DevLan/vispubs huggingface dataset:
Interactive Exploration of Protein Cavities
Authors: Michael Krone, Martin Falk, Sascha Rehm, Jürgen Pleiss, Thomas Ertl
Published at EuroVis, 2011

We present a novel application for the interactive exploration of cavities within proteins in dynamic data sets. Inside a protein, cavities can often be found close to the active center. Therefore, when analyzing a molecular dynamics simulation trajectory it is of great interest to find these cavities and determine if such a cavity opens up to the environment, making the binding site accessible to the surrounding substrate. Our user‐driven approach enables expert users to select a certain cavity and track its evolution over time. The user is supported by different visualizations of the extracted cavity to facilitate the analysis. The boundary of the protein and its cavities is obtained by means of volume ray casting, where the volume is computed in real‐time for each frame, therefore allowing the examination of time‐dependent data sets. A fast, partial segmentation of the volume is applied to obtain the selected cavity and trace it over time. Domain experts found our method useful when they applied it exemplarily on two trajectories of lipases from Rhizomucor miehei and Candida antarctica. In both data sets cavities near the active center were easily identified and tracked over time until they reached the surface and formed an open substrate channel.
Interactive Visual Analysis of Temporal Cluster Structures
Authors: Cagatay Turkay, Július Parulek, Nathalie Reuter, Helwig Hauser
Published at EuroVis, 2011

Cluster analysis is a useful method which reveals underlying structures and relations of items after grouping them into clusters. In the case of temporal data, clusters are defined over time intervals where they usually exhibit structural changes. Conventional cluster analysis does not provide sufficient methods to analyze these structural changes, which are, however, crucial in the interpretation and evaluation of temporal clusters. In this paper, we present two novel and interactive visualization techniques that enable users to explore and interpret the structural changes of temporal clusters. We introduce the temporal cluster view, which visualizes the structural quality of a number of temporal clusters, and temporal signatures, which represents the structure of clusters over time. We discuss how these views are utilized to understand the temporal evolution of clusters. We evaluate the proposed techniques in the cluster analysis of mixed lipid bilayers.
Lagrangian Coherent Structures with Guaranteed Material Separation
Authors: Tobias Germer, Mathias Otto, Ronald Peikert, Holger Theisel
Published at EuroVis, 2011

Given an unsteady flow field, one common way to compute Lagrangian Coherent Structures (LCS) is to extract extremal structures of the Finite Time Lyapunov Exponent (FTLE). Experience has shown that the resulting structures are often close to material structures (i.e., material lines or material surfaces). Moreover, it has been proven that for an integration time converging to infinity, they converge to exact material structures. However, due to the finite integration time in FTLE, they are generally not exact material structures.In this paper we introduce a modification of the FTLE method which is guaranteed to produce separating material structures as features of a scalar field. We achieve this by incorporating the complete available integration time both in forward and backward direction, and by choosing an appropriate definition for separating structures. We apply our method to two test data sets and show the differences to classical FTLE.
PaperVis: Literature Review Made Easy
Authors: Jia-Kai Chou, Chuan-Kai Yang
Published at EuroVis, 2011

Reviewing literatures for a certain research field is always important for academics. One could use Google‐like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross‐referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user‐friendly interface to help users quickly grasp the intrinsic complex citation‐reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node‐link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis.
Pathway Preserving Representation of Metabolic Networks
Authors: Antoine Lambert, Jonathan Dubois, Romain Bourqui
Published at EuroVis, 2011

Improvements in biological data acquisition and genomes sequencing now allow to reconstruct entire metabolic networks of many living organisms. The size and complexity of these networks prohibit manual drawing and thereby urge the need of dedicated visualization techniques. An efficient representation of such a network should preserve the topological information of metabolic pathways while respecting biological drawing conventions. These constraints complicate the automatic generation of such visualization as it raises graph drawing issues. In this paper we propose a method to lay out the entire metabolic network while preserving the pathway information as much as possible. That method is flexible as it enables the user to define whether or not node duplication should be performed, to preserve or not the network topology. Our technique combines partitioning, node placement and edge bundling to provide a pseudo‐orthogonal visualization of the metabolic network. To ease pathway information retrieval, we also provide complementary interaction tools that emphasize relevant pathways in the entire metabolic context.
Perceptual Evaluation of Ghosted View Techniques for the Exploration of Vascular Structures and Embedded Flow
Authors: Alexandra Baer, Rocco Gasteiger, Douglas W. Cunningham, Bernhard Preim
Published at EuroVis, 2011

This paper presents three controlled perceptual studies investigating the visualization of the cerebral aneurysm anatomy with embedded flow visualization. We evaluate and compare the common semitransparent visualization technique with a ghosted view and a ghosted view with depth enhancement technique. We analyze the techniques’ ability to facilitate and support the shape and spatial representation of the aneurysm models as well as evaluating the smart visibility characteristics. The techniques are evaluated with respect to the participants accuracy, response time and their personal preferences. We used as stimuli 3D aneurysm models of five clinical datasets. There was overwhelming preference for the two ghosted view techniques over the semitransparent technique. Since smart visibility techniques are rarely evaluated, this paper may serve as orientation for further studies.
Piece wise Laplacian-based Projection for Interactive Data Exploration and Organization
Authors: Fernando Vieira Paulovich, Danilo Medeiros Eler, Jorge Poco, Charl P. Botha, Rosane Minghim, Luis Gustavo Nonato
Published at EuroVis, 2011

Multidimensional projection has emerged as an important visualization tool in applications involving the visual analysis of high‐dimensional data. However, high precision projection methods are either computationally expensive or not flexible enough to enable feedback from user interaction into the projection process. A built‐in mechanism that dynamically adapts the projection based on direct user intervention would make the technique more useful for a larger range of applications and data sets. In this paper we propose the Piecewise Laplacian‐based Projection (PLP), a novel multidimensional projection technique, that, due to the local nature of its formulation, enables a versatile mechanism to interact with projected data and to allow interactive changes to alter the projection map dynamically, a capability unique of this technique. We exploit the flexibility provided by PLP in two interactive projection‐based applications, one designed to organize pictures visually and another to build music playlists. These applications illustrate the usefulness of PLP in handling high‐dimensional data in a flexible and highly visual way. We also compare PLP with the currently most promising projections in terms of precision and speed, showing that it performs very well also according to these quality criteria.
Probabilistic Marching Cubes
Authors: Kai Pöthkow, Britta Weber, Hans-Christian Hege
Published at EuroVis, 2011

In this paper we revisit the computation and visualization of equivalents to isocontours in uncertain scalar fields. We model uncertainty by discrete random fields and, in contrast to previous methods, also take arbitrary spatial correlations into account. Starting with joint distributions of the random variables associated to the sample locations, we compute level crossing probabilities for cells of the sample grid. This corresponds to computing the probabilities that the well‐known symmetry‐reduced marching cubes cases occur in random field realizations. For Gaussian random fields, only marginal density functions that correspond to the vertices of the considered cell need to be integrated. We compute the integrals for each cell in the sample grid using a Monte Carlo method. The probabilistic ansatz does not suffer from degenerate cases that usually require case distinctions and solutions of ill‐conditioned problems. Applications in 2D and 3D, both to synthetic and real data from ensemble simulations in climate research, illustrate the influence of spatial correlations on the spatial distribution of uncertain isocontours.
Progressive Splatting of Continuous Scatterplots and Parallel Coordinates
Authors: Julian Heinrich, Sven Bachthaler, Daniel Weiskopf
Published at EuroVis, 2011

Continuous scatterplots and parallel coordinates are used to visualize multivariate data defined on a continuous domain. With the existing techniques, rendering such plots becomes prohibitively slow, especially for large scientific datasets. This paper presents a scalable and progressive rendering algorithm for continuous data plots that allows exploratory analysis of large datasets at interactive framerates. The algorithm employs splatting to produce a series of plots that are combined using alpha blending to achieve a progressively improving image. For each individual frame, splats are obtained by transforming Gaussian density kernels from the 3‐D domain of the input dataset to the respective data domain. A closed‐form analytic description of the resulting splat footprints is derived to allow pre‐computation of splat textures for efficient GPU rendering. The plotting method is versatile because it supports arbitrary reconstruction or interpolation schemes for the input data and the splatting technique is scalable because it chooses splat samples independently from the size of the input dataset. Finally, the effectiveness of the method is compared to existing techniques regarding rendering performance and quality.
Prostate Cancer Visualization from MR Imagery and MR Spectroscopy
Authors: Joseph Marino, Arie E. Kaufman
Published at EuroVis, 2011

Prostate cancer is one of the most prevalent cancers among males, and the use of magnetic resonance imaging (MRI) has been suggested for its detection. A framework is presented for scoring and visualizing various MR data in an efficient and intuitive manner. A classification method is introduced where a cumulative score volume is created which takes into account each of three acquisition types. This score volume is integrated into a volume rendering framework which allows the user to view the prostate gland, the multi‐modal score values, and the surrounding anatomy. A visibility persistence mode is introduced to automatically avoid full occlusion of a selected score and indicate overlaps. The use of GPU‐accelerated multi‐modal single‐pass ray casting provides an interactive experience. User driven importance rendering allows the user to gain insight into the data and can assist in localization of the disease and treatment planning. We evaluate our results against pathology and radiologists'determinations.
Semantic-Preserving Word Clouds by Seam Carving
Authors: Yingcai Wu, Thomas Provan, Furu Wei, Shixia Liu, Kwan-Liu Ma
Published at EuroVis, 2011

Word clouds are proliferating on the Internet and have received much attention in visual analytics. Although word clouds can help users understand the major content of a document collection quickly, their ability to visually compare documents is limited. This paper introduces a new method to create semantic‐preserving word clouds by leveraging tailored seam carving, a well‐established content‐aware image resizing operator. The method can optimize a word cloud layout by removing a left‐to‐right or top‐to‐bottom seam iteratively and gracefully from the layout. Each seam is a connected path of low energy regions determined by a Gaussian‐based energy function. With seam carving, we can pack the word cloud compactly and effectively, while preserving its overall semantic structure. Furthermore, we design a set of interactive visualization techniques for the created word clouds to facilitate visual text analysis and comparison. Case studies are conducted to demonstrate the effectiveness and usefulness of our techniques.
Stable Morse Decompositions for Piecewise Constant Vector Fields on Surfaces
Authors: Andrzej Szymczak
Published at EuroVis, 2011

Numerical simulations and experimental observations are inherently imprecise. Therefore, most vector fields of interest in scientific visualization are known only up to an error. In such cases, some topological features, especially those not stable enough, may be artifacts of the imprecision of the input. This paper introduces a technique to compute topological features of user‐prescribed stability with respect to perturbation of the input vector field. In order to make our approach simple and efficient, we develop our algorithms for the case of piecewise constant (PC) vector fields. Our approach is based on a super‐transition graph, a common graph representation of all PC vector fields whose vector value in a mesh triangle is contained in a convex set of vectors associated with that triangle. The graph is used to compute a Morse decomposition that is coarse enough to be correct for all vector fields satisfying the constraint. Apart from computing stable Morse decompositions, our technique can also be used to estimate the stability of Morse sets with respect to perturbation of the vector field or to compute topological features of continuous vector fields using the PC framework.
Structural Decomposition Trees
Authors: Daniel Engel, René Rosenbaum, Bernd Hamann, Hans Hagen
Published at EuroVis, 2011

Researchers and analysts in modern industrial and academic environments are faced with a daunting amount of multi‐dimensional data. While there has been significant development in the areas of data mining and knowledge discovery, there is still the need for improved visualizations and generic solutions. The state‐of‐the‐art in visual analytics and exploratory data visualization is to incorporate more profound analysis methods while focusing on fast interactive abilities. The common trend in these scenarios is to either visualize an abstraction of the data set or to better utilize screen‐space.This paper presents a novel technique that combines clustering, dimension reduction and multi‐dimensional data representation to form a multivariate data visualization that incorporates both detail and overview. This amalgamation counters the individual drawbacks of common projection and multi‐dimensional data visualization techniques, namely ambiguity and clutter. A specific clustering criterion is used to decompose a multi‐dimensional data set into a hierarchical tree structure. This decomposition is embedded in a novel Dimensional Anchor visualization through the use of a weighted linear dimension reduction technique. The resulting Structural Decomposition Tree (SDT) provides not only an insight of the data set's inherent structure, but also conveys detailed coordinate value information. Further, fast and intuitive interaction techniques are explored in order to guide the user in highlighting, brushing, and filtering of the data.
Tablorer - An Interactive Tree Visualization System for Tablet PCs
Authors: Hyunju Shin, GwangHyun Park, JungHyun Han
Published at EuroVis, 2011

A variety of mobile devices are available today, but there is no dominant tree visualization system in the devices. This paper proposes Tablorer, a novel interactive tree visualization system for medium‐sized mobile devices, especially for tablet PCs. The system shows the hierarchical information with a compact way using an expandable table format. For efficient navigation, the system provides an integrated view of context and focus information. The experimental results show that Tablorer can reduce the search time by about 22%.
Temporal Visualization of Boundary-based Geo-information Using Radial Projection
Authors: Yoann Drocourt, Rita Borgo, Kilian Scharrer, Tavi Murray, Suzanne Bevan, Min Chen 0001
Published at EuroVis, 2011

This work is concerned with a design study by an interdisciplinary team on visualizing a 10‐year record of seasonal and inter‐annual changes in frontal position (advance/retreat) of nearly 200 marine terminating glaciers in Greenland. Whilst the spatiotemporal nature of the raw data presents a challenge to develop a compact and intuitive visual design, the focus on coastal boundaries provides an opportunity for dimensional reduction. In this paper, we report the user‐centered design process carried out by the team, and present several visual encoding schemes that have met the requirements including compactness, intuitiveness, and ability to depict temporal changes and spatial relations. In particular, we designed a family of radial visualization, where radial lines correspond to different coastal locations, and nested rings represent the evolution of the temporal dimension from inner to outer circles. We developed an algorithm for mapping glacier terminus positions from Cartesian coordinates to angular coordinates. Instead of a naive uniform mapping, the algorithm maintains consistent spatial perception of the visually‐sensitive geographical references between their Cartesian and angular coordinates, and distributes other termini positions between primary locations based on coastal distance. This work has provided a useful solution to address the problem of inaccuracy in change evaluation based on pixel‐based visualization [BPC*10].
The Undistort Lens
Authors: John Brosz, Sheelagh Carpendale, Miguel A. Nacenta
Published at EuroVis, 2011

Detail‐in‐context lens techniques can be useful for exploring visualizations of data spaces that are too large or have too much detail to fit in regular displays. For example, by bending the space in the right way we can bring together details from two separate areas for easy comparison while roughly keeping the context that situates each area within the global space. While these techniques can be powerful tools, they also introduce distortions that need to be understood, and often the tools have to be disabled in order to have access to the undistorted data. We introduce the undistort lens, a complement to existing distortion‐based techniques that provides a local and separate presentation of the original geometry without affecting any distortion‐based lenses currently used in the presentation. The undistort lens is designed to allow interactive access to the underlying undistorted data within the context of the distorted space, and to enable a better understanding of the distortions. The paper describes the implementation of a generic back‐mapping mechanism that enables the implementation of undistort lenses for arbitrary distortion based techniques, including those presented in the lens literature. We also provide a series of use‐case scenarios that demonstrate the situations in which the technique can complement existing lenses.
Topological Features in 2D Symmetric Higher-Order Tensor Fields
Authors: Thomas Schultz 0001
Published at EuroVis, 2011

The topological structure of scalar, vector, and second‐order tensor fields provides an important mathematical basis for data analysis and visualization. In this paper, we extend this framework towards higher‐order tensors. First, we establish formal uniqueness properties for a geometrically constrained tensor decomposition. This allows us to define and visualize topological structures in symmetric tensor fields of orders three and four. We clarify that in 2D, degeneracies occur at isolated points, regardless of tensor order. However, for orders higher than two, they are no longer equivalent to isotropic tensors, and their fractional Poincaré index prevents us from deriving continuous vector fields from the tensor decomposition. Instead, sorting the terms by magnitude leads to a new type of feature, lines along which the resulting vector fields are discontinuous. We propose algorithms to extract these features and present results on higher‐order derivatives and higher‐order structure tensors.
Topology-based Visualization of Transformation Pathways in Complex Chemical Systems
Authors: Kenes Beketayev, Gunther H. Weber, Maciej Haranczyk, Peer-Timo Bremer, Mario Hlawitschka, Bernd Hamann
Published at EuroVis, 2011

Studying transformation in a chemical system by considering its energy as a function of coordinates of the system's components provides insight and changes our understanding of this process. Currently, a lack of effective visualization techniques for high‐dimensional energy functions limits chemists to plot energy with respect to one or two coordinates at a time. In some complex systems, developing a comprehensive understanding requires new visualization techniques that show relationships between all coordinates at the same time. We propose a new visualization technique that combines concepts from topological analysis, multi‐dimensional scaling, and graph layout to enable the analysis of energy functions for a wide range of molecular structures. We demonstrate our technique by studying the energy function of a dimer of formic and acetic acids and a LTA zeolite structure, in which we consider diffusion of methane.
Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction
Authors: Wolfgang Berger, Harald Piringer, Peter Filzmoser, M. Eduard Gröller
Published at EuroVis, 2011

Systems projecting a continuous n‐dimensional parameter space to a continuous m‐dimensional target space play an important role in science and engineering. If evaluating the system is expensive, however, an analysis is often limited to a small number of sample points. The main contribution of this paper is an interactive approach to enable a continuous analysis of a sampled parameter space with respect to multiple target values. We employ methods from statistical learning to predict results in real‐time at any user‐defined point and its neighborhood. In particular, we describe techniques to guide the user to potentially interesting parameter regions, and we visualize the inherent uncertainty of predictions in 2D scatterplots and parallel coordinates. An evaluation describes a real‐world scenario in the application context of car engine design and reports feedback of domain experts. The results indicate that our approach is suitable to accelerate a local sensitivity analysis of multiple target dimensions, and to determine a sufficient local sampling density for interesting parameter regions.