Visual Representations

Görg, Carsten; Pohl, Mathias; Qeli, Ermir; Xu, Kai

doi:10.1007/978-3-540-71949-6_4

Cited by 20 publications

(16 citation statements)

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“…These range from the early work by Purchase et al [26] on the effectiveness of graph drawing aesthetics to the more recent work on 3D graphs [32], visual representation of directed edges [18,19], and readability of dynamic graphs [2]. Please refer to a recent survey [14] for more details. In most of these studies, users were asked to perform graph-related task(s) on drawings produced by different visualization techniques.…”

Section: Graph Visualization Evaluationsmentioning

confidence: 99%

A User Study on Curved Edges in Graph Visualization

Rooney

Passmore

et al. 2012

IEEE Trans. Visual. Comput. Graphics

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Abstract-Recently there has been increasing research interest in displaying graphs with curved edges to produce more readable visualizations. While there are several automatic techniques, little has been done to evaluate their effectiveness empirically. In this paper we present two experiments studying the impact of edge curvature on graph readability. The goal is to understand the advantages and disadvantages of using curved edges for common graph tasks compared to straight line segments, which are the conventional choice for showing edges in node-link diagrams. We included several edge variations: straight edges, edges with different curvature levels, and mixed straight and curved edges. During the experiments, participants were asked to complete network tasks including determination of connectivity, shortest path, node degree, and common neighbors. We also asked the participants to provide subjective ratings of the aesthetics of different edge types. The results show significant performance differences between the straight and curved edges and clear distinctions between variations of curved edges.

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Section: Graph Visualization Evaluationsmentioning

confidence: 99%

A User Study on Curved Edges in Graph Visualization

Rooney

Passmore

et al. 2012

IEEE Trans. Visual. Comput. Graphics

Self Cite

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“…Instead of integrating it into the main window, we decided to use a multiple views approach that is a widely used technique to visualize different kind of data simultaneously. This method provides the possibility of choosing the most suitable visualization technique for a specific view and data set [7]. Guided by these ideas we added a separate interactive diagram placed at the right upper corner in a tab, called aggregated links view, to present these statistical data.…”

Section: Aggregated Links Viewmentioning

confidence: 99%

Guiding the interactive exploration of metabolic pathway interconnections

Jusufi

Klukas

Kerren

et al. 2011

Information Visualization

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Abstract-Approaches to investigate biological processes have been of strong interest in the last years and are in the focus of several research areas, especially Systems Biology. Biochemical networks are very important for such a comprehensive understanding of living beings. Drawings of these networks are often visually overloaded and do not scale. A common solution to deal with this complexity is to divide the complete network, e.g., the metabolism, into a large set of single pathways that are hierarchically structured. If those pathways are visualized, this strategy generates additional navigation and exploration problems as the user looses the context within the complete network. In this paper, we present a general solution of this problem of visualizing interconnected pathways and discuss it in context of biochemical networks. Our new visualization approach supports the analyst to get an overview to related pathways if he/she is working within a particular pathway of interest. By using glyphs, brushing, and topological information of the related pathways, our interactive visualization tool is able to intuitively guide the exploration and navigation process, and thus the analysis processes too. To deal with real data and current networks, our tool has been implemented as plugin for the VANTED system.

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“…Furthermore, one has to consider that the attributes involved may belong to various types of data. Each data type needs specific requirements for its visual representation [9]. The challenge here lies in finding a harmonic combination of visual representations for mixtures of different data types.…”

Section: Visualization Of Multiple Attributesmentioning

confidence: 99%

“…A possible solution lies in the use of so-called preattentive features [9]. A preattentive feature is a visual property of a picture or drawing that can be very rapidly and accurately detected by the low-level human visual system.…”

Section: Visualization Of Multiple Attributesmentioning

confidence: 99%

On Open Problems in Biological Network Visualization

Albrecht

Kerren

Klein

et al. 2010

Lecture Notes in Computer Science

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Abstract. Much of the data generated and analyzed in the life sciences can be interpreted and represented by networks or graphs. Network analysis and visualization methods help in investigating them, and many universal as well as specialpurpose tools and libraries are available for this task. However, the two fields of graph drawing and network biology are still largely disconnected. Hence, visualization of biological networks does typically not apply state-of-the-art graph drawing techniques, and graph drawing tools do not respect the drawing conventions of the life science community.In this paper, we analyze some of the major problems arising in biological network visualization. We characterize these problems and formulate a series of open graph drawing problems. These use cases illustrate the need for efficient algorithms to present, explore, evaluate, and compare biological network data. For each use case, problems are discussed and possible solutions suggested.

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Visual Representations

Cited by 20 publications

References 0 publications

A User Study on Curved Edges in Graph Visualization

A User Study on Curved Edges in Graph Visualization

Guiding the interactive exploration of metabolic pathway interconnections

On Open Problems in Biological Network Visualization

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