Journal ArticleDOI
Visualization of structural information: automatic drawing of compound digraphs
Kozo Sugiyama,Kazuo Misue +1 more
- Vol. 21, Iss: 4, pp 876-892
TLDR
An automatic method for drawing compound digraphs that contain both inclusion edges and adjacency edges are presented, and a heuristic algorithm to generate readable diagrams is developed.Abstract:
An automatic method for drawing compound digraphs that contain both inclusion edges and adjacency edges are presented. In the method vertices are drawn as rectangles (areas for texts, images, etc.), inclusion edges by the geometric inclusion among the rectangles, and adjacency edges by arrows connecting them. Readability elements such as drawing conventions and rules are identified, and a heuristic algorithm to generate readable diagrams is developed. Several applications are shown to demonstrate the effectiveness of the algorithm. The utilization of curves to improve the quality of diagrams is investigated. A possible set of command primitives for progressively organizing structures within this graph formalism is discussed. The computational time for the applications shows that the algorithm achieves satisfactory performance. >read more
Citations
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Journal ArticleDOI
Graph visualization and navigation in information visualization: A survey
TL;DR: This is a survey on graph visualization and navigation techniques, as used in information visualization, which approaches the results of traditional graph drawing from a different perspective.
Journal ArticleDOI
External cognition: how do graphical representations work?
Mike Scaife,Yvonne Rogers +1 more
TL;DR: This analysis reveals a fragmented and poorly understood account of how graphical representations work, exposing a number of assumptions and fallacies, and proposes a new agenda for graphical representation research.
Journal ArticleDOI
Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data
TL;DR: This paper presents a new method for visualizing compound graphs based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together and discusses the results based on an informal evaluation provided by potential users of such visualizations.
Journal ArticleDOI
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow
Kanit Wongsuphasawat,Daniel Smilkov,James Wexler,Jimbo Wilson,Dandelion Mane,Doug Fritz,Dilip Krishnan,Fernanda B. Viégas,Martin Wattenberg +8 more
TL;DR: Overall, users find the TensorFlow Graph Visualizer useful for understanding, debugging, and sharing the structures of their models.
Journal ArticleDOI
Metrics for Graph Drawing Aesthetics
TL;DR: Formal metrics for measuring the aesthetic presence in a graph drawing for seven common aesthetic criteria, applicable to any graph drawing of anysize are presented.
References
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Book
The Design and Analysis of Computer Algorithms
Alfred V. Aho,John E. Hopcroft +1 more
TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.
Book
Graph Algorithms
TL;DR: A thoroughly revised second edition of Shimon Even's Graph Algorithms, with a foreword by Richard M. Karp and notes by Andrew V Goldberg, explains algorithms in a formal but simple language with a direct and intuitive presentation.
Journal ArticleDOI
On visual formalisms
TL;DR: The higraph, a general kind of diagramming object, forms a visual formalism of topological nature that is suited for a wide array of applications to databases, knowledge representation, and the behavioral specification of complex concurrent systems using the higraph-based language of statecharts.
Journal ArticleDOI
Methods for Visual Understanding of Hierarchical System Structures
TL;DR: Two kinds of new methods are developed to obtain effective representations of hierarchies automatically: theoretical and heuristic methods that determine the positions of vertices in two steps to improve the readability of drawings.