EuroVis15: Eurographics Conference on Visualization

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https://diglib7.eg.org/handle/10.2312/13890

Frontmatter: EuroVis 2015 Eurographics Conference on Visualization

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Carr, Hamish

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Ma, Kwan-Liu

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Santucci, Giuseppe

Biomedical Visualization

MoleCollar and Tunnel Heat Map Visualizations for Conveying Spatio-Temporo-Chemical Properties Across and Along Protein Voids

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Byska, Jan

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Jurcik, Adam

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Gröller, M. Eduard

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Viola, Ivan

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Kozlikova, Barbora

Biomedical Visualization

Visual Analytics for the Exploration of Tumor Tissue Characterization

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Raidou, Renata Georgia

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Heide, Uulke A. van der

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Dinh, Cuong Viet

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Ghobadi, Ghazaleh

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Kallehauge, Jesper Follsted

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Breeuwer, Marcel

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Vilanova, Anna

Biomedical Visualization

Cell Lineage Visualisation

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Pretorius, A. Johannes

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Khan, Imtiaz A.

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Errington, Rachel J.

Biomedical Visualization

Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks

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Bach, Benjamin

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Henry-Riche, Nathalie

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Dwyer, Tim

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Madhyastha, Tara

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Fekete, Jean-Daniel

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Grabowski, Thomas

Text & Humanities

Adaptive Recommendations for Enhanced Non-linear Exploration of Annotated 3D Objects

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Rodriguez, Marcos Balsa

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Agus, Marco

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Marton, Fabio

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Gobbetti, Enrico

Text & Humanities

Visual Analysis of Proximal Temporal Relationships of Social and Communicative Behaviors

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Han, Yi

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Rozga, Agata

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Dimitrova, Nevena

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Abowd, Gregory D.

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Stasko, John

Text & Humanities

Visual Assessment of Alleged Plagiarism Cases

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Riehmann, Patrick

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Potthast, Martin

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Stein, Benno

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Froehlich, Bernd

Text & Humanities

Perfopticon: Visual Query Analysis for Distributed Databases

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Moritz, Dominik

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Halperin, Daniel

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Howe, Bill

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Heer, Jeffrey

Volume Analysis and Classification

Efficient Local Histogram Searching via Bitmap Indexing

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Wei, Tzu-Hsuan

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Chen, Chun-Ming

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Biswas, Ayan

Volume Analysis and Classification

Guided Volume Editing based on Histogram Dissimilarity

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Karimov, Alexey

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Mistelbauer, Gabriel

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Auzinger, Thomas

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Bruckner, Stefan

Volume Analysis and Classification

Compressive Volume Rendering

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Liu, Xiaoyang

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Alim, Usman R.

Volume Analysis and Classification

Learning Probabilistic Transfer Functions: A Comparative Study of Classifiers

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Soundararajan, Krishna Prasad

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Schultz, Thomas

Volume Rendering

Rule-Enhanced Transfer Function Generation for Medical Volume Visualization

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Cai, Li-Le

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Nguyen, Binh P.

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Chui, Chee-Kong

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Ong, Sim-Heng

Volume Rendering

Edge-Aware Volume Smoothing Using L0 Gradient Minimization

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Wang, Qichao

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Tao, Yubo

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Lin, Hai

Volume Rendering

Photoelasticity Raycasting

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Bußler, Michael

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Ertl, Thomas

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Sadlo, Filip

Volume Rendering

Visualization of Particle-based Data with Transparency and Ambient Occlusion

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Staib, Joachim

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Grottel, Sebastian

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Gumhold, Stefan

Traffic

Exploring Traffic Dynamics in Urban Environments Using Vector-Valued Functions

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Poco, Jorge

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Doraiswamy, Harish

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Vo, Huy. T.

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Comba, João L. D.

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Freire, Juliana

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Silva, Cláudio T.

Traffic

Interactive Visual Analysis for Vehicle Detector Data

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Chen, Yi-Cheng

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Wang, Yu-Shuen

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Lin, Wen-Chieh

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Huang, Wei-Xiang

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Lin, I-Chen

Traffic

Visual Analytics for Exploring Local Impact of Air Traffic

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Buchmüller, Juri

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Janetzko, Halldor

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Andrienko, Gennady

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Andrienko, Natalia

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Fuchs, Georg

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Keim, Daniel A.

Traffic

Rationale Visualization for Safety and Security

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Scheepens, Roeland

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Michels, Steffen

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Wetering, Huub van de

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Wijk, Jarke J. van

Evaluation and Design

Data-driven Evaluation of Visual Quality Measures

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Sedlmair, Michael

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Aupetit, Michael

Evaluation and Design

Efficient Contrast Effect Compensation with Personalized Perception Models

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Mittelstädt, Sebastian

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Keim, Daniel A.

Evaluation and Design

An Evaluation of the Impact of Visual Embellishments in Bar Charts

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Skau, Drew

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Harrison, Lane

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Kosara, Robert

Evaluation and Design

An Exploratory Study of Data Sketching for Visual Representation

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Walny, Jagoda

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Huron, Samuel

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Carpendale, Sheelagh

Multi-modal and Multi-field

Fiber Surfaces: Generalizing Isosurfaces to Bivariate Data

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Carr, Hamish

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Geng, Zhao

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Tierny, Julien

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Chattopadhyay, Amit

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Knoll, Aaron

Multi-modal and Multi-field

Interactive Fusion and Tracking For Multi-Modal Spatial Data Visualization

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Elshehaly, Mai

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Gracanin, Denis

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Gad, Mohamed

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Elmongui, Hicham G.

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Matkovic, Kresimir

High-dimensional Visualization

A Multi-task Comparative Study on Scatter Plots and Parallel Coordinates Plots

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Kanjanabose, Rassadarie

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Abdul-Rahman, Alfie

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Chen, Min

High-dimensional Visualization

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections

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Liu, Shusen

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Wang, Bei

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Thiagarajan, Jayaraman J.

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Bremer, Peer-Timo

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Pascucci, Valerio

High-dimensional Visualization

Uncovering Representative Groups in Multidimensional Projections

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Joia, Paulo

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Petronetto, Fabiano

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Nonato, Luis Gustavo

High-dimensional Visualization

Visualnostics: Visual Guidance Pictograms for Analyzing Projections of High-dimensional Data

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Lehmann, Dirk J.

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Kemmler, Fritz

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Zhyhalava, Tatsiana

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Kirschke, Marco

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Theisel, Holger

Graphs

Refinery: Visual Exploration of Large, Heterogeneous Networks through Associative Browsing

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Kairam, Sanjay

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Henry-Riche, Nathalie

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Drucker, Steven

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Fernandez, Roland

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Heer, Jeffrey

Graphs

Dual Adjacency Matrix: Exploring Link Groups in Dense Networks

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Dinkla, Kasper

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Henry-Riche, Nathalie

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Westenberg, Michel A.

Graphs

Detangler: Visual Analytics for Multiplex Networks

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Renoust, Benjamin

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Melancon, Guy

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Munzner, Tamara

Geospatial Visualization

Visualization of Object-Centered Vulnerability to Possible Flood Hazards

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Cornel, Daniel

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Konev, Artem

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Sadransky, Bernhard

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Horvath, Zsolt

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Gröller, Eduard

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Waser, Jürgen

Geospatial Visualization

VIMTEX: A Visualization Interface for Multivariate, Time-Varying, Geological Data Exploration

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Dasgupta, Aritra

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Kosara, Robert

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Gosink, Luke

Geospatial Visualization

Mosaic Drawings and Cartograms

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Cano, Rafael G.

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Buchin, Kevin

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Castermans, Thom

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Pieterse, Astrid

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Sonke, Willem

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Speckmann, Bettina

Engineering and Physical Sciences

Visualizing Time-Specific Hurricane Predictions, with Uncertainty, from Storm Path Ensembles

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Liu, Le

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Mirzargar, Mahsa

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Kirby, Robert M.

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Whitaker, Ross

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House, Donald H.

Geospatial Visualization

Quantitative Measures for Cartogram Generation Techniques

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Alam, Md. Jawaherul

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Kobourov, Stephen G.

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Veeramoni, Sankar

Engineering and Physical Sciences

Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting

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Diehl, Alexandra

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Pelorosso, Leandro

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Delrieux, Claudio

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Saulo, Celeste

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Ruiz, Juan

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Gröller, M. Eduard

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Bruckner, Stefan

Engineering and Physical Sciences

A Shot at Visual Vulnerability Analysis

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Kerzner, Ethan

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Butler, Lee A.

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Hansen, Charles

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Meyer, Miriah

Engineering and Physical Sciences

A Novel Framework for Visual Detection and Exploration of Performance Bottlenecks in Organic Photovoltaic Solar Cell Materials

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Aboulhassan, Amal

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Baum, Daniel

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Wodo, Olga

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Ganapathysubramanian, Baskar

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Amassian, Aram

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Hadwiger, Markus

Time-series and Topology

Visual Analytics for Correlation-Based Comparison of Time Series Ensembles

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Köthur, Patrick

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Witt, Carl

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Sips, Mike

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Marwan, Norbert

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Schinkel, Stefan

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Dransch, Doris

Evaluation of Graphs

Map-based Visualizations Increase Recall Accuracy of Data

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Saket, Bahador

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Scheidegger, Carlos

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Kobourov, Stephen G.

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Börner, Katy

Time-series and Topology

Persistent Homology for the Evaluation of Dimensionality Reduction Schemes

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Rieck, Bastian

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Leitte, Heike

Time-series and Topology

Feature-Driven Visual Analytics of Chaotic Parameter-Dependent Movement

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Luboschik, Martin

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Röhlig, Martin

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Bittig, Arne T.

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Andrienko, Natalia

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Schumann, Heidrun

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Tominski, Christian

Evaluation of Graphs

GraphUnit: Evaluating Interactive Graph Visualizations Using Crowdsourcing

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Okoe, Mershack

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Jianu, Radu

Evaluation of Graphs

Towards a Smooth Design Process for Static Communicative Node-link Diagrams

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Suslik Spritzer, Andre

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Boy, Jeremy

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Dragicevic, Pierre

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Fekete, Jean-Daniel

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Dal Sasso Freitas, Carla Maria

Flow Visualization

Finite-Time Mass Separation for Comparative Visualizations of Inertial Particles

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Günther, Tobias

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Theisel, Holger

Flow Visualization

Vector Field Visualization of Advective-Diffusive Flows

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Hochstetter, Hendrik

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Wurm, Maximilian

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Kolb, Andreas

Flow Visualization

Visualization of Coherent Structures of Light Transport

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Zirr, Tobias

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Ament, Marco

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Dachsbacher, Carsten

Flow Visualization

Evaluating 2D Flow Visualization Using Eye Tracking

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Ho, Hsin-Yang

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Yeh, I-Cheng

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Lai, Yu-Chi

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Lin, Wen-Chieh

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Cherng, Fu-Yin

Browse

Now showing 1 - 52 of 52

Frontmatter: EuroVis 2015 Eurographics Conference on Visualization
(Eurographics Association, 2015) Carr, Hamish; Ma, Kwan-Liu; Santucci, Giuseppe; -
MoleCollar and Tunnel Heat Map Visualizations for Conveying Spatio-Temporo-Chemical Properties Across and Along Protein Voids
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Byska, Jan; Jurcik, Adam; Gröller, M. Eduard; Viola, Ivan; Kozlikova, Barbora; H. Carr, K.-L. Ma, and G. Santucci
Studying the characteristics of proteins and their inner void space, including their geometry, physico-chemical properties and dynamics are instrumental for evaluating the reactivity of the protein with other small molecules. The analysis of long simulations of molecular dynamics produces a large number of voids which have to be further explored and evaluated. In this paper we propose three new methods: two of them convey important properties along the long axis of a selected void during molecular dynamics and one provides a comprehensive picture across the void. The first two proposed methods use a specific heat map to present two types of information: an overview of all detected tunnels in the dynamics and their bottleneck width and stability over time, and an overview of a specific tunnel in the dynamics showing the bottleneck position and changes of the tunnel length over time. These methods help to select a small subset of tunnels, which are explored individually and in detail. For this stage we propose the third method, which shows in one static image the temporal evolvement of the shape of the most critical tunnel part, i.e., its bottleneck. This view is enriched with abstract depictions of different physicochemical properties of the amino acids surrounding the bottleneck. The usefulness of our newly proposed methods is demonstrated on a case study and the feedback from the domain experts is included. The biochemists confirmed that our novel methods help to convey the information about the appearance and properties of tunnels in a very intuitive and comprehensible manner.
Visual Analytics for the Exploration of Tumor Tissue Characterization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Raidou, Renata Georgia; Heide, Uulke A. van der; Dinh, Cuong Viet; Ghobadi, Ghazaleh; Kallehauge, Jesper Follsted; Breeuwer, Marcel; Vilanova, Anna; H. Carr, K.-L. Ma, and G. Santucci
Tumors are heterogeneous tissues consisting of multiple regions with distinct characteristics. Characterization of these intra-tumor regions can improve patient diagnosis and enable a better targeted treatment. Ideally, tissue characterization could be performed non-invasively, using medical imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derived feature space is prohibiting for easy exploration and analysis - especially when clinical researchers require to associate observations from the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing them and mentally reconstructing their relationships. This is a time consuming and tedious process, from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visual analysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesis generation and confirmation, with respect to reference data used in clinical research. We employ, as central view, a 2D embedding of the imaging-derived features. Multiple linked interactive views provide functionality for the exploration and analysis of the local structure of the feature space, enabling linking to patient anatomy and clinical reference data. We performed an initial evaluation with ten clinical researchers. All participants agreed that, unlike current practice, the proposed visual tool enables them to identify, explore and analyze heterogeneous intra-tumor regions and particularly, to generate and confirm hypotheses, with respect to clinical reference data.
Cell Lineage Visualisation
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Pretorius, A. Johannes; Khan, Imtiaz A.; Errington, Rachel J.; H. Carr, K.-L. Ma, and G. Santucci
Cell lineages describe the developmental history of cell populations and are produced by combining time-lapse imaging and image processing. Biomedical researchers study cell lineages to understand fundamental processes such as cell differentiation and the pharmacodynamic action of anticancer agents. Yet, the interpretation of cell lineages is hindered by their complexity and insufficient capacity for visual analysis. We present a novel approach for interactive visualisation of cell lineages. Based on an understanding of cellular biology and live-cell imaging methodology, we identify three requirements: multimodality (cell lineages combine spatial, temporal, and other properties), symmetry (related to lineage branching structure), and synchrony (related to temporal alignment of cellular events). We address these by combining visual summaries of the spatiotemporal behaviour of an arbitrary number of lineages, including variation from average behaviour, with node-link representations that emphasise the presence or absence of symmetry and synchrony. We illustrate the merit of our approach by presenting a real-world case study where the cytotoxic action of the anticancer drug topotecan was determined.
Small MultiPiles: Piling Time to Explore Temporal Patterns in Dynamic Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Bach, Benjamin; Henry-Riche, Nathalie; Dwyer, Tim; Madhyastha, Tara; Fekete, Jean-Daniel; Grabowski, Thomas; H. Carr, K.-L. Ma, and G. Santucci
We introduce MultiPiles, a visualization to explore time-series of dense, weighted networks. MultiPiles is based on the physical analogy of piling adjacency matrices, each one representing a single temporal snapshot. Common interfaces for visualizing dynamic networks use techniques such as: flipping/animation; small multiples; or summary views in isolation. Our proposed 'piling' metaphor presents a hybrid of these techniques, leveraging each one's advantages, as well as offering the ability to scale to networks with hundreds of temporal snapshots. While the MultiPiles technique is applicable to many domains, our prototype was initially designed to help neuroscientists investigate changes in brain connectivity networks over several hundred snapshots. The piling metaphor and associated interaction and visual encodings allowed neuroscientists to explore their data, prior to a statistical analysis. They detected high-level temporal patterns in individual networks and this helped them to formulate and reject several hypotheses.
Adaptive Recommendations for Enhanced Non-linear Exploration of Annotated 3D Objects
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Rodriguez, Marcos Balsa; Agus, Marco; Marton, Fabio; Gobbetti, Enrico; H. Carr, K.-L. Ma, and G. Santucci
We introduce a novel approach for letting casual viewers explore detailed 3D models integrated with structured spatially associated descriptive information organized in a graph. Each node associates a subset of the 3D surface seen from a particular viewpoint to the related descriptive annotation, together with its author-defined importance. Graph edges describe, instead, the strength of the dependency relation between information nodes, allowing content authors to describe the preferred order of presentation of information. At run-time, users navigate inside the 3D scene using a camera controller, while adaptively receiving unobtrusive guidance towards interesting viewpoints and history- and location-dependent suggestions on important information, which is adaptively presented using 2D overlays displayed over the 3D scene. The capabilities of our approach are demonstrated in a real-world cultural heritage application involving the public presentation of sculptural complex on a large projection-based display. A user study has been performed in order to validate our approach.
Visual Analysis of Proximal Temporal Relationships of Social and Communicative Behaviors
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Han, Yi; Rozga, Agata; Dimitrova, Nevena; Abowd, Gregory D.; Stasko, John; H. Carr, K.-L. Ma, and G. Santucci
Developmental psychology researchers examine the temporal relationships of social and communicative behaviors, such as how a child responds to a name call, to understand early typical and atypical development and to discover early signs of autism and developmental delay. These related behaviors occur together or within close temporal proximity, forming unique patterns and relationships of interest. However, the task of finding these early signs, which are in the form of atypical behavioral patterns, becomes more challenging when behaviors of multiple children at different ages need to be compared with each other in search of generalizable patterns. The ability to visually explore the temporal relationships of behaviors, including flexible redefinition of closeness, over multiple social interaction sessions with children of different ages, can make such knowledge extraction easier. We have designed a visualization tool called TipoVis that helps psychology researchers visually explore the temporal patterns of social and communicative behaviors. We present two case studies to show how TipoVis helped two researchers derive new understandings of their data.
Visual Assessment of Alleged Plagiarism Cases
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Riehmann, Patrick; Potthast, Martin; Stein, Benno; Froehlich, Bernd; H. Carr, K.-L. Ma, and G. Santucci
We developed a visual analysis tool to support the verification, assessment, and presentation of alleged cases of plagiarism. The analysis of a suspicious document typically results in a compilation of categorized ''finding spots''. The categorization reveals the way in which the suspicious text fragment was created from the source, e.g. by obfuscation, translation, or by shake and paste. We provide a three-level approach for exploring the finding spots in context. The overview shows the relationship of the entire suspicious document to the set of source documents. A glyph-based view reveals the structural and textual differences and similarities of a set of finding spots and their corresponding source text fragments. For further analysis and editing of the finding spot's assessment, the actual text fragments can be embedded side-by-side in the diffline view. The different views are tied together by versatile navigation and selection operations. Our expert reviewers confirm that our tool provides a significant improvement over existing static visualizations for assessing plagiarism cases.
Perfopticon: Visual Query Analysis for Distributed Databases
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Moritz, Dominik; Halperin, Daniel; Howe, Bill; Heer, Jeffrey; H. Carr, K.-L. Ma, and G. Santucci
Distributed database performance is often unpredictable due to issues such as system complexity, network congestion, or imbalanced data distribution. These issues are difficult for users to assess in part due to the opaque mapping between declaratively specified queries and actual physical execution plans. Database developers currently must expend significant time and effort scanning log files to isolate and debug the root causes of performance issues. In response, we present Perfopticon, an interactive query profiling tool that enables rapid insight into common problems such as performance bottlenecks and data skew. Perfopticon combines interactive visualizations of (1) query plans, (2) overall query execution, (3) data flow among servers, and (4) execution traces. These views coordinate multiple levels of abstraction to enable detection, isolation, and understanding of performance issues. We evaluate our design choices through engagements with system developers, scientists, and students. We demonstrate that Perfopticon enables performance debugging for real-world tasks.
Efficient Local Histogram Searching via Bitmap Indexing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wei, Tzu-Hsuan; Chen, Chun-Ming; Biswas, Ayan; H. Carr, K.-L. Ma, and G. Santucci
Representing features by local histograms is a proven technique in several volume analysis and visualization applications including feature tracking and transfer function design. The efficiency of these applications, however, is hampered by the high computational complexity of local histogram computation and matching. In this paper, we propose a novel algorithm to accelerate local histogram search by leveraging bitmap indexing. Our method avoids exhaustive searching of all voxels in the spatial domain by examining only the voxels whose values fall within the value range of user-defined local features and their neighborhood. Based on the idea that the value range of local features is in general much smaller than the dynamic range of the entire dataset, we propose a local voting scheme to construct the local histograms so that only a small number of voxels need to be examined. Experimental results show that our method can reduce much computational workload compared to the conventional approaches. To demonstrate the utility of our method, an interactive interface was developed to assist users in defining target features as local histograms and identify the locations of these features in the dataset.
Guided Volume Editing based on Histogram Dissimilarity
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Karimov, Alexey; Mistelbauer, Gabriel; Auzinger, Thomas; Bruckner, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and errorprone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high-quality segmentations.
Compressive Volume Rendering
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liu, Xiaoyang; Alim, Usman R.; H. Carr, K.-L. Ma, and G. Santucci
Compressive rendering refers to the process of reconstructing a full image from a small subset of the rendered pixels, thereby expediting the rendering task. In this paper, we empirically investigate three image order techniques for compressive rendering that are suitable for direct volume rendering. The first technique is based on the theory of compressed sensing and leverages the sparsity of the image gradient in the Fourier domain. The latter techniques exploit smoothness properties of the rendered image; the second technique recovers the missing pixels via a total variation minimization procedure while the third technique incorporates a smoothness prior in a variational reconstruction framework employing interpolating cubic B-splines. We compare and contrast the three techniques in terms of quality, efficiency and sensitivity to the distribution of pixels. Our results show that smoothness-based techniques significantly outperform techniques that are based on compressed sensing and are also robust in the presence of highly incomplete information. We achieve high quality recovery with as little as 20% of the pixels distributed uniformly in screen space.
Learning Probabilistic Transfer Functions: A Comparative Study of Classifiers
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Soundararajan, Krishna Prasad; Schultz, Thomas; H. Carr, K.-L. Ma, and G. Santucci
Complex volume rendering tasks require high-dimensional transfer functions, which are notoriously difficult to design. One solution to this is to learn transfer functions from scribbles that the user places in the volumetric domain in an intuitive and natural manner. In this paper, we explicitly model and visualize the uncertainty in the resulting classification. To this end, we extend a previous intelligent system approach to volume rendering, and we systematically compare five supervised classification techniques - Gaussian Naive Bayes, k Nearest Neighbor, Support Vector Machines, Neural Networks, and Random Forests - with respect to probabilistic classification, support for multiple materials, interactive performance, robustness to unreliable input, and easy parameter tuning, which we identify as key requirements for the successful use in this application. Based on theoretical considerations, as well as quantitative and visual results on volume datasets from different sources and modalities, we conclude that, while no single classifier can be expected to outperform all others under all circumstances, random forests are a useful off-the-shelf technique that provides fast, easy, robust and accurate results in many scenarios.
Rule-Enhanced Transfer Function Generation for Medical Volume Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cai, Li-Le; Nguyen, Binh P.; Chui, Chee-Kong; Ong, Sim-Heng; H. Carr, K.-L. Ma, and G. Santucci
In volume visualization, transfer functions are used to classify the volumetric data and assign optical properties to the voxels. In general, transfer functions are generated in a transfer function space, which is the feature space constructed by data values and properties derived from the data. If volumetric objects have the same or overlapping data values, it would be difficult to separate them in the transfer function space. In this paper, we present a rule-enhanced transfer function design method that allows important structures of the volume to be more effectively separated and highlighted. We define a set of rules based on the local frequency distribution of volume attributes. A rule-selection method based on a genetic algorithm is proposed to learn the set of rules that can distinguish the user-specified target tissue from other tissues. In the rendering stage, voxels satisfying these rules are rendered with higher opacities in order to highlight the target tissue. The proposed method was tested on various volumetric datasets to enhance the visualization of important structures that are difficult to be visualized by traditional transfer function design methods. The results demonstrate the effectiveness of the proposed method.
Edge-Aware Volume Smoothing Using L0 Gradient Minimization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Wang, Qichao; Tao, Yubo; Lin, Hai; H. Carr, K.-L. Ma, and G. Santucci
In volume visualization, noise in regions of homogeneous material and at boundaries between different materials poses a great challenge in extracting, analyzing and rendering features of interest. In this paper, we present a novel volume denoising / smoothing method based on the L0 gradient minimization framework. This framework globally controls how many voxels with a non-zero gradient are in the result in order to approximate important features' structures in a sparse way. This procedure can be solved quickly by the alternating optimization strategy with half-quadratic splitting. While the proposed L0 volume gradient minimization method can effectively remove noise in homogeneous materials, a blurring-sharpening strategy is proposed to diminish noise or smooth local details on the boundaries. This generates salient features with smooth boundaries and visually pleasing structures. We compare our method with the bilateral filter and anisotropic diffusion, and demonstrate the effectiveness and efficiency of our method with several volumes in different modalities.
Photoelasticity Raycasting
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Bußler, Michael; Ertl, Thomas; Sadlo, Filip; H. Carr, K.-L. Ma, and G. Santucci
We present a novel physically-based method to visualize stress tensor fields. By incorporating photoelasticity into traditional raycasting and extending it with reflection and refraction, taking into account polarization, we obtain the virtual counterpart to traditional experimental polariscopes. This allows us to provide photoelastic analysis of stress tensor fields in arbitrary domains. In our model, the optical material properties, such as stress-optic coefficient and refractive index, can either be chosen in compliance with the subject under investigation, or, in case of stress problems that do not model optical properties or that are not transparent, be chosen according to known or even new transparent materials. This enables direct application of established polariscope methodology together with respective interpretation. Using a GPU-based implementation, we compare our technique to experimental data, and demonstrate its utility with several simulated datasets.
Visualization of Particle-based Data with Transparency and Ambient Occlusion
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Staib, Joachim; Grottel, Sebastian; Gumhold, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Particle-based simulation techniques, like the discrete element method or molecular dynamics, are widely used in many research fields. In real-time explorative visualization it is common to render the resulting data using opaque spherical glyphs with local lighting only. Due to massive overlaps, however, inner structures of the data are often occluded rendering visual analysis impossible. Furthermore, local lighting is not sufficient as several important features like complex shapes, holes, rifts or filaments cannot be perceived well. To address both problems we present a new technique that jointly supports transparency and ambient occlusion in a consistent illumination model. Our approach is based on the emission-absorption model of volume rendering. We provide analytic solutions to the volume rendering integral for several density distributions within a spherical glyph. Compared to constant transparency our approach preserves the three-dimensional impression of the glyphs much better. We approximate ambient illumination with a fast hierarchical voxel cone-tracing approach, which builds on a new real-time voxelization of the particle data. Our implementation achieves interactive frame rates for millions of static or dynamic particles without any preprocessing. We illustrate the merits of our method on real-world data sets gaining several new insights.
Exploring Traffic Dynamics in Urban Environments Using Vector-Valued Functions
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Poco, Jorge; Doraiswamy, Harish; Vo, Huy. T.; Comba, João L. D.; Freire, Juliana; Silva, Cláudio T.; H. Carr, K.-L. Ma, and G. Santucci
The traffic infrastructure greatly impacts the quality of life in urban environments. To optimize this infrastructure, engineers and decision makers need to explore traffic data. In doing so, they face two important challenges: the sparseness of speed sensors that cover only a limited number of road segments, and the complexity of traffic patterns they need to analyze. In this paper we take a first step at addressing these challenges. We use New York City (NYC) taxi trips as sensors to capture traffic information. While taxis provide substantial coverage of the city, the data captured about taxi trips contain neither the location of taxis at frequent intervals nor their routes. We propose an efficient traffic model to derive speed and direction information from these data, and show that it provides reliable estimates. Using these estimates, we define a time-varying vector-valued function on a directed graph representing the road network, and adapt techniques used for vector fields to visualize the traffic dynamics. We demonstrate the utility of our technique in several case studies that reveal interesting mobility patterns in NYC's traffic. These patterns were validated by experts from NYC's Department of Transportation and the NYC Taxi & Limousine Commission, who also provided interesting insights into these results.
Interactive Visual Analysis for Vehicle Detector Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Chen, Yi-Cheng; Wang, Yu-Shuen; Lin, Wen-Chieh; Huang, Wei-Xiang; Lin, I-Chen; H. Carr, K.-L. Ma, and G. Santucci
Visualization of vehicle detection (VD) data is essential because the data play an important role in traffic control and policy development. Most previous works focus on visualizing trajectories obtained from global positioning system (GPS), which are detailed but less representative. In contrast, VD data report the traffic statistic at each sensing site during a time span, including speed, flow, and occupancy of each lane, which contain comprehensive traffic information for analysis. In this work, we visualize three-year VD data of freeways in Taiwan. The visualization depicts the traffic situation at a site over time using a color-coded chart that extends from left to right over time. The charts are vertically stacked and horizontally aligned according to VD's located mileage and data time, respectively, to provide global insight. Our system allows semantic zoom, which changes the chart appearance in a continuous manner, to enable macro- and micro- scopic visualizations. Analysts can explore events that span an area with different sizes and that persist a time span with various lengths. To ensure the feasibility of our visualization, before the system design, we conducted a study with experts who work in the national freeway bureau and the institute of transportation of Taiwan. We also showed our results to the experts after the prototype system was built. The feedback shows that our VD data visualization is helpful to traffic control and policy development.
Visual Analytics for Exploring Local Impact of Air Traffic
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Buchmüller, Juri; Janetzko, Halldor; Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg; Keim, Daniel A.; H. Carr, K.-L. Ma, and G. Santucci
The environmental and noise impact of airports often causes extensive political discussion which in some cases even lead to transnational tensions. Analyzing local approach and departure patterns around an airport is difficult since it depends on a variety of complex variables like weather, local and general regulations and many more. Yet, understanding these movements and the expected amount of flights during arrival and departure is of great interest to both casual and expert users, as planes have a higher impact on the areas beneath during these phases. We present a Visual Analytics framework that enables users to develop an understanding of local flight behavior through visual exploration of historical data and interactive manipulation of prediction models with direct feedback, as well as a classification quality visualization using a random noise metaphor. We showcase our approach using real world data from the Zurich International Airport region, where aircraft noise has led to an ongoing conflict between Germany and Switzerland. The use cases, findings and expert feedback demonstrate how our approach helps in understanding the situation and to substantiate the otherwise often subjective discourse on the topic.
Rationale Visualization for Safety and Security
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Scheepens, Roeland; Michels, Steffen; Wetering, Huub van de; Wijk, Jarke J. van; H. Carr, K.-L. Ma, and G. Santucci
In safety and security domains where objects of interest (OOI), such as people, vessels, or transactions, are continuously monitored, automated reasoning is required due to their sheer number and volume of information. We present a method to visually explain the rationale of a reasoning engine that raises an alarm if a certain situation is reached. Based both on evidence from heterogeneous and possibly unreliable sources, and on a domain specific reasoning structure, this engine concludes with a certain probability that, e.g., the OOI is suspected of smuggling. To support decision making, we visualize the rationale, an abstraction of the complicated reasoning structure. The evidence is displayed in a color-coded matrix that easily reveals if and where observations contradict. In it, domain and operational experts can quickly understand and find complicated patterns and relate them to real-world situations. Also, two groups of these experts evaluate our system through maritime use cases based on real data.
Data-driven Evaluation of Visual Quality Measures
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Sedlmair, Michael; Aupetit, Michael; H. Carr, K.-L. Ma, and G. Santucci
Visual quality measures seek to algorithmically imitate human judgments of patterns such as class separability, correlation, or outliers. In this paper, we propose a novel data-driven framework for evaluating such measures. The basic idea is to take a large set of visually encoded data, such as scatterplots, with reliable human ''ground truth'' judgements, and to use this human-labeled data to learn how well a measure would predict human judgements on previously unseen data. Measures can then be evaluated based on predictive performance-an approach that is crucial for generalizing across datasets but has gained little attention so far. To illustrate our framework, we use it to evaluate 15 state-of-the-art class separation measures, using human ground truth data from 828 class separation judgments on color-coded 2D scatterplots.
Efficient Contrast Effect Compensation with Personalized Perception Models
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Mittelstädt, Sebastian; Keim, Daniel A.; H. Carr, K.-L. Ma, and G. Santucci
Color is one of the most effective visual variables and is frequently used to encode metric quantities. Contrast effects are considered harmful in data visualizations since they significantly bias our perception of colors. For instance, a gray patch appears brighter on a black background than on a white background. Accordingly, the perception of color-encoded data items depends on the surround in the rendered visualization. A method that compensates for contrast effects has been presented previously, which significantly improves the users' accuracy in reading and comparing color encoded data. The method utilizes established perception models to compensate for contrast effects, assuming an average human observer. In this paper, we provide experiments that show a significant difference in the perception of users. We introduce methods to personalize contrast effect compensation and show that this outperforms the original method with a user study. We, further, overcome the major limitation of the original method, which is a runtime of several minutes. With the use of efficient optimization and surrogate models, we are able to reduce runtime to milliseconds, making the method applicable in interactive visualizations.
An Evaluation of the Impact of Visual Embellishments in Bar Charts
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Skau, Drew; Harrison, Lane; Kosara, Robert; H. Carr, K.-L. Ma, and G. Santucci
As data visualization becomes further intertwined with the field of graphic design and information graphics, small graphical alterations are made to many common chart formats. Despite the growing prevalence of these embellishments, their effects on communication of the charts' data is unknown. From an overview of the design space, we have outlined some of the common embellishments that are made to bar charts. We have studied the effects of these chart embellishments on the communication of the charts' data through a series of user studies on Amazon's Mechanical Turk platform. The results of these studies lead to a better understanding of how each chart type is perceived, and help provide guiding principles for the graphic design of charts.
An Exploratory Study of Data Sketching for Visual Representation
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Walny, Jagoda; Huron, Samuel; Carpendale, Sheelagh; H. Carr, K.-L. Ma, and G. Santucci
Hand-drawn sketching on napkins or whiteboards is a common, accessible method for generating visual representations. This practice is shared by experts and non-experts and is probably one of the faster and more expressive ways to draft a visual representation of data. In order to better understand the types of and variations in what people produce when sketching data, we conducted a qualitative study. We asked people with varying degrees of visualization expertise, from novices to experts, to manually sketch representations of a small, easily understandable dataset using pencils and paper and to report on what they learned or found interesting about the data. From this study, we extract a data sketching representation continuum from numeracy to abstraction; a data report spectrum from individual data items to speculative data hypothesis; and show the correspondence between the representation types and the data reports from our results set. From these observations we discuss the participants' representations in relation to their data reports, indicating implications for design and potentially fruitful directions for research.
Fiber Surfaces: Generalizing Isosurfaces to Bivariate Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Carr, Hamish; Geng, Zhao; Tierny, Julien; Chattopadhyay, Amit; Knoll, Aaron; H. Carr, K.-L. Ma, and G. Santucci
Scientific visualization has many effective methods for examining and exploring scalar and vector fields, but rather fewer for bivariate fields. We report the first general purpose approach for the interactive extraction of geometric separating surfaces in bivariate fields. This method is based on fiber surfaces: surfaces constructed from sets of fibers, the multivariate analogues of isolines. We show simple methods for fiber surface definition and extraction. In particular, we show a simple and efficient fiber surface extraction algorithm based on Marching Cubes. We also show how to construct fiber surfaces interactively with geometric primitives in the range of the function. We then extend this to build user interfaces that generate parameterized families of fiber surfaces with respect to arbitrary polygons. In the special case of isovalue-gradient plots, fiber surfaces capture features geometrically for quantitative analysis that have previously only been analysed visually and qualitatively using multi-dimensional transfer functions in volume rendering. We also demonstrate fiber surface extraction on a variety of bivariate data.
Interactive Fusion and Tracking For Multi-Modal Spatial Data Visualization
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Elshehaly, Mai; Gracanin, Denis; Gad, Mohamed; Elmongui, Hicham G.; Matkovic, Kresimir; H. Carr, K.-L. Ma, and G. Santucci
Scientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time-identified events, have fueled the need for interactive techniques to successfully analyze and understand trends and patterns across space and time. We present a novel interactive visualization technique that fuses ground truth measurements with simulation results in real-time to support the continuous tracking and analysis of spatiotemporal patterns. We start by constructing a reference model which densely represents the expected temporal behavior, and then use GPU parallelism to advect measurements on the model and track their location at any given point in time. Our results show that users can interactively fill the spatio-temporal gaps in real world observations, and generate animations that accurately describe physical phenomena.
A Multi-task Comparative Study on Scatter Plots and Parallel Coordinates Plots
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kanjanabose, Rassadarie; Abdul-Rahman, Alfie; Chen, Min; H. Carr, K.-L. Ma, and G. Santucci
Previous empirical studies for comparing parallel coordinates plots and scatter plots showed some uncertainty about their relative merits. Some of these studies focused on the task of value retrieval, where visualization usually has a limited advantage over reading data directly. In this paper, we report an empirical study that compares user performance, in terms of accuracy and response time, in the context of four different visualization tasks, namely value retrieval, clustering, outlier detection, and change detection. In order to evaluate the relative merits of the two types of plots with a common base line (i.e., reading data directly), we included three forms of stimuli, data tables, scatter plots, and parallel coordinate plots. Our results show that data tables are better suited for the value retrieval task, while parallel coordinates plots generally outperform the two other visual representations in three other tasks. Subjective feedbacks from the users are also consistent with the quantitative analyses. As visualization is commonly used for aiding multiple observational and analytical tasks, our results provided new evidence to support the prevailing enthusiasm for parallel coordinates plots in the field of visualization.
Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liu, Shusen; Wang, Bei; Thiagarajan, Jayaraman J.; Bremer, Peer-Timo; Pascucci, Valerio; H. Carr, K.-L. Ma, and G. Santucci
We introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that create smooth animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.
Uncovering Representative Groups in Multidimensional Projections
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Joia, Paulo; Petronetto, Fabiano; Nonato, Luis Gustavo; H. Carr, K.-L. Ma, and G. Santucci
Multidimensional projection-based visualization methods typically rely on clustering and attribute selection mechanisms to enable visual analysis of multidimensional data. Clustering is often employed to group similar instances according to their distance in the visual space. However, considering only distances in the visual space may be misleading due to projection errors as well as the lack of guarantees to ensure that distinct clusters contain instances with different content. Identifying clusters made up of a few elements is also an issue for most clustering methods. In this work we propose a novel multidimensional projection-based visualization technique that relies on representative instances to define clusters in the visual space. Representative instances are selected by a deterministic sampling scheme derived from matrix decomposition, which is sensitive to the variability of data while still been able to handle classes with a small number of instances. Moreover, the sampling mechanism can easily be adapted to select relevant attributes from each cluster. Therefore, our methodology unifies sampling, clustering, and feature selection in a simple framework. A comprehensive set of experiments validate our methodology, showing it outperforms most existing sampling and feature selection techniques. A case study shows the effectiveness of the proposed methodology as a visual data analysis tool.
Visualnostics: Visual Guidance Pictograms for Analyzing Projections of High-dimensional Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Lehmann, Dirk J.; Kemmler, Fritz; Zhyhalava, Tatsiana; Kirschke, Marco; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of multivariate projections is a challenging task, because complex visual structures occur. This causes fatigue or misinterpretations, which distorts the analysis. In fact, the same projection can lead to different analysis results. We provide visual guidance pictograms to improve objectivity of the visual search. A visual guidance pictogram is an iconic visual density map encoding the visual structure of certain data properties. By using them to guide the analysis, structures in the projection can be better understood and mentally linked to properties in the data. We introduce a systematic scheme for designing such pictograms and provide a set of pictograms for standard visual tasks, such as correlation and distribution analysis, for standard projections like scatterplots, RadVis, and Star Coordinates. We conduct a study that compares the visual analysis of real data with and without the support of guidance pictograms. Our tests show that the training effort for a visual search can be decreased and the analysis bias can be reduced by supporting the user's visual search with guidance pictograms.
Refinery: Visual Exploration of Large, Heterogeneous Networks through Associative Browsing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kairam, Sanjay; Henry-Riche, Nathalie; Drucker, Steven; Fernandez, Roland; Heer, Jeffrey; H. Carr, K.-L. Ma, and G. Santucci
Browsing is a fundamental aspect of exploratory information-seeking. Associative browsing represents a common and intuitive set of exploratory strategies in which users step iteratively from familiar to novel bits of information. In this paper, we examine associative browsing as a strategy for bottom-up exploration of large, heterogeneous networks. We present Refinery, an interactive visualization system informed by guidelines for associative browsing drawn from literature on exploratory information-seeking. These guidelines motivate Refinery's query model, which allows users to simply and expressively construct queries using heterogeneous sets of nodes. This system computes degree-of-interest scores for associated content using a fast, random-walk algorithm. Refinery visualizes query nodes within a subgraph of results, providing explanatory context, facilitating serendipitous discovery, and stimulating continued exploration. A study of 12 academic researchers using Refinery to browse publication data demonstrates how the system enables discovery of valuable new content, even within existing areas of expertise.
Dual Adjacency Matrix: Exploring Link Groups in Dense Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dinkla, Kasper; Henry-Riche, Nathalie; Westenberg, Michel A.; H. Carr, K.-L. Ma, and G. Santucci
Node grouping is a common way of adding structure and information to networks that aids their interpretation. However, certain networks benefit from the grouping of links instead of nodes. Link communities, for example, are a form of link groups that describe high-quality overlapping node communities. There is a conceptual gap between node groups and link groups that poses an interesting visualization challenge. We introduce the Dual Adjacency Matrix to bridge this gap. This matrix combines node and link group techniques via a generalization that also enables it to be coordinated with a node-link-contour diagram. These methods have been implemented in a prototype that we evaluated with an information scientist and neuroscientist via interviews and prototype walk- throughs. We demonstrate this prototype with the analysis of a trade network and an fMRI correlation network.
Detangler: Visual Analytics for Multiplex Networks
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Renoust, Benjamin; Melancon, Guy; Munzner, Tamara; H. Carr, K.-L. Ma, and G. Santucci
A multiplex network has links of different types, allowing it to express many overlapping types of relationships. A core task in network analysis is to evaluate and understand group cohesion; that is, to explain why groups of elements belong together based on the underlying structure of the network. We present Detangler, a system that supports visual analysis of group cohesion in multiplex networks through dual linked views. These views feature new data abstractions derived from the original multiplex network: the substrate network and the catalyst network. We contribute two novel techniques that allow the user to analyze the complex structure of the multiplex network without the extreme visual clutter that would result from simply showing it directly. The harmonized layout visual encoding technique provides spatial stability between the substrate and catalyst views. The pivot brushing interaction technique supports linked highlighting between the views based on computations in the underlying multiplex network to leapfrog between subsets of catalysts and substrates. We present results from the motivating application domain of annotated news documents with a usage scenario and preliminary expert feedback. A second usage scenario presents group cohesion analysis of the social network of the early American independence movement.
Visualization of Object-Centered Vulnerability to Possible Flood Hazards
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cornel, Daniel; Konev, Artem; Sadransky, Bernhard; Horvath, Zsolt; Gröller, Eduard; Waser, Jürgen; H. Carr, K.-L. Ma, and G. Santucci
As flood events tend to happen more frequently, there is a growing demand for understanding the vulnerability of infrastructure to flood-related hazards. Such demand exists both for flood management personnel and the general public. Modern software tools are capable of generating uncertainty-aware flood predictions. However, the information addressing individual objects is incomplete, scattered, and hard to extract. In this paper, we address vulnerability to flood-related hazards focusing on a specific building. Our approach is based on the automatic extraction of relevant information from a large collection of pre-simulated flooding events, called a scenario pool. From this pool, we generate uncertainty-aware visualizations conveying the vulnerability of the building of interest to different kinds of flooding events. On the one hand, we display the adverse effects of the disaster on a detailed level, ranging from damage inflicted on the building facades or cellars to the accessibility of the important infrastructure in the vicinity. On the other hand, we provide visual indications of the events to which the building of interest is vulnerable in particular. Our visual encodings are displayed in the context of urban 3D renderings to establish an intuitive relation between geospatial and abstract information. We combine all the visualizations in a lightweight interface that enables the user to study the impacts and vulnerabilities of interest and explore the scenarios of choice. We evaluate our solution with experts involved in flood management and public communication.
VIMTEX: A Visualization Interface for Multivariate, Time-Varying, Geological Data Exploration
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Dasgupta, Aritra; Kosara, Robert; Gosink, Luke; H. Carr, K.-L. Ma, and G. Santucci
Observing interactions among chemical species and microorganisms in the earth's sub-surface is a common task in the field of geology. Bioremediation experiments constitute one such class of interactions which focus on getting rid of pollutants through processes such as carbon sequestration. The main goal of scientists' observations is to analyze the dynamics of the chemical reactions and understand how they collectively affect the carbon content of the soil. In our work, we extract the high-level goals of geologists and propose a visual analytics solution which helps scientists in deriving insights about multivariate, temporal behavior of these chemical species. Specifically, our key contributions are the following: i) characterization of the domain-specific goals and their translation to exploratory data analysis tasks, ii) developing an analytical abstraction in the form of perceptually motivated screen-space metrics for bridging the gap between the tasks and the visualization, and iii) realization of the tasks and metrics in the form of VIMTEX, which is a set of coordinated multiple views for letting scientists observe multivariate, temporal relationships in the data. We provide several examples and case studies along with expert feedback for demonstrating the efficacy of our solution.
Mosaic Drawings and Cartograms
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Cano, Rafael G.; Buchin, Kevin; Castermans, Thom; Pieterse, Astrid; Sonke, Willem; Speckmann, Bettina; H. Carr, K.-L. Ma, and G. Santucci
Cartograms visualize quantitative data about a set of regions such as countries or states. There are several different types of cartograms and - for some - algorithms to automatically construct them exist. We focus on mosaic cartograms: cartograms that use multiples of simple tiles - usually squares or hexagons - to represent regions. Mosaic cartograms communicate well data that consist of, or can be cast into, small integer units (for example, electorial college votes). In addition, they allow users to accurately compare regions and can often maintain a (schematized) version of the input regions' shapes. We propose the first fully automated method to construct mosaic cartograms. To do so, we first introduce mosaic drawings of triangulated planar graphs. We then show how to modify mosaic drawings into mosaic cartograms with low cartographic error while maintaining correct adjacencies between regions. We validate our approach experimentally and compare to other cartogram methods.
Visualizing Time-Specific Hurricane Predictions, with Uncertainty, from Storm Path Ensembles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Liu, Le; Mirzargar, Mahsa; Kirby, Robert M.; Whitaker, Ross; House, Donald H.; H. Carr, K.-L. Ma, and G. Santucci
The U.S. National Hurricane Center (NHC) issues advisories every six hours during the life of a hurricane. These advisories describe the current state of the storm, and its predicted path, size, and wind speed over the next five days. However, from these data alone, the question ''What is the likelihood that the storm will hit Houston with hurricane strength winds between 12:00 and 14:00 on Saturday?'' cannot be directly answered. To address this issue, the NHC has recently begun making an ensemble of potential storm paths available as part of each storm advisory. Since each path is parameterized by time, predicted values such as wind speed associated with the path can be inferred for a specific time period by analyzing the statistics of the ensemble. This paper proposes an approach for generating smooth scalar fields from such a predicted storm path ensemble, allowing the user to examine the predicted state of the storm at any chosen time. As a demonstration task, we show how our approach can be used to support a visualization tool, allowing the user to display predicted storm position - including its uncertainty - at any time in the forecast. In our approach, we estimate the likelihood of hurricane risk for a fixed time at any geospatial location by interpolating simplicial depth values in the path ensemble. Adaptivelysized radial basis functions are used to carry out the interpolation. Finally, geometric fitting is used to produce a simple graphical visualization of this likelihood. We also employ a non-linear filter, in time, to assure frame-toframe coherency in the visualization as the prediction time is advanced. We explain the underlying algorithm and definitions, and give a number of examples of how our algorithm performs for several different storm predictions, and for two different sources of predicted path ensembles.
Quantitative Measures for Cartogram Generation Techniques
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Alam, Md. Jawaherul; Kobourov, Stephen G.; Veeramoni, Sankar; H. Carr, K.-L. Ma, and G. Santucci
Cartograms are used to visualize geographically distributed data by scaling the regions of a map (e.g., US states) such that their areas are proportional to some data associated with them (e.g., population). Thus the cartogram computation problem can be considered as a map deformation problem where the input is a planar polygonal map M and an assignment of some positive weight for each region. The goal is to create a deformed map M0, where the area of each region realizes the weight assigned to it (no cartographic error) while the overall map remains readable and recognizable (e.g., the topology, relative positions and shapes of the regions remain as close to those before the deformation as possible). Although several such measures of cartogram quality are well-known, different cartogram generation methods optimize different features and there is no standard set of quantitative metrics. In this paper we define such a set of seven quantitative measures, designed to evaluate how faithfully a cartogram represents the desired weights and to estimate the readability of the final representation. We then study several cartogram-generation algorithms and compare them in terms of these quantitative measures.
Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Diehl, Alexandra; Pelorosso, Leandro; Delrieux, Claudio; Saulo, Celeste; Ruiz, Juan; Gröller, M. Eduard; Bruckner, Stefan; H. Carr, K.-L. Ma, and G. Santucci
Weather conditions affect multiple aspects of human life such as economy, safety, security, and social activities. For this reason, weather forecast plays a major role in society. Currently weather forecasts are based on Numerical Weather Prediction (NWP) models that generate a representation of the atmospheric flow. Interactive visualization of geo-spatial data has been widely used in order to facilitate the analysis of NWP models. This paper presents a visualization system for the analysis of spatio-temporal patterns in short-term weather forecasts. For this purpose, we provide an interactive visualization interface that guides users from simple visual overviews to more advanced visualization techniques. Our solution presents multiple views that include a timeline with geo-referenced maps, an integrated webmap view, a forecast operation tool, a curve-pattern selector, spatial filters, and a linked meteogram. Two key contributions of this work are the timeline with geo-referenced maps and the curve-pattern selector. The latter provides novel functionality that allows users to specify and search for meaningful patterns in the data. The visual interface of our solution allows users to detect both possible weather trends and errors in the weather forecast model.We illustrate the usage of our solution with a series of case studies that were designed and validated in collaboration with domain experts.
A Shot at Visual Vulnerability Analysis
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kerzner, Ethan; Butler, Lee A.; Hansen, Charles; Meyer, Miriah; H. Carr, K.-L. Ma, and G. Santucci
Increasing the safety of vehicles is an important goal for vehicle manufacturers. These manufacturers often turn to simulations to understand how to improve a vehicle's design as real-world safety tests are expensive and time consuming. Understanding the results of these simulations, however, is challenging due to the complexity of the data, which often includes both spatial and nonspatial data types. In this design study we collaborated with analysts who are trying to understand the vulnerability of military vehicles. From this design study we contribute a problem characterization, data abstraction, and task analysis for vehicle vulnerability analysis, as well as a validated and deployed tool called Shotviewer. Shotviewer links 3D spatial views with abstract 2D views to support a broad range of analysis needs. Furthermore, reflection on our design study process elucidates a strategy of viewdesign parallelism for creating multiview visualizations, as well as four recommendations for conducting design studies in large organizations with sensitive data.
A Novel Framework for Visual Detection and Exploration of Performance Bottlenecks in Organic Photovoltaic Solar Cell Materials
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Aboulhassan, Amal; Baum, Daniel; Wodo, Olga; Ganapathysubramanian, Baskar; Amassian, Aram; Hadwiger, Markus; H. Carr, K.-L. Ma, and G. Santucci
Current characterization methods of the so-called Bulk Heterojunction (BHJ), which is the main material of Organic Photovoltaic (OPV) solar cells, are limited to the analysis of global fabrication parameters. This reduces the efficiency of the BHJ design process, since it misses critical information about the local performance bottlenecks in the morphology of the material. In this paper, we propose a novel framework that fills this gap through visual characterization and exploration of local structure-performance correlations. We also propose a formula that correlates the structural features with the performance bottlenecks. Since research into BHJ materials is highly multidisciplinary, our framework enables a visual feedback strategy that allows scientists to build intuition about the best choices of fabrication parameters. We evaluate the usefulness of our proposed system by obtaining new BHJ characterizations. Furthermore, we show that our approach could substantially reduce the turnaround time.
Visual Analytics for Correlation-Based Comparison of Time Series Ensembles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Köthur, Patrick; Witt, Carl; Sips, Mike; Marwan, Norbert; Schinkel, Stefan; Dransch, Doris; H. Carr, K.-L. Ma, and G. Santucci
An established approach to studying interrelations between two non-stationary time series is to compute the 'windowed' cross-correlation (WCC). The time series are divided into intervals and the cross-correlation between corresponding intervals is calculated. The outcome is a matrix that describes the correlation between two time series for different intervals and varying time lags. This important technique can only be used to compare two single time series. However, many applications require the comparison of ensembles of time series. Therefore, we propose a visual analytics approach that extends the WCC to support a correlation-based comparison of two ensembles of time series. We compute the pairwise WCC between all time series from the two ensembles, which results in hundreds of thousands of WCC matrices. Statistical measures are used to derive a concise description of the time-varying correlations between the ensembles as well as the uncertainty of the correlation values. We further introduce a visually scalable overview visualization of the computed correlation and uncertainty information. These components are combined with multiple linked views into a visual analytics system to support configuration of the WCC as well as detailed analysis of correlation patterns between two ensembles. Two use cases from very different domains, cognitive science and paleoclimatology, demonstrate the utility of our approach.
Map-based Visualizations Increase Recall Accuracy of Data
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Saket, Bahador; Scheidegger, Carlos; Kobourov, Stephen G.; Börner, Katy; H. Carr, K.-L. Ma, and G. Santucci
We investigate the memorability of data represented in two different visualization designs. In contrast to recent studies that examine which types of visual information make visualizations memorable, we examine the effect of different visualizations on time and accuracy of recall of the displayed data, minutes and days after interaction with the visualizations. In particular, we describe the results of an evaluation comparing the memorability of two different visualizations of the same relational data: node-link diagrams and map-based visualization. We find significant differences in the accuracy of the tasks performed, and these differences persist days after the original exposure to the visualizations. Specifically, participants in the study recalled the data better when exposed to map-based visualizations as opposed to node-link diagrams. We discuss the scope of the study and its limitations, possible implications, and future directions.
Persistent Homology for the Evaluation of Dimensionality Reduction Schemes
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Rieck, Bastian; Leitte, Heike; H. Carr, K.-L. Ma, and G. Santucci
High-dimensional data sets are a prevalent occurrence in many application domains. This data is commonly visualized using dimensionality reduction (DR) methods. DR methods provide e.g. a two-dimensional embedding of the abstract data that retains relevant high-dimensional characteristics such as local distances between data points. Since the amount of DR algorithms from which users may choose is steadily increasing, assessing their quality becomes more and more important. We present a novel technique to quantify and compare the quality of DR algorithms that is based on persistent homology. An inherent beneficial property of persistent homology is its robustness against noise which makes it well suited for real world data. Our pipeline informs about the best DR technique for a given data set and chosen metric (e.g. preservation of local distances) and provides knowledge about the local quality of an embedding, thereby helping users understand the shortcomings of the selected DR method. The utility of our method is demonstrated using application data from multiple domains and a variety of commonly used DR methods.
Feature-Driven Visual Analytics of Chaotic Parameter-Dependent Movement
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Luboschik, Martin; Röhlig, Martin; Bittig, Arne T.; Andrienko, Natalia; Schumann, Heidrun; Tominski, Christian; H. Carr, K.-L. Ma, and G. Santucci
Analyzing movements in their spatial and temporal context is a complex task. We are additionally interested in understanding the movements' dependency on parameters that govern the processes behind the movement. We propose a visual analytics approach combining analytic, visual, and interactive means to deal with the added complexity. The key idea is to perform an analytical extraction of features that capture distinct movement characteristics. Different parameter configurations and extracted features are then visualized in a compact fashion to facilitate an overview of the data. Interaction enables the user to access details about features, to compare features, and to relate features back to the original movement. We instantiate our approach with a repository of more than twenty accepted and novel features to help analysts in gaining insight into simulations of chaotic behavior of thousands of entities over thousands of data points. Domain experts applied our solution successfully to study dynamic groups in such movements in relation to thousands of parameter configurations.
GraphUnit: Evaluating Interactive Graph Visualizations Using Crowdsourcing
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Okoe, Mershack; Jianu, Radu; H. Carr, K.-L. Ma, and G. Santucci
We present GraphUnit, a framework and online service that automates the process of designing, running and analyzing results of controlled user studies of graph visualizations by leveraging crowdsourcing and a set of evaluation modules based on a graph task taxonomy. User studies play an important role in visualization research but conducting them requires expertise and is time consuming. GraphUnit simplifies the evaluation process by allowing visualization designers to easily configure user studies for their web-based graph visualizations, deploy them online, use Mechanical Turk to attract participants, collect user responses and store them in a database, and analyze incoming results automatically using appropriate statistical tools and graphs. We demonstrate the effectiveness of GraphUnit by replicating two published evaluation studies on network visualization, and showing that these studies could be configured in less than an hour. Finally, we discuss how GraphUnit can facilitate quick evaluations of alternative graph designs and thus encourage the frequent use of user studies to evaluate design decisions in iterative development processes.
Towards a Smooth Design Process for Static Communicative Node-link Diagrams
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Suslik Spritzer, Andre; Boy, Jeremy; Dragicevic, Pierre; Fekete, Jean-Daniel; Dal Sasso Freitas, Carla Maria; H. Carr, K.-L. Ma, and G. Santucci
Node-link infographics are visually very rich and can communicate messages effectively, but can be very difficult to create, often involving a painstaking and artisanal process. In this paper we present an investigation of nodelink visualizations for communication and how to better support their creation. We begin by breaking down these images into their basic elements and analyzing how they are created. We then present a set of techniques aimed at improving the creation workflow by bringing more flexibility and power to users, letting them manipulate all aspects of a node-link diagram (layout, visual attributes, etc.) while taking into account the context in which it will appear. These techniques were implemented in a proof-of-concept prototype called GraphCoiffure, which was designed as an intermediary step between graph drawing/editing software and image authoring applications. We describe how GraphCoiffure improves the workflow and illustrate its benefits through practical examples.
Finite-Time Mass Separation for Comparative Visualizations of Inertial Particles
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Günther, Tobias; Theisel, Holger; H. Carr, K.-L. Ma, and G. Santucci
The visual analysis of flows with inertial particle trajectories is a challenging problem because time-dependent particle trajectories additionally depend on mass, which gives rise to an infinite number of possible trajectories passing through every point in space-time. This paper presents an approach to a comparative visualization of the inertial particles' separation behavior. For this, we define the Finite-Time Mass Separation (FTMS), a scalar field that measures at each point in the domain how quickly inertial particles separate that were released from the same location but with slightly different mass. Extracting and visualizing the mass that induces the largest separation provides a simplified view on the critical masses. By using complementary coordinated views, we additionally visualize corresponding inertial particle trajectories in space-time by integral curves and surfaces. For a quantitative analysis, we plot Euclidean and arc length-based distances to a reference particle over time, which allows to observe the temporal evolution of separation events. We demonstrate our approach on a number of analytic and one real-world unsteady 2D field.
Vector Field Visualization of Advective-Diffusive Flows
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Hochstetter, Hendrik; Wurm, Maximilian; Kolb, Andreas; H. Carr, K.-L. Ma, and G. Santucci
We propose a framework for unified visualization of advective and diffusive concentration fluxes, which play a key role in many phenomena like, e.g. Marangoni convection and microscopic mixing. The main idea is the decomposition of fluxes into their concentration and velocity parts. Using this flux decomposition, we are able to convey advective-diffusive concentration transport using integral lines. In order to visualize superimposed flux effects, we introduce a new graphical metaphor, the stream feather, which adds extensions to stream tubes pointing in the directions of deviating fluxes. The resulting unified visualization of macroscopic advection and microscopic diffusion allows for deeper insight into complex flow scenarios that cannot be achieved with current volume and surface rendering techniques alone. Our approach for flux decomposition and visualization of advective-diffusive flows can be applied to any kind of (simulation) data if velocity and concentration data are available. We demonstrate that our techniques can easily be integrated into Smoothed Particle Hydrodynamics (SPH) based simulations.
Visualization of Coherent Structures of Light Transport
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Zirr, Tobias; Ament, Marco; Dachsbacher, Carsten; H. Carr, K.-L. Ma, and G. Santucci
Inspired by vector field topology, an established tool for the extraction and identification of important features of flows and vector fields, we develop means for the analysis of the structure of light transport. For that, we derive an analogy to vector field topology that defines coherent structures in light transport. We also introduce Finite-Time Path Deflection (FTPD), a scalar quantity that represents the deflection characteristic of all light transport paths passing through a given point in space. For virtual scenes, the FTPD can be computed directly using path-space Monte Carlo integration. We visualize the FTPD field for several example scenes and discuss the revealed structures. Lastly, we show that the coherent regions visualized by the FTPD are closely related to the coherent regions in our new topologically-motivated analysis of light transport. FTPD visualizations are thus also visualizations of the structure of light transport.
Evaluating 2D Flow Visualization Using Eye Tracking
(The Eurographics Association and John Wiley & Sons Ltd., 2015) Ho, Hsin-Yang; Yeh, I-Cheng; Lai, Yu-Chi; Lin, Wen-Chieh; Cherng, Fu-Yin; H. Carr, K.-L. Ma, and G. Santucci
Flow visualization is recognized as an essential tool for many scientific research fields and different visualization approaches are proposed. Several studies are also conducted to evaluate their effectiveness but these studies rarely examine the performance from the perspective of visual perception. In this paper, we aim at exploring how users' visual perception is influenced by different 2D flow visualization methods. An eye tracker is used to analyze users' visual behaviors when they perform the free viewing, advection prediction, flow feature detection, and flow feature identification tasks on the flow field images generated by different visualizations methods. We evaluate the illustration capability of five representative visualization algorithms. Our results show that the eye-tracking-based evaluation provides more insights to quantitatively analyze the effectiveness of these visualization methods.

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