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Using Signposts for Navigation in Large Graphs
Author(s) -
May T.,
Steiger M.,
Davey J.,
Kohlhammer J.
Publication year - 2012
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2012.03091.x
Subject(s) - computer science , focus (optics) , visualization , graph , set (abstract data type) , context (archaeology) , theoretical computer science , representation (politics) , shortest path problem , node (physics) , artificial intelligence , geography , physics , archaeology , structural engineering , engineering , politics , law , political science , optics , programming language
In this paper we present a new Focus & Context technique for the exploration of large, abstract graphs. Most Focus & Context techniques present context in a visual way. In contrast, our technique uses a symbolic representation: while the focus is a set of visible nodes, labelled signposts provide cues for the context — off‐screen regions of the graph — and indicate the direction of the shortest path linking the visible nodes to these regions. We show how the regions are defined and how they are selected dynamically, depending on the visible nodes. To define the set of visible nodes we use an approach developed by van Ham and Perer that dynamically extracts a subgraph based on an initial focal node and a degree‐of‐interest function. This approach is extended to support multiple focal nodes. With the symbolic visualization, potentially interesting regions of a graph may be represented with a very small visual footprint. We conclude the paper with an initial user study to evaluate the effectiveness of the signposts for navigation tasks.