DevLan/vispubs huggingface dataset:
A Visual Analytics Approach for Peak-Preserving Prediction of Large Seasonal Time Series
Authors: Ming C. Hao, Halldór Janetzko, Sebastian Mittelstädt, W. Hill, Umeshwar Dayal, Daniel A. Keim, Manish Marwah, Ratnesh K. Sharma
Published at EuroVis, 2011

Time series prediction methods are used on a daily basis by analysts for making important decisions. Most of these methods use some variant of moving averages to reduce the number of data points before prediction. However, to reach a good prediction in certain applications (e.g., power consumption time series in data centers) it is important to preserve peaks and their patterns. In this paper, we introduce automated peak‐preserving smoothing and prediction algorithms, enabling a reliable long term prediction for seasonal data, and combine them with an advanced visual interface: (1) using high resolution cell‐based time series to explore seasonal patterns, (2) adding new visual interaction techniques (multi‐scaling, slider, and brushing &amp; linking) to incorporate human expert knowledge, and (3) providing both new visual accuracy color indicators for validating the predicted results and certainty bands communicating the uncertainty of the prediction. We have integrated these techniques into a well‐fitted solution to support the prediction process, and applied and evaluated the approach to predict both power consumption and server utilization in data centers with 70–80% accuracy.
An Evaluation of Visualization Techniques to Illustrate Statistical Deformation Models
Authors: Jesus J. Caban, Penny Rheingans, Terry S. Yoo
Published at EuroVis, 2011

As collections of 2D/3D images continue to grow, interest in effective ways to visualize and explore the statistical morphological properties of a group of images has surged. Recently, deformation models have emerged as simple methods to capture the variability and statistical properties of a collection of images. Such models have proven to be effective in tasks such as image classification, generation, registration, segmentation, and analysis of modes of variation. A crucial element missing from most statistical models has been an effective way to summarize and visualize the statistical morphological properties of a group of images. This paper evaluates different visualization techniques that can be extended and used to illustrate the information captured by such statistical models. First, four illustration techniques are described as methods to summarize the statistical morphological properties as captured by deformation models. Second, results of a user study conducted to compare the effectiveness of each visualization technique are presented. After comparing the performance of 40 subjects, we found that statistical annotation techniques present significant benefits when analyzing the structural properties of a group of images.
Anatomy-Guided Multi-Level Exploration of Blood Flow in Cerebral Aneurysms
Authors: Mathias Neugebauer, Gábor Janiga, Oliver Beuing, Martin Skalej, Bernhard Preim
Published at EuroVis, 2011

For cerebral aneurysms, the ostium, the area of inflow, is an important anatomic landmark, since it separates the pathological vessel deformation from the healthy parent vessel. A better understanding of the inflow characteristics, the flow inside the aneurysm and the overall change of pre‐ and post‐aneurysm flow in the parent vessel provide insights for medical research and the development of new risk‐reduced treatment options. We present an approach for a qualitative, visual flow exploration that incorporates the ostium and derived anatomical landmarks. It is divided into three scopes: a global scope for exploration of the in‐ and outflow, an ostium scope that provides characteristics of the flow profile close to the ostium and a local scope for a detailed exploration of the flow in the parent vessel and the aneurysm. The approach was applied to five representative datasets, including measured and simulated blood flow. Informal interviews with two board‐certified radiologists confirmed the usefulness of the provided exploration tools and delivered input for the integration of the ostium‐based flow analysis into the overall exploration workflow.
Assisted Descriptor Selection Based on Visual Comparative Data Analysis
Authors: Sebastian Bremm, Tatiana von Landesberger, Jürgen Bernard, Tobias Schreck
Published at EuroVis, 2011

Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have been proposed. In most instances, they require data labels and often are black box approaches. Non‐expert users have difficulties to comprehend the coherency of input, parameters, and output of these algorithms. Alternative approaches, interactive systems for visual feature selection, overburden the user with an overwhelming set of options and data views. Therefore, it is essential to offer the users a guidance in this analytical process. In this paper, we present a novel system for data description selection, which facilitates the user's access to the data analysis process. As finding of suitable data description consists of several steps, we support the user with guidance. Our system combines automatic data analysis with interactive visualizations. By this, the system provides a recommendation for suitable data descriptor selections. It supports the comparison of data descriptors with differing dimensionality for unlabeled data. We propose specialized scores and interactive views for descriptor comparison. The visualization techniques are scatterplot‐based and grid‐based. For the latter case, we apply Self‐Organizing Maps as adaptive grids which are well suited for large multi‐dimensional data sets. As an example, we demonstrate the usability of our system on a real‐world biochemical application.
Automatic Registration of Multi-Projector Domes Using a Single Uncalibrated Camera
Authors: Behzad Sajadi, Aditi Majumder
Published at EuroVis, 2011

In this paper we present a novel technique for easily calibrating multiple casually aligned projectors on spherical domes using a single uncalibrated camera. Using the prior knowledge of the display surface being a dome, we can estimate the camera intrinsic and extrinsic parameters and the projector to display surface correspondences automatically using a set of images. These images include the image of the dome itself and a projected pattern from each projector. Using these correspondences we can register images from the multiple projectors on the dome. Further, we can register displays which are not entirely visible in a single camera view using multiple pan and tilted views of an uncalibrated camera making our method suitable for displays of different size and resolution. We can register images from any arbitrary viewpoint making it appropriate for a single head‐tracked user in a 3D visualization system. Also, we can use several cartographic mapping techniques to register images in a manner that is appropriate for multi‐user visualization.Domes are known to produce a tremendous sense of immersion and presence in visualization systems. Yet, till date, there exists no easy way to register multiple projectors on a dome to create a high‐resolution realistic visualizations. To the best of our knowledge, this is the first method that can achieve accurate geometric registration of multiple projectors on a dome simply and automatically using a single uncalibrated camera.
Comparison of Multiple Weighted Hierarchies: Visual Analytics for Microbe Community Profiling
Authors: Kasper Dinkla, Michel A. Westenberg, H. M. Timmerman, Sacha A. F. T. van Hijum, Jarke J. van Wijk
Published at EuroVis, 2011

We propose visual analytics techniques to support concurrent comparison of hundreds of cumulatively weighted instances of a single hierarchy. This includes a node‐link representation of the hierarchy where nodes depict the weights of all instances with high‐density heat maps that are grouped and aligned to ease cross‐referencing. Hierarchy exploration is facilitated by smoothly animated expansion and collapse of its branches. Detailed information about hierarchy structure, weights, and meta‐data is provided by secondary linked visualizations. These techniques have been implemented in a prototype tool, in which the computational analysis concerns have been strictly separated from the visualization concerns. The analysis algorithms are extensible via a script engine. We discuss the effectiveness of our techniques for the visual analytic process of microbe community profiling experts.
Complete Tensor Field Topology on 2D Triangulated Manifolds embedded in 3D
Authors: Cornelia Auer, Ingrid Hotz
Published at EuroVis, 2011

This paper is concerned with the extraction of the surface topology of tensor fields on 2D triangulated manifolds embedded in 3D. In scientific visualization topology is a meaningful instrument to get a hold on the structure of a given dataset. Due to the discontinuity of tensor fields on a piecewise planar domain, standard topology extraction methods result in an incomplete topological skeleton. In particular with regard to the high computational costs of the extraction this is not satisfactory. This paper provides a method for topology extraction of tensor fields that leads to complete results. The core idea is to include the locations of discontinuity into the topological analysis. For this purpose the model of continuous transition bridges is introduced, which allows to capture the entire topology on the discontinuous field. The proposed method is applied to piecewise linear three‐dimensional tensor fields defined on the vertices of the triangulation and for piecewise constant two or three‐dimensional tensor fields given per triangle, e.g. rate of strain tensors of piecewise linear flow fields.
Curve Density Estimates
Authors: Ove Daae Lampe, Helwig Hauser
Published at EuroVis, 2011

In this work, we present a technique based on kernel density estimation for rendering smooth curves. With this approach, we produce uncluttered and expressive pictures, revealing frequency information about one, or, multiple curves, independent of the level of detail in the data, the zoom level, and the screen resolution. With this technique the visual representation scales seamlessly from an exact line drawing, (for low‐frequency/low‐complexity curves) to a probability density estimate for more intricate situations. This scale‐independence facilitates displays based on non‐linear time, enabling high‐resolution accuracy of recent values, accompanied by long historical series for context. We demonstrate the functionality of this approach in the context of prediction scenarios and in the context of streaming data.
Depth of Field Effects for Interactive Direct Volume Rendering
Authors: Mathias Schott, Andre Vincent Pascal Grosset, Tobias Martin, Vincent Pegoraro, Sean T. Smith, Charles D. Hansen
Published at EuroVis, 2011

In this paper, a method for interactive direct volume rendering is proposed for computing depth of field effects, which previously were shown to aid observers in depth and size perception of synthetically generated images. The presented technique extends those benefits to volume rendering visualizations of 3D scalar fields from CT/MRI scanners or numerical simulations. It is based on incremental filtering and as such does not depend on any pre‐computation, thus allowing interactive explorations of volumetric data sets via on‐the‐fly editing of the shading model parameters or (multi‐dimensional) transfer functions.
Dynamic Insets for Context-Aware Graph Navigation
Authors: Sohaib Ghani, Nathalie Henry Riche, Niklas Elmqvist
Published at EuroVis, 2011

Maintaining both overview and detail while navigating in graphs, such as road networks, airline route maps, or social networks, is difficult, especially when targets of interest are located far apart. We present a navigation technique called Dynamic Insets that provides context awareness for graph navigation. Dynamic insets utilize the topological structure of the network to draw a visual inset for off‐screen nodes that shows a portion of the surrounding area for links leaving the edge of the screen. We implement dynamic insets for general graph navigation as well as geographical maps. We also present results from a set of user studies that show that our technique is more efficient than most of the existing techniques for graph navigation in different networks.
Efficient Parallel Vectors Feature Extraction from Higher-Order Data
Authors: Christian Azambuja Pagot, Daniel K. Osmari, Filip Sadlo, Daniel Weiskopf, Thomas Ertl, João Comba
Published at EuroVis, 2011

The parallel vectors (PV) operator is a feature extraction approach for defining line‐type features such as creases (ridges and valleys) in scalar fields, as well as separation, attachment, and vortex core lines in vector fields. In this work, we extend PV feature extraction to higher‐order data represented by piecewise analytical functions defined over grid cells. The extraction uses PV in two distinct stages. First, seed points on the feature lines are placed by evaluating the inclusion form of the PV criterion with reduced affine arithmetic. Second, a feature flow field is derived from the higher‐order PV expression where the features can be extracted as streamlines starting at the seeds. Our approach allows for guaranteed bounds regarding accuracy with respect to existence, position, and topology of the features obtained. The method is suitable for parallel implementation and we present results obtained with our GPU‐based prototype. We apply our method to higher‐order data obtained from discontinuous Galerkin fluid simulations.
Energy-scale Aware Feature Extraction for Flow Visualization
Authors: Armin Pobitzer, M. Tutkun, Øyvind Andreassen, Raphael Fuchs, Ronald Peikert, Helwig Hauser
Published at EuroVis, 2011

In the visualization of flow simulation data, feature detectors often tend to result in overly rich response, making some sort of filtering or simplification necessary to convey meaningful images. In this paper we present an approach that builds upon a decomposition of the flow field according to dynamical importance of different scales of motion energy. Focusing on the high‐energy scales leads to a reduction of the flow field while retaining the underlying physical process. The presented method acknowledges the intrinsic structures of the flow according to its energy and therefore allows to focus on the energetically most interesting aspects of the flow. Our analysis shows that this approach can be used for methods based on both local feature extraction and particle integration and we provide a discussion of the error caused by the approximation. Finally, we illustrate the use of the proposed approach for both a local and a global feature detector and in the context of numerical flow simulations.
Evaluation of the Visibility of Vessel Movement Features in Trajectory Visualizations
Authors: Niels Willems, Huub van de Wetering, Jarke J. van Wijk
Published at EuroVis, 2011

There are many visualizations that show the trajectory of a moving object to obtain insights in its behavior. In this user study, we test the performance of three of these visualizations with respect to three movement features that occur in vessel behavior. Our goal is to compare the recently presented vessel density by Willems et al. [WvdWvW09] with well‐known trajectory visualizations such as an animation of moving dots and the space‐time cube. We test these visualizations with common maritime analysis tasks by investigating the ability of users to find stopping objects, fast moving objects, and estimate the busiest routes in vessel trajectories. We test the robustness of the visualizations towards scalability and the influence of complex trajectories using small‐scale synthetic data sets. The performance is measured in terms of correctness and response time. The user test shows that each visualization type excels for correctness for a specific movement feature. Vessel density performs best for finding stopping objects, but does not perform significantly less than the remaining visualizations for the other features. Therefore, vessel density is a nice extension in the toolkit for analyzing trajectories of moving objects, in particular for vessel movements, since stops can be visualized better, and the performance for comparing lanes and finding fast movers is at a similar level as established trajectory visualizations.
Exploring Collections of Tagged Text for Literary Scholarship
Authors: Michael Correll, Michael Witmore, Michael Gleicher
Published at EuroVis, 2011

Modern literary scholars must combine access to vast collections of text with the traditional close analysis of their field. In this paper, we discuss the design and development of tools to support this work. Based on analysis of the needs of literary scholars, we constructed a suite of visualization tools for the analysis of large collections of tagged text (i.e. text where one or more words have been annotated as belonging to a specific category). These tools unite the aspects of the scholars’ work: large scale overview tools help to identify corpus‐wide statistical patterns while fine scale analysis tools assist in finding specific details that support these observations. We designed visual tools that support and integrate these levels of analysis. The result is the first tool suite that can support the multilevel text analysis performed by scholars, combining standard visual elements with novel methods for selecting individual texts and identifying represenative passages in them.
Fast Extraction of High-quality Crease Surfaces for Visual Analysis
Authors: Samer S. Barakat, Nathan Andrysco, Xavier Tricoche
Published at EuroVis, 2011

We present a novel algorithm for the efficient extraction and visualization of high‐quality ridge and valley surfaces from numerical datasets. Despite their rapidly increasing popularity in visualization, these so‐called crease surfaces remain challenging to compute owing to their strongly nonlinear and non‐orientable nature, and their complex boundaries. In this context, existing meshing techniques require an extremely dense sampling that is computationally prohibitive. Our proposed solution intertwines sampling and meshing steps to yield an accurate approximation of the underlying surfaces while ensuring the geometric quality of the resulting mesh. Using the computation power of the GPU, we propose a fast, parallel method for sampling. Additionally, we present a new front propagation meshing strategy that leverages CPU multiprocessing. Results are shown for synthetic, medical and fluid dynamics datasets.
Flowstrates: An Approach for Visual Exploration of Temporal Origin-Destination Data
Authors: Ilya Boyandin, Enrico Bertini, Peter Bak, Denis Lalanne
Published at EuroVis, 2011

Many origin‐destination datasets have become available in the recent years, e.g. flows of people, animals, money, material, or network traffic between pairs of locations, but appropriate techniques for their exploration still have to be developed. Especially, supporting the analysis of datasets with a temporal dimension remains a significant challenge. Many techniques for the exploration of spatio‐temporal data have been developed, but they prove to be only of limited use when applied to temporal origin‐destination datasets. We present Flowstrates, a new interactive visualization approach in which the origins and the destinations of the flows are displayed in two separate maps, and the changes over time of the flow magnitudes are represented in a separate heatmap view in the middle. This allows the users to perform spatial visual queries, focusing on different regions of interest for the origins and destinations, and to analyze the changes over time provided with the means of flow ordering, filtering and aggregation in the heatmap. In this paper, we discuss the challenges associated with the visualization of temporal origin‐destination data, introduce our solution, and present several usage scenarios showing how the tool we have developed supports them.
Illustrative Molecular Visualization with Continuous Abstraction
Authors: Matthew van der Zwan, Wouter Lueks, Henk Bekker, Tobias Isenberg 0001
Published at EuroVis, 2011

Molecular systems may be visualized with various degrees of structural abstraction, support of spatial perception, and ‘illustrativeness.’ In this work we propose and realize methods to create seamless transformations that allow us to affect and change each of these three parameters individually. The resulting transitions give viewers a dedicated control of abstraction in illustrative molecular visualization and, consequently, allow them to seamlessly explore the resulting abstraction space for obtaining a fundamental understanding of molecular systems. We show example visualizations created with our approach and report informal feedback on our technique from domain experts.
ImPrEd: An Improved Force-Directed Algorithm that Prevents Nodes from Crossing Edges
Authors: Paolo Simonetto, Daniel Archambault, David Auber, Romain Bourqui
Published at EuroVis, 2011

PrEd [Ber00] is a force‐directed algorithm that improves the existing layout of a graph while preserving its edge crossing properties. The algorithm has a number of applications including: improving the layouts of planar graph drawing algorithms, interacting with a graph layout, and drawing Euler‐like diagrams. The algorithm ensures that nodes do not cross edges during its execution. However, PrEd can be computationally expensive and overly‐restrictive in terms of node movement.In this paper, we introduce ImPrEd: an improved version of PrEd that overcomes some of its limitations and widens its range of applicability. ImPrEd also adds features such as flexible or crossable edges, allowing for greater control over the output. Flexible edges, in particular, can improve the distribution of graph elements and the angular resolution of the input graph. They can also be used to generate Euler diagrams with smooth boundaries. As flexible edges increase data set size, we experience an execution/drawing quality trade off. However, when flexible edges are not used, ImPrEdproves to be consistently faster than PrEd.
In-situ Sampling of a Large-Scale Particle Simulation for Interactive Visualization and Analysis
Authors: Jonathan Woodring, James P. Ahrens, J. Figg, Joanne Wendelberger, Salman Habib, Katrin Heitmann
Published at EuroVis, 2011

We describe a simulation‐time random sampling of a large‐scale particle simulation, the RoadRunner Universe MC3 cosmological simulation, for interactive post‐analysis and visualization. Simulation data generation rates will continue to be far greater than storage bandwidth rates by many orders of magnitude. This implies that only a very small fraction of data generated by a simulation can ever be stored and subsequently post‐analyzed. The limiting factors in this situation are similar to the problem in many population surveys: there aren't enough human resources to query a large population. To cope with the lack of resources, statistical sampling techniques are used to create a representative data set of a large population. Following this analogy, we propose to store a simulation‐time random sampling of the particle data for post‐analysis, with level‐of‐detail organization, to cope with the bottlenecks. A sample is stored directly from the simulation in a level‐of‐detail format for post‐visualization and analysis, which amortizes the cost of post‐processing and reduces workflow time. Additionally by sampling during the simulation, we are able to analyze the entire particle population to record full population statistics and quantify sample error.