the geological uncertainty is to generate a large number of random 3D geological models and then perform flow simulations for each of them. Such a brute-force approach is not efficient as the flow simulations are computationally costly and as a result, domain experts cannot afford running a large number of simulations. Therefore, it is critically important to be able to address the uncertainty using a few geological models, which can reasonably represent the overall uncertainty of the ensemble. Our goal is to design and develop a visual analytics framework to filter the geological models and to only select models that can potentially cover the uncertain space. This framework is based on the mutual information for the calculation of the distance between the models and clustering for the grouping of similar models. Interactive visualization tasks have also been designed to make the whole process more understandable. Finally, we evaluated our results by comparing with the existent brute force approach.

Paper Nr: 24
Title:

Designing a Classification for User-authored Annotations in Data Visualization

Authors:

Pierre Vanhulst, Florian Évéquoz, Raphaël Tuor and Denis Lalanne

Abstract: This article introduces a classification system for user-authored annotations in the domain of data visualization. The classification system was created with a bottom-up approach, starting from actual user-authored annotations. To devise relevant dimensions for this classification, we designed a data analysis web platform displaying four visualizations of a common dataset. Using this tool, 16 analysts recorded over 300 annotations that were used to design a classification system. That classification system was then iteratively evaluated and refined until a high inter-coder agreement was found. Use cases for such a classification includes assessing the expressiveness of visualizations on a common ground, based on the types of annotations that are produced with each visualization.

Paper Nr: 26
Title:

PreechVis: Visual Profiling using Multiple-word Combinations

Authors:

Seongmin Mun, Gyeongcheol Choi, Guillaume Desagulier and Kyungwon Lee

Abstract: Words in the corpus include features and information, and the visualizing of such words can improve the user’s understanding of them. Words in text corpus may be consist of one-word or they may be a combination of words that together, constitute a word. The latter is referred to as a multiword expression. And if we analyze both single word and multiword with visualization, we can get more accurate results and more information than we analyze only single word from corpus. An interactive visualization can be useful for analyzing multiword expressions, because the following features are of interest to linguistics scholars: (1) Showing the combinatory POS pattern of a hierarchical form, (2) exploring results according to the POS pattern, and (3) searching the source corpus for the analysis-result verification. Therefore, we propose PreechVis, an interactive-visualization tool that includes all of the requisite functions for an analysis for which multiple words (http://202.30.24.167:3010/PreechVisMWE) are utilized. For the present study, we used a total of 957 speeches of 43 U.S. Presidents from George Washington to Barack Obama as the corpus data. PreechVis is divided into two views. In the first view, the system consists of a combination of Sunburst and RadVis. Through the circular Sunburst, we present the POS and its combination patterns for each gram. In RadVis, the Presidents were positioned according to their frequency value. In addition, when the President was selected, the frequency value was displayed on Sunburst to improve the user’s understanding. In the second view, the user can simultaneously confirm and verify the details of the result using the Wordcloud. The two different views are synchronized with each other and are changed by the selected grams, issues, and Presidents. In the experiments and case studies on the U.S.-President speech data, we verified the effectiveness and usability of PreechVis.

Paper Nr: 31
Title:

A New Approach to GraphMaps, a System Browsing Large Graphs as Interactive Maps

Authors:

Debajyoti Mondal and Lev Nachmanson

Abstract: A GraphMaps is a system that visualizes a graph using zoom levels, which is similar to a geographic map visualization. GraphMaps reveals the structural properties of the graph and enables users to explore the graph in a natural way by using the standard zoom and pan operations. The available implementation of GraphMaps faces many challenges such as the number of zoom levels may be large, nodes may be unevenly distributed to different levels, shared edges may create ambiguity due to the selection of multiple nodes. In this paper, we develop an algorithmic framework to construct GraphMaps from any given mesh (generated from a 2D point set), and for any given number of zoom levels. We demonstrate our approach introducing competition mesh, which is simple to construct, has a low dilation and high angular resolution. We present an algorithm for assigning nodes to zoom levels that minimizes the change in the number of nodes on visible on the screen while the user zooms in and out between the levels. We think that keeping this change small facilitates smooth browsing of the graph. We also propose new node selection techniques to cope with some of the challenges of the GraphMaps approach.

Paper Nr: 39
Title:

An Evolutionary Algorithm for an Optimization Model of Edge Bundling

Authors:

Joelma Ferreira, Hugo Nascimento and Les Foulds

Abstract: This paper presents two edge bundling optimization problems that address minimizing the total number of bundles, in conjunction with other aspects, as the main goal. A novel evolutionary edge bundling algorithm for these problems is described. The algorithm was successfully tested by solving two related problems applied to real-world instances in reasonable computational time. The development and analysis of optimization models have received little attention in the area of edge bundling. However, the reported experimental results demonstrate the effectiveness and the applicability of the proposed evolutionary algorithm to help resolve edge bundling problems formally defined as optimization models.

Paper Nr: 48
Title:

Orthogonal Compaction using Additional Bends

Authors:

Michael Jünger, Petra Mutzel and Christiane Spisla

Abstract: Compacting orthogonal drawings is a challenging task. Usually algorithms try to compute drawings with small area or total edge length while preserving the underlying orthogonal shape. We suggest a moderate relaxation of the orthogonal compaction problem, namely the one-dimensional monotone flexible edge compaction problem with fixed vertex star geometry. We further show that this problem can be solved in polynomial time using a network flow model. An experimental evaluation shows that by allowing additional bends we were able to reduce the total edge length and the drawing area.

Short Papers
Paper Nr: 4
Title:

DoSVis: Document Stance Visualization

Authors:

Kostiantyn Kucher, Carita Paradis and Andreas Kerren

Abstract: Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer’s attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature.

Paper Nr: 12
Title:

Visualizing Text Data in Space and Time to Augment a Political News Broadcast on a Second Screen

Authors:

Christina Niederer, Wolfgang Aigner, Kerstin Blumenstein, Štefan Emrich and Markus Wagner

Abstract: While second screen scenarios - that is, simultaneously using a phone, tablet or laptop while watching TV or a recorded broadcast - are finding their ways into the homes of millions of people, our understanding of how to properly design them is still very limited. We envision this design space and investigate how interactive data visualization can be leveraged in a second screen context. In this paper, we present the design process of a tablet application visualizing content from the stenographic minutes of the Austrian National Council.

Paper Nr: 16
Title:

Storytelling and Visualization: A Survey

Authors:

Chao Tong, Richard Roberts, Robert S. Laramee, Kodzo Wegba, Aidong Lu, Yun Wang, Huamin Qu, Qiong Luo and XiaoJuan Ma

Abstract: Throughout history, storytelling has been an effective way of conveying information and knowledge. In the field of visualization, storytelling is rapidly gaining momentum and evolving cutting-edge techniques that enhance understanding. Many communities have commented on the importance of storytelling in data visualization. Storytellers tend to be integrating complex visualizations into their narratives in growing numbers. In this paper, we present a survey of storytelling literature in visualization and present an overview of the common and important elements in storytelling visualization. We also describe the challenges in this field as well as a novel classification of the literature on storytelling in visualization. Our classification scheme highlights the open and unsolved problems in this field as well as the more mature storytelling sub-fields. The benefits offer a concise overview and a starting point into this rapidly evolving research trend and provide a deeper understanding of this topic.

Paper Nr: 17
Title:

Data Aggregation and Distance Encoding for Interactive Large Multidimensional Data Visualization

Authors:

Desislava Decheva and Lars Linsen

Abstract: Visualization of unlabeled multidimensional data is commonly performed using projections to a 2D visual space, which supports an investigative interactive analysis. However, static views obtained by a projection method like Principal Component Analysis (PCA) may not capture well all data features. Moreover. in case of large data with many samples, the scatterplots suffer from overplotting, which hinders analysis purposes. Clustering tools allow for aggregation of data to meaningful structures. Clustering methods like K-means, however, also suffer from drawbacks. We present a novel approach to visually encode aggregated data in projected views and to interactively explore the data. We make use of the benefits of PCA and K-means clustering, but overcome their main drawbacks. The sensitivity of K-means to outlier points is ameliorated, while the sensitivity of PCA to axis scaling is converted into a powerful flexibility, allowing the user to change observation perspective by rescaling the original axes. Analysis of both clusters and outliers is facilitated. Properties of clusters are visually encoded in aggregated form using color and size or examined in detail via local scatterplots or local circular parallel coordinate plots. The granularity of the data aggregation process can be adjusted interactively. A star coordinate interaction widget allows for modifying the projection matrix. To convey how much the projection maintains neighborhoods, we use a distance encoding. We evaluate our tool using synthetic and real-world data sets and perform a user study to evaluate its effectiveness.

Paper Nr: 25
Title:

Visual Analysis and Exploration of Entity Relations in Document Collections

Authors:

Markus John, Florian Heimerl, Ba-Anh Vu and Thomas Ertl

Abstract: Interactive text visualization can help users explore and gain insights into complex and often large document sets. One popular visualization strategy to represent such collections is to depict each document as a glyph in 2D space. These spaces have proven effective, especially when combined with interactive exploration methods. However, current exploratory approaches are largely limited to single areas of a 2D spatialization, lacking support for important comparative exploration and analysis tasks. In this paper, we extend a flexible focus+context exploration technique to tackle this challenge. In particular, based on practical tasks from the digital humanities, we focus on exploring and investigating relationships between entities in large document collections. Our approach uses natural language processing to extract characters and places, including information about their relationships. We then use linked views to facilitate visual analysis of extracted information artifacts. Based on two usage scenarios, we demonstrate successful applications of the approach and discuss its benefits and limitations.

Paper Nr: 30
Title:

EvoCells - A Treemap Layout Algorithm for Evolving Tree Data

Authors:

Willy Scheibel, Christopher Weyand and Jürgen Döllner

Abstract: We propose the rectangular treemap layout algorithm EvoCells that maps changes in tree-structured data onto an initial treemap layout. Changes in topology and node weights are mapped to insertion, removal, growth, and shrinkage of the layout rectangles. Thereby, rectangles displace their neighbors and stretche their enclosing rectangles with a run-time complexity of O (n log n). An evaluation using layout stability metrics on the open source ElasticSearch software system suggests EvoCells as a valid alternative for stable treemap layouting.

Paper Nr: 40
Title:

Area Preserving Dynamic Geospatial Visualization on Physical Globe

Authors:

Shima Dadkhahfard, Katayoon Etemad, John Brosz and Faramarz Samavati

Abstract: We present a methodology for creating dynamic visualization of geospatial data on physical globe. To achieve this goal, we use a piecewise curved-display and multi-projector setup. The curved-display is a physical representation of the globe and provides closer approximation of the Earth and reduce distortions. In our method, we use a Discrete Grid Global System (DGGS) for discretizing the Earth to hierarchical cells in different resolutions. This DGGS employs an area preserving projection for on the fly integration of geospatial datasets. There is a one-to-one correspondence between pieces of our curved-display and DGGS cells in a specific resolution. We use 3D printing technology for fabricating of each piece of the display. For controlling the projection, we developed software that takes data from DGGS, warp it and then feeds it to the projectors. The fabrication of the cells and the generation of projection feed follow the same structure of DGGS. We demonstrate the flexibility of our construction with several example setups and apply them to visualize multiple datasets, including time-varying geospatial data.

Paper Nr: 43
Title:

Performance Visualization for TAU Instrumented Scientific Workflows

Authors:

Cong Xie, Wei Xu, Sungsoo Ha, Kevin Huck, Sameer Shende, Hubertus Van Dam, Kerstin Kleese Van Dam and Klaus Mueller

Abstract: In exascale scientific computing, it is essential to efficiently monitor, evaluate and improve performance. Visualization and especially visual analytics are useful and inevitable techniques in the exascale computing era to enable such a human-centered experience. In this ongoing work, we present a visual analytics framework for performance evaluation of scientific workflows. Ultimately, we aim to solve two current challenges: the capability to deal with workflows, and the scalability toward exascale scenario. On the way to achieve these goals, in this work, we first incorporate TAU (Tuning and Analysis Utilities) instrumentation tool and improve it to accommodate workflow measurements. Then we establish a web-based visualization framework, whose back end handles data storage, query and aggregation, while front end presents the visualization and takes user interaction. In order to support the scalability, a few level-of-detail mechanisms are developed. Finally, a chemistry workflow use case is adopted to verify our methods.

Posters
Paper Nr: 1
Title:

To Paint in Tongues - Interactive, Artistic and Mobile Information Visualization for Social Media Texts - Creativity Enhancement by Painting with Tweets on a Smart Tablet

Authors:

Robin Horst and Elisabeth Franziska Stein

Abstract: A vast amount of thousands of Twitter messages are produced per second. As not only researchers and data professionals are interested in utilizing this data, other people could make use of specific insights. Without the skill to conduct queries with expert systems, tweets must tediously be read entirely in the traditional way. The creativity gets constrained and neglected in this tiring and cognitive demanding process. However these tweets could be a great source for conducting investigations as for example in sociocultural creative research, as writing for lyrics, scripts or even books. Writers could benefit from this huge amount of free accessible information about public opinions on recent topics. In this paper, we introduce a mobile visualization tool and its underlying visualization concept: Paint in Tongues. It can be used in different ways to visualize text-based social media content. Moreover it enables users that are unexperienced at information visualization to easily interact with the data and utilize it. Techniques that even enhance creativity, as doodling and combining different media, are utilized in an interactive visualization process to augment the data analysis for creative and visual oriented people.

Paper Nr: 10
Title:

Optical Graph Edge Recognition

Authors:

Rudolfs Opmanis

Abstract: Optical graph recognition is a process that from an input raster image extracts a graph topology. Graph recognition is interesting for not only because it allows reusing information from other diagrams, but also it is a tool that can measure the readability of a graph diagram visualisation or help with a testing of automatic graph visualisation engines. In this paper, we propose an optical graph edge recognition algorithm that can recognise edges with arbitrary edge routing style, handle drawings with many edge crossings and process edges that are rendered as polylines using a solid or dashed stroke. To evaluate the proposed algorithm we have developed comprehensive test suite with 2400 graphs of various sizes, edge densities, edge routing styles and edge rendering strokes.

Paper Nr: 35
Title:

Design Study for Creating Pathfinder: A Visualization Tool for Generating Software Test Plans using Model based Testing

Authors:

Kuruvilla Lukose, Shivam Agarwal, Vidyashankar Nagesha Rao and Jaya Sreevalsan-Nair

Abstract: Model Based Testing (MBT) is a popularly used software testing technique in the software industry. However, there still exists a gap between the awareness of benefits of MBT and its adoption in the industry, specifically in the Computer Aided Design (CAD) or Computer Aided Engineering (CAE) domains. This can be predominantly attributed to the learning curve of using many of the existing MBT tools. To address this gap in the CAD/CAE industry, we propose Pathfinder - an MBT tool, with a Graphical User Interface (GUI), for guiding a software tester in generating test plans for a system-under-test (SUT). The goal of using Pathfinder is for obtaining consistency and reproducibility in the generated test plans across a team of software testers. Our tool introduces a novel representation of the SUT as a High-level Model (HLM), and the use of graph visualization for test plan generation from the HLM. We have designed the GUI to be intuitive for the tester to generate test plans and select relevant tests, which precedes the test execution done outside of our tool. Here, we discuss the design decisions we adopted towards creating Pathfinder, and demonstrates its usage with two case studies.

Paper Nr: 36
Title:

Layered Graph Force-driven Vertex Positioning

Authors:

Radek Mařík

Abstract: We propose a new method of node positioning for huge layered graphs specified by layers and fixed ordering of nodes within layers. We assume that the assignments of nodes to the layers and the order of nodes within the layers are provided by other suitable methods capable of processing multitree like networks. The node positioning method is based on the force-driven approach with barrier-like repulsive forces that avoids the quadratic complexity of traditional methods. We demonstrate achievements on several datasets containing up to millions of people or species. The proposed layout method of layered graphs that are close to acyclic multitrees creates aesthetically acceptable layouts in linear time.

Paper Nr: 42
Title:

Quantitative Evaluation of Multi-Type Edge Bundling - Example for Japan Airmap

Authors:

Ryosuke Saga

Abstract: This paper describes an evaluation of multi-type edge bundling methods showing for different types of edges. Edge bundling methods such as force-directed edge bundling (FDEB) method have gained attention as one of graph drawing methods that reduce visual clutter. Also, a multi-type edge bundling methods have been proposed for multi-type graph that has an attached attribute to each edge. These methods are used for several cases and evaluated qualitatively. However, there is no cases to evaluate them quantitatively. This paper proposes one of the multi-type edge bundling methods extended from FDEB and visualizes the airline route map in Japan. After that, this paper evaluates them to know the features of each bundling method by using the three measures: mean edge length difference, mean occupation area, and edge density distribution.

Paper Nr: 45
Title:

Mirroring Sankey Diagrams for Visual Comparison Tasks

Authors:

Zana Vosough, Dietrich Kammer, Mandy Keck and Rainer Groh

Abstract: Complex data sets require suitable information visualizations. With the rapidly increasing amount and complexity of data, the need for suitable interaction techniques to perform various data analyzing tasks is also growing. Flow diagrams are a powerful tool to understand the structure in hierarchical data sets. In many application scenarios, there is a need to quickly understand all facets in the data and compare different versions to make executive decisions. In order to illustrate our concepts, we selected Product Lifecycle Costing as application domain in which comparison tasks play an important role. On the one hand, an effective comparison of different versions needs to be visually presented to the user. On the other hand, different dimensions of the components need to be considered. We propose a mirroring method with the appropriate interaction techniques based on Sankey diagrams that address both issues.

Paper Nr: 46
Title:

Symmetric Generative Methods and tSNE: A Short Survey

Authors:

Rodolphe Priam

Abstract: In data visualization, a family of methods is dedicated to the symmetric numerical matrices which contain the distances or similarities between high-dimensional data vectors. The method t-Distributed Stochastic Neighbor Embedding and its variants lead to competitive nonlinear embeddings which are able to reveal the natural classes. For comparisons, it is surveyed the recent probabilistic and model-based alternative methods from the literature (LargeVis, Glove, Latent Space Position Model, probabilistic Correspondence Analysis, Stochastic Block Model) for nonlinear embedding via low dimensional positions.

Area 2 - General Data Visualization

Full Papers
Paper Nr: 14
Title:

MultiVisA: Visual Analysis of Multi-run Physical Simulation Data using Interactive Aggregated Plots

Authors:

Alexey Fofonov and Lars Linsen

Abstract: Physical simulations aim at modeling and computing spatio-temporal phenomena. As the simulations depend on initial conditions and/or parameter settings whose impact is to be investigated, a larger number of simulation runs is commonly executed. Analyzing all facets of such multi-run multi-field spatio-temporal simulation data poses a challenge for visualization. It requires the design of different visual encodings that aggregate information in multiple ways and at multiple abstraction levels. MultiVisA is a tool for the interactive visual analysis of multi-run data from physical simulations based on a number of aggregated plots and coordinated interactions. A histogram-based plot allows for the investigation of the distribution of function values within all simulation runs. A density-based time-series plot allows for the detection of temporal patterns and outliers within the ensemble of multiple runs for single and multiple fields. A similarity-based plot allows for the comparison of multiple or individual runs and their behavior over time. Coordinated views allow for linking the plots to spatial visualizations in physical space. We apply MultiVisA to physical simulations from the field of climate research and astrophysics. We document the analysis process, demonstrate its effectiveness, and provide evaluations involving domain experts.

Paper Nr: 33
Title:

TabularVis – a Circos-inspired interactive web client based tool for improving the clarity of tabular data visualization

Authors:

György Papp and Roland Kunkli

Abstract: Table visualization is one of the earliest problems in the field of data visualization, and there are many applications which provide different solutions to this task. One of the most popular ones is Circos, a well-known genome visualization software package based on the so-called circular layout technique. In this work, we present an interactive web-based visualization tool inspired by Circos' table viewer web application, in which we provide new extensions and techniques beyond its existing main ideas, for improving the clarity of the generated visualization. One of them is making the links easier to follow by giving an automatic solution to reduce the number of intersections between the links. We also present different tools which could be particularly useful in such situations, in which the table's data induce extreme scatter, i.e., the difference between the data is significantly large or small. Our proposed visualization accepts tables with non-negative numbers, and the amount of efficiently displayable data depends on the number of zeros in the table. In the paper, besides describing our contributions in detail, we also compare the outputs of our method and Circos table viewer to confirm the legitimacy of our application and the implemented techniques it contains.

Short Papers
Paper Nr: 13
Title:

Data Visualization Support for Complex Logistics Operations and Cyber-Physical Systems

Authors:

Didem Gürdür, Klaus Raizer and Jad El-Khoury

Abstract: Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeholders, and different data visualizations to support the stakeholders in order to understand interactions between entities easier and faster. Three different levels were identified—supply chain, automated warehouse, and intelligent agent—to define the complex logistics operations. For each level, important stakeholders and performance indicators were determined. A case study was designed and described to exemplify the role of cyber-physical systems in complex logistics operations. Moreover, different data visualizations were developed as part of a dashboard to illustrate key performance indicators of different levels for the purpose of supporting stakeholders. This exploratory study concludes by identifying important data necessity for each performance indicator, suggesting ways to collect these data, and exemplifying how data visualization approach can be used through a dashboard design.

Paper Nr: 44
Title:

Digital Visual Exploration Library

Authors:

Nicholas Tan Jerome and Andreas Kopmann

Abstract: With the advancement of instrument precision, research facilities are generating data at an unprecedented rate. These experimental results are stored in a digital library platform which the contents are later accessible from within the facility or the public. However, the sheer volume of collected data is overwhelming the capacity of researchers and impedes the process of browsing for the desired data. In this paper, we present a concept of Digital Visual Exploration Library (DVEL) based on the confluence of two major research domains—digital library and visualisation—that enables efficient browsing of the growing data within a digital library. We complement the current state-of-the-art textual metadata description by integrating visual exploration to address big complex data, i.e., data of large size, multimodal data and multivariate data. We describe our concept based on use cases from three unique domains: climate research with Doppler wind lidar, X-ray-imaging for entomology research, and medical imaging with ultrasound computer tomography.

Posters
Paper Nr: 9
Title:

Bifocal Parallel Coordinates Plot for Multivariate Data Visualization

Authors:

Gurminder Kaur and Bijaya B. Karki

Abstract: Visualization of multivariate data using parallel coordinates plot (PCP) becomes overwhelming as the number of dimensions/variables increases beyond one dozen or so. Here we propose bifocal parallel coordinates plot (BPCP) based on the focus + context approach. BPCP splits vertically the overall rendering into the focus and context regions whose sizes can be adjusted to optimize the use of the available space. The focus area maps a few selected dimensions of interest, referred to as priority axes, at sufficiently wide spacing. The remaining dimensions are represented in the context area in a compact way so as to retain useful information and provide the data continuity. The focus display can be further enhanced with various options, such as axes overlays, scatterplot, and nested juxtaposed PCPs. In order to accommodate an arbitrarily large number of dimensions, the context display supports multi-level stacked view, each PCP level mapping a subset of the context axes. With flexible interactivity, BPCP can manage the priority axes and data rendering with respect to the corresponding dimensions to support exploratory visualization while providing useful context on the same visualization display.

Paper Nr: 27
Title:

Parallel Bubbles - Evaluation of Three Techniques for Representing Mixed Categorical and Continuous Data in Parallel Coordinates

Authors:

Raphaël Tuor, Florian Evéquoz and Denis Lalanne

Abstract: Parallel Coordinates are a widely used visualization method for multivariate data analysis tasks. In this paper we discuss the techniques that aim to enhance the representation of categorical data in Parallel Coordinates. We propose Parallel Bubbles, a method that improves the graphical perception of categorical dimensions in Parallel Coordinates by adding a visual encoding of frequency. Our main contribution consists in a user study that compares the performance of three variants of Parallel Coordinates, with similarity and frequency tasks. We base our design choices on the literature review, and on the research guidelines provided by Johansson et al (2016). Parallel Bubbles are a good trade-off between Parallel Coordinates and Parallel Sets in terms of performance for both types of tasks. Adding a visual encoding of frequency leads to a significant difference in performance for a frequency-based task consisting in assessing the most represented category. This study is the first of a series that will aim at testing the three visualization methods in tasks centered on the continuous axis, and where we assume that the performance of Parallel Sets will be worse.

Paper Nr: 28
Title:

Annotations as a Support for Knowledge Generation - Supporting Visual Analytics in the Field of Ophthalmology

Authors:

Christoph Schmidt, Paul Rosenthal and Heidrun Schumann

Abstract: While visual analytics (VA) supports the appraisal of large data amounts, annotations support the amendment of additional information to the VA system. Despite the fact that annotations have occasionally been used to facilitate the analysis, a thorough investigation of annotations themselves is challenging. Although they can represent a suitable way to transfer additional information into the visualization system, there is the need to characterize annotations in order to assure an appropriate use. With our paper we provide a characteristic for annotations, revealing and depicting key issues for the use of annotations. By supplementary fitting our characteristic into the knowledge generation model from Sacha et al. (2014), we provide a systematic view on annotations. We show the general applicability of our characteristic of annotations with a visual analytics approach on medical data in the field of ophthalmology.

Paper Nr: 41
Title:

A Tale of Two Visions - Exploring the Dichotomy of Interest between Academia and Industry in Visualisation

Authors:

Richard Roberts, Robert Laramee, Paul Brookes, Gary A. Smith, Tony D'Cruze and Matt J. Roach

Abstract: The pairing of a commercial organisation with an academic institution is a typical example of a symbiotic relationship. Commercial organisations dedicate money, time, and often data into a university project with the ultimate goal of a financial return on their prudent investments. Academic institutions welcome these relationships as it supports their research in a field where obtaining funding is extremely competitive. Specifically in the field of visualisation, the culture, visions, and goals of both academia and industry differ in unique ways. In this position paper we explore the dichotomy of interests between the two groups, based on first hand experience and interviews, deriving recommendations for any organisation considering entering into a working relationship with either party.

Area 3 - Spatial Data Visualization

Full Papers
Paper Nr: 3
Title:

SmoothIsoPoints: Making PDE-based Surface Extraction from Point-based Volume Data Fast

Authors:

Paul Rosenthal, Vladimir Molchanov and Lars Linsen

Abstract: PDE-based methods like level-set methods are a valuable and well-established approach in visualization to extract surfaces from volume data. We propose a novel method for the efficient computation of a signed-distance function to a surface in point-cloud representation and embed this method into a framework for PDE-based surface extraction from point-based volume data. This enables us to develop a fast level-set approach for extracting smooth isosurfaces from data with highly varying point density. The level-set method operates just locally in a narrow band around the zero-level set. It relies on the explicit representation of the zero-level set and the fast generation of a signed-distance function to it. A level-set step is executed in the narrow band utilizing the properties and derivatives of the signed-distance function. The zero-level set is extracted after each level-set step using direct isosurface extraction from point-based volume data. In contrast to existing methods for unstructured data which operate on implicit representations, our approach can use any starting surface for the level-set approach. Since for most applications a rough estimate of the desired surface can be obtained quickly, the overall level-set process can be shortened significantly. Additionally, we avoid the computational overhead and numerical difficulties of PDE-based reinitialization. Still, our approach achieves equivalent quality, flexibility, and robustness as existing methods for point-based volume data.

Paper Nr: 5
Title:

Overcoming the Curse of Dimensionality When Clustering Multivariate Volume Data

Authors:

Vladimir Molchanov and Lars Linsen

Abstract: Visual analytics of multidimensional data suffer from the curse of dimensionality, i.e., that even large numbers of data points will be scattered in a high-dimensional space. The curse of dimensionality prohibits the proper use of clustering algorithms in the high-dimensional space. Projecting the space before clustering imposes a loss of information and possible mixing of separated clusters. We present an approach where we overcome the curse of dimensionality for a particular type of multidimensional data, namely for attribute spaces of multivariate volume data. For multivariate volume data, it is possible to interpolate between the data points in the high-dimensional attribute space based on their spatial relationship in the volumetric domain (or physical space). We apply this idea to a histogram-based clustering algorithm. We create a uniform partition of the attribute space in multidimensional bins and compute a histogram indicating the number of data samples belonging to each bin. Only non-empty bins are stored for efficiency. Without interpolation, the analysis is highly sensitive to the cell sizes yielding inaccurate clustering for improper choices: Large cells result in no cluster separation, while clusters fall apart for small cells. Using tri-linear interpolation in physical space, we can refine the data by generating additional samples. The refinement scheme can adapt to the data point distribution in attribute space and the histogram’s bin size. As a consequence, we can generate a density computation, where clusters stay connected even when using very small cell sizes. We exploit this result to create a robust hierarchical cluster tree. It can be visually explored using coordinated views to physical space visualizations and to parallel coordinates plots. We apply our technique to several datasets and compare the results against results without interpolation.

Short Papers
Paper Nr: 20
Title:

Visual GISwaps - An Interactive Visualization Framework for Geospatial Decision Making

Authors:

Goran Milutinovic and Stefan Seipel

Abstract: Different visualization techniques are frequently used in geospatial information systems (GIS) to support geospatial decision making. However, visualization in GIS context is usually limited to the initial phase of the decision-making process, i.e. situation analysis and problem recognition. This is partly due to the choice of methods used in GIS multi-criteria decision-making (GIS-MCDM) that usually deploy some non-interactive approach, leaving the decision maker little or no control over the calculation of overall values for the considered alternatives; the role of visualization is thus reduced to presenting the final results of the computations. The contributions of this paper are twofold. First, we introduce GISwaps, a novel, intuitive interactive method for decision making in geospatial context. The second and main contribution is an interactive visualization of the choice phase of the decision making process. The visualization allows the decision maker to explore the consequences of trade-offs and costs accepted during the iterative decision process, both in terms of the abstract relation between different decision variables and in spatial context.

Posters
Paper Nr: 32
Title:

Slice-based Visualization of Brain Fiber Bundles - A LIC-based Approach

Authors:

Stefan Philips, Mario Hlawitschka and Gerik Scheuermann

Abstract: The reconstruction of brain fibers from diffusion MRI data is a widely studied field. There is a great variety of algorithms to generate fiber tracts. Despite the many possibilities to create fiber tractograms, it is not very common within the medical community to make use of them. We think there are two reasons why the acceptance of this technique is so low. The first reason is that most time the degree of detail provided by singular fibers is neither justified nor needed. Second, within the medical domain tractography visualization is still uncommon. To solve the first problem it is common to apply clustering algorithms which aggregate the single fibers to fiber bundles. In this paper, we display the fiber bundles within slices. The presentation within slices is common within the medical community and very intuitive to examine. Furthermore, our visualization allows the spatial assignment of fiber bundles to the brain structure provided as T1 images. Among many neuroscientists and physicians, T1 images are the main source for spatial orientation within the brain.