An Analysis of the Interplay and Mutual Benefits of Grounded Theory and Visualization.

Grounded theory (GT) is a research methodology that entails a systematic workflow for theory generation grounded on emergent data. In this paper, we juxtapose GT workflows with typical workflows in visualization and visual analytics (VIS), unveiling the characteristics shared by these workflows. We explore the research landscape of VIS to study where GT is applied to generate VIS theories, explicitly as well as implicitly.

Challenges and Opportunities in Data Visualization Education: A Call to Action.

This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge.

VisLitE: Visualization Literacy and Evaluation.

With the widespread advent of visualization techniques to convey complex data, visualization literacy (VL) is growing in importance. Two noteworthy facets of literacy are user understanding and the discovery of visual patterns with the help of graphical representations. The research literature on VL provides useful guidance and opportunities for further studies in this field.

RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses.

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more.

VIS30K: A Collection of Figures and Tables From IEEE Visualization Conference Publications.

We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation.

TransVis: Integrated Distant and Close Reading of Othello Translations.

Studying variation among time-evolved translations is a valuable research area for cultural heritage. Understanding how and why translations vary reveals cultural, ideological, and even political influences on literature as well as author relations. In this article, we introduce a novel integrated visual application to support distant and close reading of a collection of Othello translations.

AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs.

Glyphs representing complex behavior provide a useful and common means of visualizing multivariate data. However, due to their complex shape, overlapping, and occlusion of glyphs is a common and prominent limitation. This limits the number of discreet data tuples that can be displayed in a given image.

A Provenance Task Abstraction Framework.

Visual analytics tools integrate provenance recording to externalize analytic processes or user insights. Provenance can be captured on varying levels of detail, and in turn activities can be characterized from different granularities. However, current approaches do not support inferring activities that can only be characterized across multiple levels of provenance.

Molecular Graphics: Bridging Structural Biologists and Computer Scientists.

Visualization of molecular structures is one of the most common tasks carried out by structural biologists, typically using software, such as Chimera, COOT, PyMOL, or VMD. In this Perspective article, we outline how past developments in computer graphics and data visualization have expanded the understanding of biomolecular function, and we summarize recent advances that promise to further transform structural biology. We also highlight how progress in molecular graphics has been impeded by communication barriers between two communities: the computer scientists driving these advances, and the structural and computational biologists who stand to benefit.

Integral Curve Clustering and Simplification for Flow Visualization: A Comparative Evaluation.

Unsupervised clustering techniques have been widely applied to flow simulation data to alleviate clutter and occlusion in the resulting visualization. However, there is an absence of systematic guidelines for users to evaluate (both quantitatively and visually) the appropriate clustering technique and similarity measures for streamline and pathline curves. In this work, we provide an overview of a number of prevailing curve clustering techniques.

Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces.

Asymmetric tensor fields have found applications in many science and engineering domains, such as fluid dynamics. Recent advances in the visualization and analysis of 2D asymmetric tensor fields focus on pointwise analysis of the tensor field and effective visualization metaphors such as colors, glyphs, and hyperstreamlines. In this paper, we provide a novel multi-scale topological analysis framework for asymmetric tensor fields on surfaces.

Teaching Data Visualization as a Skill.

This paper explores the meaning of the term "skill" in the context of information (data) visualization and its place in the labor market. It examines the visualization skills and software competencies that are in high demand in industry today, and the ramifications for teaching Data Visualization for professional students in higher education.

Visual Analysis of Spatio-temporal Relations of Pairwise Attributes in Unsteady Flow.

Despite significant advances in the analysis and visualization of unsteady flow, the interpretation of it's behavior still remains a challenge. In this work, we focus on the linear correlation and non-linear dependency of different physical attributes of unsteady flows to aid their study from a new perspective. Specifically, we extend the existing spatial correlation quantification, i.

Smart Brushing for Parallel Coordinates.

The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges when using parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address these challenges.

Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold.

Three-dimensional symmetric tensor fields have a wide range of applications in solid and fluid mechanics. Recent advances in the (topological) analysis of 3D symmetric tensor fields focus on degenerate tensors which form curves. In this paper, we introduce a number of feature surfaces, such as neutral surfaces and traceless surfaces, into tensor field analysis, based on the notion of eigenvalue manifold.

Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in 'Daily Diary' tags.

Background: Smart tags attached to freely-roaming animals recording multiple parameters at infra-second rates are becoming commonplace, and are transforming our understanding of the way wild animals behave. Interpretation of such data is complex and currently limits the ability of biologists to realise the value of their recorded information.

Description: This work presents Framework4, an all-encompassing software suite which operates on smart sensor data to determine the 4 key elements considered pivotal for movement analysis from such tags (Endangered Species Res 4: 123-37, 2008).

Knowledge-Assisted Ranking: A Visual Analytic Application for Sports Event Data.

Organizing sports video data for performance analysis can be challenging, especially in cases involving multiple attributes and when the criteria for sorting frequently changes depending on the user's task. The proposed visual analytic system enables users to specify a sort requirement in a flexible manner without depending on specific knowledge about individual sort keys. The authors use regression techniques to train different analytical models for different types of sorting requirements and use visualization to facilitate knowledge discovery at different stages of the process.

Similarity measures for enhancing interactive streamline seeding.

Streamline seeding rakes are widely used in vector field visualization. We present new approaches for calculating similarity between integral curves (streamlines and pathlines). While others have used similarity distance measures, the computational expense involved with existing techniques is relatively high due to the vast number of euclidean distance tests, restricting interactivity and their use for streamline seeding rakes.

Angular histograms: frequency-based visualizations for large, high dimensional data.

Parallel coordinates is a popular and well-known multivariate data visualization technique. However, one of their inherent limitations has to do with the rendering of very large data sets. This often causes an overplotting problem and the goal of the visual information seeking mantra is hampered because of a cluttered overview and non-interactive update rates.

FoamVis: visualization of 2D foam simulation data.

Research in the field of complex fluids such as polymer solutions, particulate suspensions and foams studies how the flow of fluids with different material parameters changes as a result of various constraints. Surface Evolver, the standard solver software used to generate foam simulations, provides large, complex, time-dependent data sets with hundreds or thousands of individual bubbles and thousands of time steps. However this software has limited visualization capabilities, and no foam specific visualization software exists.

Asymmetric tensor field visualization for surfaces.

Asymmetric tensor field visualization can provide important insight into fluid flows and solid deformations. Existing techniques for asymmetric tensor fields focus on the analysis, and simply use evenly-spaced hyperstreamlines on surfaces following eigenvectors and dual-eigenvectors in the tensor field. In this paper, we describe a hybrid visualization technique in which hyperstreamlines and elliptical glyphs are used in real and complex domains, respectively.

Morse set classification and hierarchical refinement using Conley index.

Morse decomposition provides a numerically stable topological representation of vector fields that is crucial for their rigorous interpretation. However, Morse decomposition is not unique, and its granularity directly impacts its computational cost. In this paper, we propose an automatic refinement scheme to construct the Morse Connection Graph (MCG) of a given vector field in a hierarchical fashion.