IAT 355 1 Graphs ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT]

Slides:



Advertisements
Similar presentations
IAT Graphs ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT]
Advertisements

Cpt S 223 – Advanced Data Structures Graph Algorithms: Introduction
Orthogonal Drawing Kees Visser. Overview  Introduction  Orthogonal representation  Flow network  Bend optimal drawing.
Network Visualization by Semantic Substrates Aleks Aris Ben Shneiderman.
22C:19 Discrete Math Graphs Fall 2014 Sukumar Ghosh.
Midwestern State University Department of Computer Science Dr. Ranette Halverson CMPS 2433 – CHAPTER 4 GRAPHS 1.
Label Placement and graph drawing Imo Lieberwerth.
Data Structure and Algorithms (BCS 1223) GRAPH. Introduction of Graph A graph G consists of two things: 1.A set V of elements called nodes(or points or.
Hank Childs, University of Oregon November 22 nd, 2013 Force Directed Layouts.
Last time: terminology reminder w Simple graph Vertex = node Edge Degree Weight Neighbours Complete Dual Bipartite Planar Cycle Tree Path Circuit Components.
Graph Drawing Zsuzsanna Hollander. Reviewed Papers Effective Graph Visualization via Node Grouping Janet M. Six and Ioannis G. Tollis. Proc InfoVis 2001.
Visual Analysis of Large Graphs Using (X, Y)-clustering and Hybrid Visualizations V. Batagelj, W. Didimo, G. Liotta, P. Palladino, M. Patrignani (Univ.
Identifying Patterns in Road Networks Topographic Data and Maps Henri Lahtinen Arto Majoinen.
Graph Drawing Introduction 2005/2006. Graph Drawing: Introduction2 Contents Applications of graph drawing Planar graphs: some theory Different types of.
Graph & BFS.
Computational Methods for Management and Economics Carla Gomes Module 9a Network Models Terminology (Slides adapted from J.Orlin’s)
Graph Visualization cs5764: Information Visualization Chris North.
Chapter 9 Graph algorithms. Sample Graph Problems Path problems. Connectedness problems. Spanning tree problems.
CSE 6405 Graph Drawing Text Books T. Nishizeki and M. S. Rahman, Planar Graph Drawing, World Scientific, Singapore, G. Di Battista,
SIMS 247: Information Visualization and Presentation jeffrey heer
Spring 2010CS 2251 Graphs Chapter 10. Spring 2010CS 2252 Chapter Objectives To become familiar with graph terminology and the different types of graphs.
CSE 780 Algorithms Advanced Algorithms Graph Algorithms Representations BFS.
Visualization of Graph Data CS 4390/5390 Data Visualization Shirley Moore, Instructor October 6,
CS/ENGRD 2110 Object-Oriented Programming and Data Structures Fall 2014 Doug James Lecture 17: Graphs.
Department of Computer Science, University of California, Irvine Site Visit for UC Irvine KD-D Project, April 21 st 2004 The Java Universal Network/Graph.
Graphs, Networks, Trees. Examples for in class Visual Web ▫ Website as graphs ( Website as graphs.
Visualization Taxonomies and Techniques Graphs University of Texas – Pan American CSCI 6361, Spring 2014.
I NTRODUCTION TO G RAPH DRAWING Fall 2010 Battista, G. D., Eades, P., Tamassia, R., and Tollis, I. G Graph Drawing: Algorithms for the Visualization.
Programming for Geographical Information Analysis: Advanced Skills Online mini-lecture: Introduction to Networks Dr Andy Evans.
Chapter 9 – Graphs A graph G=(V,E) – vertices and edges
IAT Text ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT]
Crossing Minimisation (1) Ronald Kieft. Global contents Specific 2-layer Crossing Minimisation techniques After the break, by Johan Crossing Minimisation.
Network Aware Resource Allocation in Distributed Clouds.
Computer Science 112 Fundamentals of Programming II Introduction to Graphs.
Lecture 12: Network Visualization Slides are modified from Lada Adamic, Adam Perer, Ben Shneiderman, and Aleks Aris.
Graphs, Networks, Trees. Examples for in class Visual Web ▫ Website as graphs Website as graphs  See Brad’s
GRAPHS CSE, POSTECH. Chapter 16 covers the following topics Graph terminology: vertex, edge, adjacent, incident, degree, cycle, path, connected component,
IAT 814 Trees Chapter 3.2 of Spence ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS +
Representing and Using Graphs
Nyhoff, ADTs, Data Structures and Problem Solving with C++, Second Edition, © 2005 Pearson Education, Inc. All rights reserved Graphs.
Mathematics of Networks (Cont)
Paradigms for Graph Drawing Graph Drawing: Algorithms for the Visualization of Graphs - Chapter 2 Presented by Liana Diesendruck.
Data Structures & Algorithms Graphs
IAT Text ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT]
COSC 2007 Data Structures II Chapter 14 Graphs I.
Most of contents are provided by the website Graph Essentials TJTSD66: Advanced Topics in Social Media.
CS270 Project Overview Maximum Planar Subgraph Danyel Fisher Jason Hong Greg Lawrence Jimmy Lin.
Visualizing Massive Multi-Digraphs James Abello Jeffrey Korn Information Visualization Research Shannon Laboratories, AT&T Labs-Research All the graphs.
Graphs A graphs is an abstract representation of a set of objects, called vertices or nodes, where some pairs of the objects are connected by links, called.
Graphs. Introduction Graphs are a collection of vertices and edges Graphs are a collection of vertices and edges The solid circles are the vertices A,
Data Structures & Algorithms Graphs Richard Newman based on book by R. Sedgewick and slides by S. Sahni.
GRAPHS. Graph Graph terminology: vertex, edge, adjacent, incident, degree, cycle, path, connected component, spanning tree Types of graphs: undirected,
Copyright © Curt Hill Graphs Definitions and Implementations.
“Niche Work” Graham J Wills, Lucent Technologies (Bell Lab)
Source: CSE 214 – Computer Science II Graphs.
Graphs Definition: a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected.
Graphs. Graph Definitions A graph G is denoted by G = (V, E) where  V is the set of vertices or nodes of the graph  E is the set of edges or arcs connecting.
IAT 355 Graphs ______________________________________________________________________________________.
Graphs Lecture 19 CS2110 – Spring 2013.
Basic Concepts Graphs For more notes and topics visit:
I206: Lecture 15: Graphs Marti Hearst Spring 2012.
CS200: Algorithm Analysis
Graphs Chapter 13.
Graphs All tree structures are hierarchical. This means that each node can only have one parent node. Trees can be used to store data which has a definite.
Graph Theory By Amy C. and John M..
Trees-2, Graphs Data Structures with C Chpater-6 Course code: 10CS35
GRAPHS Lecture 17 CS2110 Spring 2018.
GRAPHS Lecture 17 CS 2110 — Spring 2019.
Chapter 9 Graph algorithms
Presentation transcript:

IAT Graphs ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] |

Jun 18, 2014 IAT Graphs Definition –Mathematical structures used to model pairwise relations between objects Example relations –Airline Flights –Train stops –Circles of friends of MyFace

Jun 18, 2014 IAT What is a Graph? Vertices (nodes) connected by Edges (links) Adjacency Matrix ,3 2 Adjacency List

Jun 18, 2014 IAT Graph Terminology Graphs can have cycles Graph edges can be directed or undirected The degree of a vertex is the number of edges connected to it –In-degree and out-degree for directed graphs Graph edges can have values (weights) on them (nominal, ordinal or quantitative)

Jun 18, 2014 IAT Trees Subcase of general graph No cycles Typically directed edges Special designated root vertex

Jun 18, 2014 IAT Graph Uses In Information Visualization, any number of data sets can be modeled as a graph –Telephone system –World Wide Web –Distribution network for on-line retailer –Call graph of a large software system –Semantic map in an AI algorithm –Set of connected friends

Jun 18, 2014 IAT Graph Uses Facilitate understanding of complex socioeconomic patterns Social Science visualization gallery (Lothar Krempel): – Next slide: Krempel & Plumper’s study of World Trade between OECD countries, 1981 and

Jun 18, 2014 IAT

Jun 18, 2014 IAT Vizster Social Network Visualization Video

Cytoscape Visualization of protein-protien interaction networks Jun 18, 2014 IAT

Jun 18, 2014 IAT Graph Uses Facilitate understanding of network flows, relations Even information with a ‘geographical’ content can best appear as a ‘network’ rail maps Geographic landmarks largely suppressed on maps, except water (rivers in Paris, London)

Jun 18, 2014 IAT Case Study AT&T long distance phone network –110 Nodes (switches) Geographical location –Connected by 12,000 links –Directed, almost completely connected Data every 5 minutes EARTHQUAKE –Oct. 17, 1989

Jun 18, 2014 IAT Questions Where are the overloads? Which links are carrying most traffic? Was there network damage? Is there underutilized capacity? Are calls getting in to affected area or are there bottlenecks? Is overload increasing or decreasing?

Jun 18, 2014 IAT Edge Drawing Strategies Label Thickness Color Directed

Jun 18, 2014 IAT

Jun 18, 2014 IAT Problems Too many lines! –Occlusion –Long lines become “more important” –Can’t see what happens in Midwest Solutions –Use half/half technique out/out –Draw most important last –Use thickness & color for traffic

Jun 18, 2014 IAT

Jun 18, 2014 IAT More Help Shorten all lines so as to de-emphasize transcontinental links

Jun 18, 2014 IAT

Jun 18, 2014 IAT TouchGraph Facebook Friends graph –

Jun 18, 2014 IAT Focus of Graph Particular node may be focus, often placed in center for circular layout How does one build an interactive system that allows changes in focus? –Use animation –Maintain constancy of shape, link crossings

Jun 18, 2014 IAT Graph Visualization Problems Graph layout and positioning –Make a concrete rendering of abstract graph Scale –Not too much of a problem for small graphs, but large ones are much tougher Navigation/Interaction –How to support user changing focus and moving around the graph

Jun 18, 2014 IAT Graph Layout Vary hard problem, since graph nodes can have any degree Good references: –Tutorial (talk slides) – –G. diBattista, P. Eades, R. Tamassia, and I. Tollis, Graph Drawing: Algorithms for the Visualization of Graphs, Prentice Hall, –Herman et al, IEEE TVCG 2000

Jun 18, 2014 IAT Vertex Issues Shape Color Size Location Label

Jun 18, 2014 IAT Edge Issues Color Size Label Form Polyline, straight line, orthogonal, grid, curved, planar, upward/downward,...

Jun 18, 2014 IAT Complexity Considerations Crossings-- minimize towards planar Total Edge Length-- minimize towards proper scale Area-- minimize towards efficient use of space Maximum Edge Length-- minimize longest edge Uniform Edge Lengths-- minimize variances Total Bends– minimize orthogonal towards straight-line

Jun 18, 2014 IAT Which Matters? Various studies examined which of the complexity factors matter most and/or what kinds of layout/vis techniques look best –Purchase, Graph Drawing ’97 –Ware et al, Info Vis1(2), June ’02 –Ghoniem et al, Info Vis 4(2), Summer ’05 Results mixed: Edge crossings seem most important

Jun 18, 2014 IAT Layout Heuristics Layout algorithms can be –planar –grid-based –orthogonal –curved lines –hierarchies –circular

Jun 18, 2014 IAT Types of Layout Algorithms From P Mutzel et al Graph Drawing ‘97

Jun 18, 2014 IAT Layout Types Grid Layout –Put nodes on a grid Tree Layout Spring Layout –Model graph as set of masses connected by springs Planar Layout –Detect part of graph that can be laid out without edge crossings

Jun 18, 2014 IAT Layout Subproblems Rank Assignment –Compute which nodes have large degree, put those at center of clusters Crossing Minimization –Swap nodes to rearrange edges Subgraph Extraction –Pull out cluster of nodes Planarization –Pull out a set of nodes that can lay out on plane

Jun 18, 2014 IAT Scale Challenge May run out of space for vertices and edges (turns into “ball of string”) Can really slow down algorithm Often use clustering to help –Extract highly connected sets of vertices –Collapse some vertices together

Jun 18, 2014 IAT Navigation/Interaction Issues How do we allow a user to query, visit, or move around a graph? Changing focus may entail a different rendering

Design Exercise ABCDEF A B C D E F Jun 18, 2014 IAT RelationshipValue Knows1 Likes2 Dislikes3 Hates4 Loves5 Row Loves Column