A Snapshot of Current Trends in Visualization
Guest Editors’ Introduction • Theresa-Marie Rhyne and Min Chen • February 2017
Translations by Osvaldo Perez and Tiejun Huang
Listen to the Guest Editors' Introduction
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Visualization is the study of the transformation of data to visual representations. These visual elements are then used to gain insight into and from the data. In the 30 years since the landmark "Visualization in Scientific Computing” report in which the National Science Foundation Panel on Graphics, Image Processing, and Workstations outlined a vision for developing computer-generated visualization as a scientific field, the field has expanded to encompass three major subfields: scientific visualization, information visualization, and visual analytics. It also includes many domain-specific areas, such as geo-information visualization, biological data visualization, and software visualization.
This February 2017 Computing Now theme presents the highlights of last year’s IEEE VIS, a flagship multi-conference in the visualization field. The five featured articles represent the best visualization research from 2016. A related video from Kitware discusses challenges in scientific visualization software development. Together, they showcase novel algorithms, the latest visualization system additions and extensions, exciting advancements in visualization theory, and significant real-world applications.
IEEE VIS 2016
Held in Baltimore in October, IEEE VIS 2016 consisted of the following conferences:
- IEEE Visual Analytics Science and Technology (VAST)
- IEEE Information Visualization (InfoVis)
- IEEE Scientific Visualization (SciVis)
The week-long event leveraged a close partnership with IEEE Transactions on Visualization and Computer Graphics (TVCG) and IEEE Computer Graphics & Applications (CG&A); authors of 33 articles in these two publications presented their work, and 100 high-quality papers were accepted and published directly in TVCG.
The first three articles were published in TVCG and received the best paper awards during IEEE VIS 2016. The final two are inspirational articles from CG&A.
In “An Analysis of Machine- and Human-Analytics in Classification,” Gary K.L. Tam, Vivek Kothari, and Min Chen present an intriguing theoretic analysis of two case studies in which classification models developed with human soft knowledge performed better than models derived entirely from automated machine-learning. Using information-theoretic measurement, they estimate the quantities (in bits) of the human soft knowledge that were available using visual analytics in the model development processes. They conclude that developers should not ignore such soft knowledge, because it provides an abundance of extra information.
Extracting topological structures from data provides mathematical abstractions that enable advanced data analysis, exploration, and visualization. In “Jacobi Fiber Surfaces for Bivariate Reeb Space Computation,” Julien Tierny and Hamish Carr describe a novel algorithm for computing such a topological abstraction, called the Reeb space. Whereas traditional topology-based methods in visualization deal with data defined with univariate scalar functions, this algorithm enables a practical extension to bivariate datasets.
An interactive visualization display requires an articulated specification to update the visualization dynamically in response to streaming data and user interaction. In “Vega-Lite: A Grammar of Interactive Graphics,” Arvind Satyanarayan and his colleagues replace conventional programming languages and visualization APIs with a grammar designed specifically for graphics and interaction. They have released Vega-Lite as an open-source system that is now available for download here.
Kitware’s Visualization Toolkit (VTK) is an open-source software system for 3D computer graphics, image processing, and visualization that has benefited thousands of projects over the past two decades. Kenneth Moreland and his colleagues describe the development of VTK-m in “VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures.” Designed to address increasing demands related to very large datasets and parallelism in high-performance computing, VTK-m enables visualization software transformation from VTK to emerging processor architectures with fine-grained concurrency. VTK-m will be integrated into existing visualization tools, such as VTK, ParaView, and VisIt, to improve their performance on multi- and many-core devices.
Having now reached nearly every discipline, visualization applications can significantly impact everyday life. “A Decision-Support System for Sustainable Water Distribution System Planning” describes one such application: a decision-support system for expert users in urban water and waste management. Alina Freund and her colleagues explain that, using interactive visualization, these experts can explore options when preparing water resource management plans, as well as create effective visualizations for conveying meaningful information to decision makers and other stakeholders.
Kitware’s Patrick O’Leary presents the current challenges in supporting scientific data visualization on high-end heterogeneous computer architectures.
The Industry Perspective
This month’s video discusses the latest efforts to enable parallelism for high-performance computing in scientific visualization software. Patrick O’Leary, the assistant director of scientific computing at Kitware, presents the current challenges in supporting scientific data visualization on high-end heterogeneous computer architectures. He reviews advances in VTK, ParaView, and VTK-m, specifically highlighting how Kitware’s software solutions target emerging exascale computing environments.
We hope you enjoy the articles and video in this snapshot of current visualization trends, and we encourage you to follow further visualization developments through TVCG and CG&A.
Theresa-Marie Rhyne is an independent visualization consultant. She is the Visualization Viewpoints department editor for IEEE Computer Graphics and Applications and a member of the Computing Now advisory board. Contact her at email@example.com.
Min Chen is a professor of scientific visualization in the Oxford e-Research Centre at the University of Oxford, UK. He was an associate editor-in-chief of IEEE Transactions on Visualization and Computer Graphics from 2011 to 2014. Contact him at firstname.lastname@example.org.