, IEEE Computer Society
, IEEE Computer Society
, IEEE Computer Society
Pages: pp. 1381-1382
This special section of IEEE Transactions on Visualization and Computer Graphics ( TVCG) presents extended versions of four outstanding papers from the IEEE Pacific Visualization Symposium 2011 (PacificVis 2011) which was held in Hong Kong, China, on 1-4 March 2011. The objective of this annual symposium is to foster greater exchange between visualization researchers and practitioners, and to draw more researchers in the Asia-Pacific region to enter this fascinating and rapidly growing area of research. In only four years, it has become an established forum for visualization, as witnessed by the high quality and breadth of the papers published in the conference proceedings. PacificVis 2011 received 81 paper submissions from an international community. After a rigorous review process with at least four reviews per paper, 26 papers were finally accepted and presented in the conference. The four best papers from those presented were chosen by the guest editors based on the original reviews and the oral presentations. These papers were significantly extended for this special section and underwent a full journal review process. They cover four different topics in both scientific visualization and information visualization, and present visualization techniques for different data types like flow, multivariate data, textual corpora, and maps.
In “Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps,” Harsh Bhatia, Shreeraj Jadhav, Peer-Timo Bremer, Guoning Chen, Joshua A. Levine, Luis Gustavo Nonato, and Valerio Pascucci propose a new data structure called Edge Maps to more precisely represent vector fields defined on triangulated surfaces. The new representation can address two issues facing traditional flow visualizations: inconsistent views of a vector field caused by the numerical errors in computing streamlines through numerical integration, and the wrong perception of certainty by users as the errors are hidden in traditional techniques. Edge Maps encode the inflow/outflow behavior over the boundary of a triangle by mapping entry and exit points of flow paths on the edges of the triangle, and unavoidable spatial and temporal errors are explicitly stored in the representation. They demonstrate that a number of useful flow analysis and visualization tools can be developed based on Edge Maps. This work is one of the two best paper award winners at the conference.
In “Scalable Multivariate Volume Visualization and Analysis Based on Dimension Projection and Parallel Coordinates,” Hanqi Guo, He Xiao, and Xiaoru Yuan present a novel transfer function design interface for volumetric data sets with many independent parameters. An adaptive continuous Parallel Coordinates Plot (PCP) is used to visualize the data distribution on each dimension and possible correlations between neighboring dimensions while Multi-Dimensional Scaling (MDS) plots are used to reveal clusters in low dimensional space. By integrating PCP and MDS and leveraging computing parallelism, the new method enables effective and scalable visualization of large multivariate volume data.
Exploring large textual corpora is becoming a very important topic for the humanities, but also for a wider audience such as researchers. “WORDGRAPH: Keyword-in-Context Visualization for NETSPEAK's Wildcard Search,” by Patrick Riehmann, Henning Gruendl, Martin Potthast, Martin Trenkmann, Benno Stein, and Bernd Froehlich, allows visualizing a queried expression with wildcards as a graph showing all the contexts where the expression template is used. This is a challenge for visualization since the graph has to be readable and the authors use clever techniques to nicely lay out the resulting graph; this is also a challenge for building the graph in interactive time, and again, the authors explain how to preprocess textual corpora to achieve this speed. This work is another best paper award winner at the conference.
In “Visualizing Dynamic Data with Maps,” Daisuke Mashima, Stephen G. Kobourov, and Yifan Hu propose geographic maps as an interesting way to represent relational information. In such maps, entities are represented by countries and links between entities are represented by the corresponding countries sharing borders. The authors exploit geographic maps to visualize dynamics in large data sets. Their challenges are to preserve the viewer's mental map under the dynamics in the data, to ensure readability of each individual layout, and to effectively visualize on the map the changes happening over time. They address those challenges and present a system used to visualize music trends collected from an Internet radio and TV viewing trends from an IPTV service. They suggest that the geographic map metaphor can be an effective tool for a number of visualization needs.
As editors of this special section, we thank Ming Lin, the Editor-in-Chief, for the opportunity to present this work and the staff of TVCG for the outstanding support they have provided. We especially thank the anonymous reviewers for their invaluable contribution in enhancing the quality of the final papers. We look forward to future meetings of Pacific Visualization and encourage our colleagues to consider submitting their work to such meetings.
Giuseppe Di Battista