Seminar 15052 – Empirical Evaluation for Graph Drawing
Janet Siegmund Universität Passau Seminar 15052 – Empirical Evaluation for Graph Drawing • Janet Siegmund • Software Product-Line Group Janet Siegmund Software Product-Line Group Ariane-V Rocket $370 mio Janet Siegmund Software Product-Line Group Consistent use of background colors can improve program comprehension Confounding factors for program comprehension Questionnaire to measure programming experience Janet Siegmund Software Product-Line Group Differences between expert and novice program comprehension Automatic extraction of collaboration networks of developers Understanding programmers' brains with functional magnetic resonance imaging (fMRI) Janet Siegmund Software Product-Line Group Bettina Speckmann TU Eindhoven Seminar 15052 – Empirical Evaluation for Graph Drawing Algorithms for geovisualization and automated cartography Bettina Speckmann TU Eindhoven Curved Schematization Area preserving circular arcs Bézier curves circular arcs – different styles – degree of curviness User study Aesthetics Recognizability Simplicity Matthias F. Stallmann North Carolina State University Seminar 15052 – Empirical Evaluation for Graph Drawing Dagstuhl 15052 Introduction Matthias (Matt) Stallmann spent first 7 years in Bad Nauheim, Hessen last 40 at NCSU, Raleigh, NC father grew up in Königsberg Is Computer Science a Science? Challenges: • implementation takes time • need infrastructure • too many variables • what to measure • inconclusive? Observation Theory Analysis Experiments Random initial arrangements, in parallel Crossing minimization in layered graphs, for example. No communication get optimum on many “large” instances (~300 nodes, edges) using dfs+mod_bary+sifting Best different initial arrangements (e.g., 1024) - - - - expected solution quality probability of optimum or close to it better to randomize input or heuristic? better to run longer or use more parallelism? Bottleneck crossing minimization total crossings = 44 (optimum) one edge has 9 crossings total crossings = 57 no edge has more than 5 crossings Application to crosstalk/delay in circuits, not much is known ILP, SDP? Good known heuristics Michael Stoffel Universität Konstanz Seminar 15052 – Empirical Evaluation for Graph Drawing Michael Stoffel University of Konstanz Chair of Political Methodology Some other projects … MP incentives to cater to party vs. constituency EU spending efficiency subject to local and national gov’t interests Dorothea Wagner KIT - Karlsruher Institut für Technologie Seminar 15052 – Empirical Evaluation for Graph Drawing Dorothea Wagner Algorithm Engineering Route Planning me peri nt Ex Analyze Design Algorithmics Implement Graph Clustering Graph Drawing Social Network Analysis Sensor Networks Energy Networks ... 1 Dorothea Wagner – Dagstuhl 2015 Institute of Theoretical Informatics Algorithmics Group Route Planning fast shortest path computations (on-board and off-board) practical applications (Google, Microsoft, Nokia, telenav, ...) time dependence and dynamic traffic data flexible objectives (e.g. , travel time vs. cost) and constraints (e.g. , vehicle size, weight, toll roads) public transport multimodal route planning alternative routes intelligent point-of-interest search theory Dorothea Wagner – Dagstuhl 2015 Institute of Theoretical Informatics Algorithmics Group Graph Clustering network analysis and exploration (social, biological, technical, ...) compute densely connected subgraphs (clusters) = evaluate structure and function of clusters new cluster G0 Dorothea Wagner – Dagstuhl 2015 G1 dynamic networks temporal tracing of clusters G2 Institute of Theoretical Informatics Algorithmics Group Graph Drawing algorithms for visualizing graphs in the plane applications: sociology, biology, UML-diagrams, ... examples of our research: constrained planar graph drawings (e.g., point set embedding, extending partial drawings) alternative drawing conventions argument maps + Dorothea Wagner – Dagstuhl 2015 ? Institute of Theoretical Informatics Algorithmics Group Alexander Wolff Universität Würzburg Seminar 15052 – Empirical Evaluation for Graph Drawing alexander.wolff @ informatik . uni-wuerzburg . de Drawing metro maps [with Martin2 , Herman, Max, GD’12] alexander.wolff @ informatik . uni-wuerzburg . de Drawing metro maps Boundary labeling [with Martin2 , Herman, Max, GD’12] [with Michael, Antonis, Michalis, Andr´ e,... GD’04, WADS’13, GD’14] alexander.wolff @ informatik . uni-wuerzburg . de Drawing metro maps Boundary labeling [with Martin2 , Herman, Max, GD’12] [with Michael, Antonis, Michalis, Andr´ e,... GD’04, WADS’13, GD’14] todonotes.sty alexander.wolff @ informatik . uni-wuerzburg . de Drawing metro maps [with Martin2 , Herman, Max, GD’12] [with Michael, Antonis, Michalis, Andr´ e,... GD’04, WADS’13, GD’14] Boundary labeling luatodonotes.sty Kai Xu Middlesex University Seminar 15052 – Empirical Evaluation for Graph Drawing Kai Xu Lecturer, London Bachelor, Shanghai PhD, Brisbane Research Scientist, Hobart & Canberra Postdoc, Sydney User Study – Curved Edges (InfoVis 2012) Making Sense of Graphs (InfoVis 2013) How to Evaluate? How to Evaluate Dense (and Large) Graphs? • What is the salient information? • Connectivity? • Structure (such as clustering)? • Shape? • How to evaluate? End Seminar 15052 – Empirical Evaluation for Graph Drawing
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