Selected Open Problems in Graph Drawing
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Drawing Graphs and Maps with Curves
Report from Dagstuhl Seminar 13151 Drawing Graphs and Maps with Curves Edited by Stephen Kobourov1, Martin Nöllenburg2, and Monique Teillaud3 1 University of Arizona – Tucson, US, [email protected] 2 KIT – Karlsruhe Institute of Technology, DE, [email protected] 3 INRIA Sophia Antipolis – Méditerranée, FR, [email protected] Abstract This report documents the program and the outcomes of Dagstuhl Seminar 13151 “Drawing Graphs and Maps with Curves”. The seminar brought together 34 researchers from different areas such as graph drawing, information visualization, computational geometry, and cartography. During the seminar we started with seven overview talks on the use of curves in the different communities represented in the seminar. Abstracts of these talks are collected in this report. Six working groups formed around open research problems related to the seminar topic and we report about their findings. Finally, the seminar was accompanied by the art exhibition Bending Reality: Where Arc and Science Meet with 40 exhibits contributed by the seminar participants. Seminar 07.–12. April, 2013 – www.dagstuhl.de/13151 1998 ACM Subject Classification I.3.5 Computational Geometry and Object Modeling, G.2.2 Graph Theory, F.2.2 Nonnumerical Algorithms and Problems Keywords and phrases graph drawing, information visualization, computational cartography, computational geometry Digital Object Identifier 10.4230/DagRep.3.4.34 Edited in cooperation with Benjamin Niedermann 1 Executive Summary Stephen Kobourov Martin Nöllenburg Monique Teillaud License Creative Commons BY 3.0 Unported license © Stephen Kobourov, Martin Nöllenburg, and Monique Teillaud Graphs and networks, maps and schematic map representations are frequently used in many fields of science, humanities and the arts. -
Algorithms for Graph Visualization Flow Methods: Orthogonal Layout
Algorithms for Graph Visualization Flow Methods: Orthogonal Layout INSTITUT FUR¨ THEORETISCHE INFORMATIK · FAKULTAT¨ FUR¨ INFORMATIK Tamara Mchedlidze 18.01.2018 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas ER diagram in OGDF UML diagram by Oracle Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas Aesthetic functions? ER diagram in OGDF UML diagram by Oracle Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 2 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen Orthogonal Layout • Edges consist of vertical and horizontal segments • Applied in many areas Aesthetic functions: • number of bends • length of edges • ER diagram in OGDF width, height, area • monotonicity of edges UML diagram by Oracle • ... Organigram of HS Limburg Circuit diagram by Jeff Atwood 2 - 3 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. Comput. 1987] V = fv1; v2; v3; v4g E = fv1v2; v1v3; v1v4; v2v3; v2v4g 3 - 1 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. Comput. 1987] V = fv1; v2; v3; v4g E = fv1v2; v1v3; v1v4; v2v3; v2v4g combinatorial embedding/ planarization 4 3 Reduce Crossings 2 1 3 - 2 Dr. Tamara Mchedlidze · Algorithmen zur Visualisierung von Graphen Flussmethoden: orthogonales Graphenzeichnen (Planar) Orthogonal Drawings Three-step approach: Topology { Shape { Metrics [Tamassia SIAM J. -
Space and Polynomial Time Algorithm for Reachability in Directed Layered Planar Graphs
Electronic Colloquium on Computational Complexity, Revision 1 of Report No. 16 (2015) An O(n) Space and Polynomial Time Algorithm for Reachability in Directed Layered Planar Graphs Diptarka Chakraborty∗and Raghunath Tewari y Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India April 27, 2015 Abstract Given a graph G and two vertices s and t in it, graph reachability is the problem of checking whether there exists a path from s to t in G. We show that reachability in directed layered planar graphs can be decided in polynomial time and O(n ) space, for any > 0. Thep previous best known space bound for this problem with polynomial time was approximately O( n) space [INP+13]. Deciding graph reachability in SC is an important open question in complexity theory and in this paper we make progress towards resolving this question. 1 Introduction Given a graph and two vertices s and t in it, the problem of determining whether there is a path from s to t in the graph is known as the graph reachability problem. Graph reachability problem is an important question in complexity theory. Particularly in the domain of space bounded computa- tions, the reachability problem in various classes of graphs characterize the complexity of different complexity classes. The reachability problem in directed and undirected graphs, is complete for the classes non-deterministic log-space (NL) and deterministic log-space (L) respectively [LP82, Rei08]. The latter follows due to a famous result by Reingold who showed that undirected reachability is in L [Rei08]. -
Graph Drawing Dagstuhl Seminar
05191 Abstracts Collection Graph Drawing Dagstuhl Seminar Michael Jünger1, Stephen Kobourov2 and Petra Mutzel3 1 Univ. of Köln, DE 2 Univ. of Arizona, US [email protected] 3 Univ. of Dortmund, DE [email protected] Abstract. From 08.05. to 13.05.05, the Dagstuhl Seminar 05191 Graph Drawing was held in the International Conference and Research Cen- ter (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The rst section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available. Keywords. Graph Drawing, Visualization, Layout Algorithms, Inter- active Visualization 05191 Executive Summary Graph Drawing This paper summarizes the topics, aims, and achievements of the Dagstuhl Sem- inar 05191 on Graph Drawing. Keywords: Graph drawing Joint work of: Jünger, Michael; Kobourov, Stephen; Mutzel, Petra Full Paper: http://drops.dagstuhl.de/opus/volltexte/2006/342 05191 Open Problem Session Report This is a report on an informal session intended to stimulate communication and sharing of problems. Hence the attributions and citations may contain inaccu- racies, and are certainly not complete. Keywords: Open problems, graph drawing Joint work of: Whitesides, Sue Full Paper: http://drops.dagstuhl.de/opus/volltexte/2006/338 Dagstuhl Seminar Proceedings 05191 Graph Drawing http://drops.dagstuhl.de/opus/volltexte/2006/348 2 M. Jünger, S. Kobourov and P. Mutzel Matrix Zoom: A Visual Interface to Semi-external Graphs James Abello (Rutgers Univ. -
Confluent Hasse Diagrams
Confluent Hasse diagrams David Eppstein Joseph A. Simons Department of Computer Science, University of California, Irvine, USA. October 29, 2018 Abstract We show that a transitively reduced digraph has a confluent upward drawing if and only if its reachability relation has order dimension at most two. In this case, we construct a confluent upward drawing with O(n2) features, in an O(n) × O(n) grid in O(n2) time. For the digraphs representing series-parallel partial orders we show how to construct a drawing with O(n) fea- tures in an O(n) × O(n) grid in O(n) time from a series-parallel decomposition of the partial order. Our drawings are optimal in the number of confluent junctions they use. 1 Introduction One of the most important aspects of a graph drawing is that it should be readable: it should convey the structure of the graph in a clear and concise way. Ease of understanding is difficult to quantify, so various proxies for readability have been proposed; one of the most prominent is the number of edge crossings. That is, we should minimize the number of edge crossings in our drawing (a planar drawing, if possible, is ideal), since crossings make drawings harder to read. Another measure of readability is the total amount of ink required by the drawing [1]. This measure can be formulated in terms of Tufte’s “data-ink ratio” [22,35], according to which a large proportion of the ink on any infographic should be devoted to information. Thus given two different ways to present information, we should choose the more succinct and crossing-free presentation. -
Upward Planar Drawing of Single Source Acyclic Digraphs (Extended
Upward Planar Drawing of Single Source Acyclic Digraphs (Extended Abstract) y z Michael D. Hutton Anna Lubiw UniversityofWaterlo o UniversityofWaterlo o convention, the edges in the diagrams in this pap er Abstract are directed upward unless sp eci cally stated otherwise, An upward plane drawing of a directed acyclic graph is a and direction arrows are omitted unless necessary.The plane drawing of the graph in which each directed edge is digraph on the left is upward planar: an upward plane represented as a curve monotone increasing in the vertical drawing is given. The digraph on the rightisnot direction. Thomassen [14 ] has given a non-algorithmic, upward planar|though it is planar, since placing v graph-theoretic characterization of those directed graphs inside the face f would eliminate crossings, at the with a single source that admit an upward plane drawing. cost of pro ducing a downward edge. Kelly [10] and We present an ecient algorithm to test whether a given single-source acyclic digraph has an upward plane drawing v and, if so, to nd a representation of one suchdrawing. The algorithm decomp oses the graph into biconnected and triconnected comp onents, and de nes conditions for merging the comp onents into an upward plane drawing of the original graph. To handle the triconnected comp onents f we provide a linear algorithm to test whether a given plane drawing admits an upward plane drawing with the same faces and outer face, which also gives a simpler, algorithmic Upward planar Non-upward-planar pro of of Thomassen's result. The entire testing algorithm (for general single-source directed acyclic graphs) op erates 2 in O (n ) time and O (n) space. -
The Open Graph Drawing Framework (OGDF)
17 The Open Graph Drawing Framework (OGDF) Markus Chimani Friedrich-Schiller-Universit¨at Jena 17.1 Introduction::::::::::::::::::::::::::::::::::::::::::::::::: 543 • Carsten Gutwenger The History of the OGDF Outline TU Dortmund 17.2 Major Design Concepts:::::::::::::::::::::::::::::::::::: 544 Modularization • Self-Contained and Portable Source Code Michael J¨unger 17.3 General Algorithms and Data Structures ::::::::::::::: 546 • University of Cologne Augmentation and Subgraph Algorithms Graph Decomposition • Planarity and Planarization Gunnar W. Klau 17.4 Graph Drawing Algorithms ::::::::::::::::::::::::::::::: 550 • Centrum Wiskunde & Planar Drawing Algorithms Hierarchical Drawing • • Informatica Algorithms Energy-Based Drawing Algorithms Drawing Clustered Graphs Karsten Klein 17.5 Success Stories :::::::::::::::::::::::::::::::::::::::::::::: 562 • • TU Dortmund SPQR-Trees Exact Crossing Minimization Upward Graph Drawing Petra Mutzel Acknowledgments :::::::::::::::::::::::::::::::::::::::::::::::::: 564 TU Dortmund References :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 565 17.1 Introduction We present the Open Graph Drawing Framework (OGDF), a C++ library of algorithms and data structures for graph drawing. The ultimate goal of the OGDF is to help bridge the gap between theory and practice in the field of automatic graph drawing. The library offers a wide variety of algorithms and data structures, some of them requiring complex and involved implementations, e.g., algorithms for planarity testing and planarization, or data structures for graph decomposition. A substantial part of these algorithms and data structures are building blocks of graph drawing algorithms, and the OGDF aims at pro- viding such functionality in a reusable form, thus also providing a powerful platform for implementing new algorithms. The OGDF can be obtained from its website at: http://www.ogdf.net This website also provides further information like tutorials, examples, contact information, and links to related projects. -
LNCS 7034, Pp
Confluent Hasse Diagrams DavidEppsteinandJosephA.Simons Department of Computer Science, University of California, Irvine, USA Abstract. We show that a transitively reduced digraph has a confluent upward drawing if and only if its reachability relation has order dimen- sion at most two. In this case, we construct a confluent upward drawing with O(n2)features,inanO(n) × O(n)gridinO(n2)time.Forthe digraphs representing series-parallel partial orders we show how to con- struct a drawing with O(n)featuresinanO(n)×O(n)gridinO(n)time from a series-parallel decomposition of the partial order. Our drawings are optimal in the number of confluent junctions they use. 1 Introduction One of the most important aspects of a graph drawing is that it should be readable: it should convey the structure of the graph in a clear and concise way. Ease of understanding is difficult to quantify, so various proxies for it have been proposed, including the number of crossings and the total amount of ink required by the drawing [1,18]. Thus given two different ways to present information, we should choose the more succinct and crossing-free presentation. Confluent drawing [7,8,9,15,16] is a style of graph drawing in which multiple edges are combined into shared tracks, and two vertices are considered to be adjacent if a smooth path connects them in these tracks (Figure 1). This style was introduced to re- duce crossings, and in many cases it will also Fig. 1. Conventional and confluent improve the ink requirement by represent- drawings of K5,5 ing dense subgraphs concisely. -
Upward Planar Drawings with Three Slopes
Upward Planar Drawings with Three and More Slopes Jonathan Klawitter and Johannes Zink Universit¨atW¨urzburg,W¨urzburg,Germany Abstract. We study upward planar straight-line drawings that use only a constant number of slopes. In particular, we are interested in whether a given directed graph with maximum in- and outdegree at most k admits such a drawing with k slopes. We show that this is in general NP-hard to decide for outerplanar graphs (k = 3) and planar graphs (k ≥ 3). On the positive side, for cactus graphs deciding and constructing a drawing can be done in polynomial time. Furthermore, we can determine the minimum number of slopes required for a given tree in linear time and compute the corresponding drawing efficiently. Keywords: upward planar · slope number · NP-hardness 1 Introduction One of the main goals in graph drawing is to generate clear drawings. For visualizations of directed graphs (or digraphs for short) that model hierarchical relations, this could mean that we explicitly represent edge directions by letting each edge point upward. We may also require a planar drawing and, if possible, we would thus get an upward planar drawing. For schematic drawings, we try to keep the visual complexity low, for example by using only few different geometric primitives [28] { in our case few slopes for edges. If we allow two different slopes we get orthogonal drawings [14], with three or four slopes we get hexalinear and octilinear drawings [36], respectively. Here, we combine these requirements and study upward planar straight-line drawings that use only few slopes. -
The Graph Crossing Number and Its Variants: a Survey
The Graph Crossing Number and its Variants: A Survey Marcus Schaefer School of Computing DePaul University Chicago, Illinois 60604, USA [email protected] Submitted: Dec 20, 2011; Accepted: Apr 4, 2013; Published: April 17, 2013 Third edition, Dec 22, 2017 Mathematics Subject Classifications: 05C62, 68R10 Abstract The crossing number is a popular tool in graph drawing and visualization, but there is not really just one crossing number; there is a large family of crossing number notions of which the crossing number is the best known. We survey the rich variety of crossing number variants that have been introduced in the literature for purposes that range from studying the theoretical underpinnings of the crossing number to crossing minimization for visualization problems. 1 So, Which Crossing Number is it? The crossing number, cr(G), of a graph G is the smallest number of crossings required in any drawing of G. Or is it? According to a popular introductory textbook on combi- natorics [460, page 40] the crossing number of a graph is “the minimum number of pairs of crossing edges in a depiction of G”. So, which one is it? Is there even a difference? To start with the second question, the easy answer is: yes, obviously there is a differ- ence, the difference between counting all crossings and counting pairs of edges that cross. But maybe these different ways of counting don’t make a difference and always come out the same? That is a harder question to answer. Pach and Tóth in their paper “Which Crossing Number is it Anyway?” [369] coined the term pair crossing number, pcr, for the crossing number in the second definition. -
A New Approximation Algorithm for Bend Minimization in the Kandinsky Model
A New Approximation Algorithm for Bend Minimization in the Kandinsky Model Wilhelm Barth1, Petra Mutzel2, and Canan Yıldız1 1 Institute of Computer Graphics and Algorithms, Vienna University of Technology Favoritenstraße 9-11, 1040 Wien, Austria {barth,yildizca}@ads.tuwien.ac.at http://www.ads.tuwien.ac.at/ 2 Department of Computer Science, University of Dortmund Otto-Hahn-Str. 14, D-44227 Dortmund, Germany [email protected] http://ls11-www.cs.uni-dortmund.de/ Abstract. The Kandinsky model has been introduced by F¨oßmeier and Kaufmann in order to deal with planar orthogonal drawings of planar graphs with maximal vertex degree higher than four [7]. No polynomial- time algorithm is known for computing a (region preserving) bend mini- mal Kandinsky drawing. In this paper we suggest a new 2-approximation algorithm for this problem. Our extensive computational experiments [13] show that the quality of the computed solutions is better than those of its predecessors [6]. E.g., for all instances in the Rome graph bench- mark library [4] it computed the optimal solution, and for randomly generated triangulated graphs with up to 800 vertices, the absolute error was less than 2 on average. 1 Introduction Given a planar graph G =(V,E,F) with a fixed embedding F ,weconsider the problem of finding a region-preserving planar orthogonal drawing with the minimum number of bends. For graphs with maximal degree 4 this problem can be solved in polynomial time [12] if no parallel edge segments leaving a vertex at the same side are allowed. The idea is to set up a network in which each flow corresponds to an orthogonal drawing and vice versa. -
New Approaches on Octilinear Graph Drawing
New Approaches on Octilinear Graph Drawing Dissertation der Mathematisch-Naturwissenschaftlichen Fakult¨at der Eberhard Karls Universit¨atT¨ubingen zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Dipl.-Inform. (Bioinf.) Robert Krug aus Ulm T¨ubingen 2015 abc Gedruckt mit Genehmigung der Mathematisch-Naturwissenschaftlichen Fakult¨at der Eberhard Karls Universit¨atT¨ubingen. Tag der m¨undlichen Qualifikation 28.04.2015 Dekan: Prof. Dr. Wolfgang Rosenstiel 1. Berichterstatter: Prof. Dr. Michael Kaufmann 2. Berichterstatter: Prof. Dr. Peter Hauck Acknowledgements First and foremost I thank my advisor Prof. Dr. Michael Kaufmann, for giving me the opportunity to be part of his great group and write this thesis, for supporting me this whole time and enabling me to visit several international workshops and conferences. I am deeply grateful to my colleague Dr. Michael Bekos who not only par- ticipated in every research project that made it into this thesis but also gave me great support during the writing of this thesis and was a very pleasant officemate. My thanks also go to my current and former colleagues Till Bruckdorfer, Philip Effinger, Andreas Gerasch, Niklas Heinsohn, Markus Geyer, Stephan Kottler, Martin Siebenhaller and Christian Zielke who provided a very nice working atmosphere and valuable input in many scientific and non-scientific discussions during our coffee-breaks. I thank all my coauthors, namely Michael Bekos, Markus Geyer, Martin Gronemann, Michael Kaufmann, Thorsten Ludwig, Stefan N¨aherand Vin- cenzo Roselli for the pleasant and productive collaborations. I am most thankful to my friends Chrissi and Klaus who, together with Ju- lian and Laura, always offered me delicious meals and delightful company which I especially appreciated in stressful times of approaching deadlines.