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Techniques for Edge Stratification of Complex Graph Drawings
Affiliation:1. Dipartimento di Ingegneria, Università degli Studi di Perugia, Italy;2. University of Crete and Institute of Computer Science-FORTH, Greece;1. Università di Bari Aldo Moro, Dipartimento di Informatica, Via Orabona 4, 70125 Bari, Italy;2. Politecnico di Milano, Dipartimento di Elettronica e Informazione, Via Ponzio 34/5, 20133 Milano, Italy;1. Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China;2. Computer & Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA;1. Laboratory LIIAN/Department of Computer Science, Faculty of Science, BP 1796 Fes-atlas 30000, Morocco;2. Laboratory LESSI/Department of Physics, Faculty of Science, BP 1796, Fes-atlas 30000, Morocco;3. Department of Mathematics and Informatics, Multidisciplinary Faculty, BP 300, Selouane 62702, Nador, Morocco;1. University of Oviedo, Computer Science Department, C/Calvo Sotelo s/n, 33007 Oviedo, Spain;2. Alisys Software S.L.U., C/Menendez Valdes 40, 33201 Gijon, Spain;3. University of Oxford, Wolfson College, Linton Road, OX26UD Oxford, UK
Abstract:We propose an approach that allows a user (e.g., an analyst) to explore a layout produced by any graph drawing algorithm, in order to reduce the visual complexity and clarify its presentation. Our approach is based on stratifying the drawing into layers with desired properties; to this aim, heuristics are presented. The produced layers can be explored and combined by the user to gradually acquire details. We present a user study to test the effectiveness of our approach. Furthermore, we performed an experimental analysis on popular force-directed graph drawing algorithms, in order to evaluate what is the algorithm that produces the smallest number of layers and if there is any correlation between the number of crossings and the number of layers of a graph layout. The proposed approach is useful to explore graph layouts, as confirmed by the presented user study. Furthermore, interesting considerations arise from the experimental evaluation, in particular, our results suggest that the number of layers of a graph layout may represent a reliable measure of its visual complexity. The algorithms presented in this paper can be effectively applied to graph layouts with a few hundreds of edges and vertices. For larger drawings that contain lots of crossings, the time complexity of our algorithms grows quadratically in the number of edges and more efficient techniques need to be devised. The proposed approach takes as input a layout produced by any graph drawing algorithm, therefore it can be applied in a variety of application domains. Several research directions can be explored to extend our framework and to devise new visualization paradigms to effectively present stratified drawings.
Keywords:Network exploration  Human–computer interaction  Graph visualization  Information visualization
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