| 61. |
- Elmqvist, Niklas, 1977, et al.
(författare)
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Causality Visualization Using Animated Growing Polygons
- 2003
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Ingår i: Proceedings - IEEE Symposium on Information Visualization, INFO VIS. - 1522-404X. - 0780381548 ; , s. 189-196
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Konferensbidrag (refereegranskat)abstract
- We present Growing Polygons, a novel visualization technique for the graphical representation of causal relations and information flow in a system of interacting processes. Using this method, individual processes are displayed as partitioned polygons with color-coded segments showing dependencies to other processes. The entire visualization is also animated to communicate the dynamic execution of the system to the user. The results from a comparative user study of the method show that the Growing Polygons technique is significantly more efficient than the traditional Hasse diagram visualization for analysis tasks related to deducing information flow in a system for both small and large executions. Furthermore, our findings indicate that the correctness when solving causality tasks is significantly improved using our method. In addition, the subjective ratings of the users rank the method as superior in all regards, including usability, efficiency, and enjoyability.
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| 62. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
CiteWiz: a tool for the visualization of scientific citation networks
- 2007
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Ingår i: Information Visualization. - 1473-8716 .- 1473-8724. ; 6:3, s. 215-232
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Tidskriftsartikel (refereegranskat)abstract
- We present CiteWiz, an extensible framework for visualization of scientific citation networks. The system is based on a taxonomy of citation database usage for researchers, and provides a timeline visualization for overviews and an influence visualization for detailed views. The timeline displays the general chronology and importance of authors and articles in a citation database, whereas the influence visualization is implemented using the Growing Polygons technique, suitably modified to the context of browsing citation data. Using the latter technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent–child visualization and suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. We also provide an interactive concept map for keywords and co-authorship using a basic force-directed graph layout scheme. A formal user study indicates that CiteWiz is significantly more efficient than traditional database interfaces for high-level analysis tasks relating to influence and overviews, and equally efficient for low-level tasks such as finding a paper and correlating bibliographical data.
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| 63. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
CiteWiz: A Tool for the Visualization of Scientific Citation Networks
- 2004
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The management of citation data for scientific articles is part of everyday life for a researcher. In this paper, we present CiteWiz, an extensible framework for visualization of scientific networks. The system is based on a taxonomy of citation database usage for researchers, and uses the Growing Polygons causality visualization technique, suitably modified to the context of citation data. Using this technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent-child visualization, color assignment, as well as suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. Furthermore, the tool includes a static timeline visualization for overviewing the causality and importance of authors and articles in a citation database. Informal pilot studies with active researchers indicate that CiteWiz is useful for a wide range of scientific activities, and could well become a standard tool in their everyday work.
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| 64. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
DataMeadow: a visual canvas for analysis of large-scale multivariate data
- 2008
-
Ingår i: Information Visualization. - : SAGE Publications. - 1473-8716 .- 1473-8724. ; 7:1, s. 18-33
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Tidskriftsartikel (refereegranskat)abstract
- Supporting visual analytics of multiple large-scale multidimensional data sets requires a high degree of interactivity and user control beyond the conventional challenges of visualizing such data sets. We present the DataMeadow, a visual canvas providing rich interaction for constructing visual queries using graphical set representations called DataRoses. A DataRose is essentially a starplot of selected columns in a data set displayed as multivariate visualizations with dynamic query sliders integrated into each axis. The purpose of the DataMeadow is to allow users to create advanced visual queries by iteratively selecting and filtering into the multidimensional data. Furthermore, the canvas provides a clear history of the analysis that can be annotated to facilitate dissemination of analytical results to stakeholders. A powerful direct manipulation interface allows for selection, filtering, and creation of sets, subsets, and data dependencies. We have evaluated our system using a qualitative expert review involving two visualization researchers. Results from this review are favorable for the new method.
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| 65. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
DataMeadow: A Visual Canvas for Analysis of Large-Scale Multivariate Data
- 2007
-
Ingår i: Proceedings of the IEEE Symposium on Visual Analytics Science and Technology 2007 (VAST 2007). - 9781424416592 ; , s. 187-194
-
Konferensbidrag (refereegranskat)abstract
- Supporting visual analytics of multiple large-scale multidimensional datasets requires a high degree of interactivity and user control beyond the conventional challenges of visualizing such datasets. We present the DataMeadow, a visual canvas providing rich interaction for constructing visual queries using graphical set representations called DataRoses. A DataRose is essentially a starplot of selected columns in a dataset displayed as multivariate visualizations with dynamic query sliders integrated into each axis. The purpose of the DataMeadow is to allow users to create advanced visual queries by iteratively selecting and filtering into the multidimensional data. Furthermore, the canvas provides a clear history of the analysis that can be annotated to facilitate dissemination of analytical results to outsiders. Towards this end, the DataMeadow has a direct manipulation interface for selection, filtering, and creation of sets, subsets, and data dependencies using both simple and complex mouse gestures. We have evaluated our system using a qualitative expert review involving two researchers working in the area. Results from this review are favorable for our new method.
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| 66. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
Dynamic Transparency for 3D Visualization: Design and Evaluation
- 2009
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Ingår i: International Journal of Virtual Reality. - 1081-1451. ; 1:8, s. 65-78
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Tidskriftsartikel (refereegranskat)abstract
- Recent developments in occlusion management for 3D environments often involve the use of dynamic transparency, or “virtual X-ray vision”, to promote target discovery and access in complex 3D worlds. However, there are many different approach- es to achieving this effect and their actual utility for the user has yet to be evaluated. Furthermore, the introduction of semi- transparent surfaces adds additional visual complexity that may actually have a negative impact on task performance. In this paper, we report on an empirical user study investigating these human aspects of dynamic transparency. Our implementation of the technique is an image-space algorithm built using modern programmable shaders to achieve real-time performance and visually pleasing results. Results from the user study indicate that dynamic transparency provides superior performance for perceptual tasks in terms of both efficiency and correctness. Subjective ratings are also firmly in favor of the method.
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| 67. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
Employing Dynamic Transparency for 3D Occlusion Management: Design Issues and Evaluation
- 2007
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 1611-3349 .- 0302-9743. - 9783540747949 ; 4662, s. 532 - 545
-
Konferensbidrag (refereegranskat)abstract
- Recent developments in occlusion management for 3D environments often involve the use of dynamic transparency, or virtual “X-ray vision”, to promote target discovery and access in complex 3D worlds. However, there are many different approaches to achieving this effect and their actual utility for the user has yet to be evaluated. Furthermore, the introduction of semi-transparent surfaces adds additional visual complexity that may actually have a negative impact on task performance. In this paper, we report on an empirical user study comparing dynamic transparency to standard viewpoint controls. Our implementation of the technique is an image-space algorithm built using modern programmable shaders to achieve real-time performance and visually pleasing results. Results from the user study indicate that dynamic transparency is superior for perceptual tasks in terms of both efficiency and correctness.
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| 68. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
Evaluating motion constraints for 3D wayfinding in immersive and desktop virtual environments
- 2008
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Ingår i: Proceeding of the twenty-sixth annual CHI conference on Human factors in computing systems. - 9781605580111 ; , s. 1769-1778
-
Konferensbidrag (refereegranskat)abstract
- Motion constraints providing guidance for 3D navigation have recently been suggested as a way of offloading some of the cognitive effort of traversing complex 3D environments on a computer. We present findings from an evaluation of the benefits of this practice where users achieved significantly better results in memory recall and performance when given access to such a guidance method. The study was conducted on both standard desktop computers with mouse and keyboard, as well as on an immersive CAVE system. Interestingly, our results also show that the improvements were more dramatic for desktop users than for CAVE users, even outperforming the latter. Furthermore, the study indicates that allowing the users to retain local control over the navigation on the desktop platform helps them in familiarizing themselves with the 3D world.
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| 69. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
Growing Squares: Animated Visualization of Causal Relations
- 2003
-
Ingår i: Proceedings of the ACM 2003 Symposium on Software Visualization (SoftVis 2003), San Diego, 11-13 June 2003. - New York, NY, USA : ACM. - 9781581136425 ; , s. 17-26
-
Konferensbidrag (refereegranskat)abstract
- We present a novel information visualization technique for the graphical representation of causal relations, that is based on the metaphor of color pools spreading over time on a piece of paper. Messages between processes in the system affect the colors of their respective pool, making it possible to quickly see the influences each process has received. This technique, called Growing Squares, has been evaluated in a comparative user study and shown to be significantly faster and more efficient for sparse data sets than the traditional Hasse diagram visualization. Growing Squares were also more efficient for large data sets, but not significantly so. Test subjects clearly favored Growing Squares over old methods, naming the new technique easier, more efficient, and much more enjoyable to use.
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| 70. |
- Elmqvist, Niklas, 1977, et al.
(författare)
-
Growing Squares: Animated Visualization of Causal Relations
- 2002
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We present a novel information visualization technique for the graphical representation of causal relations, that is based on the metaphor of color pools spreading over time on a piece of paper. Messages between processes in the system affect the colors of their respective pool, making it possible to quickly see the influences each process has received. This technique, called Growing Squares, has been evaluated in a comparative user study and shown to be significantly faster and more efficient for sparse data sets than the traditional Hasse diagram visualization. Growing Squares were also more efficient for large data sets, but not significantly so. Test subjects clearly favored Growing Squares over old methods, naming the new technique easier, more efficient, and much more enjoyable to use.
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