Visualizing Networks: Beyond the Hairball
Nächste SlideShare
Wird geladen in ...5
×

Das gefällt Ihnen? Dann teilen Sie es mit Ihrem Netzwerk

Teilen

Visualizing Networks: Beyond the Hairball

  • 31,604 Views
Hochgeladen am

Strata NYC 2012 slides by Lynn Cherny; layout and analysis strategies for network data.

Strata NYC 2012 slides by Lynn Cherny; layout and analysis strategies for network data.

Mehr in: Technologie
  • Full Name Full Name Comment goes here.
    Sind Sie sicher, dass Sie...
    Ihre Nachricht erscheint hier
  • thanks you for gooooooood material!
    Sind Sie sicher, dass Sie...
    Ihre Nachricht erscheint hier
  • you should check the downloadable materials
    Sind Sie sicher, dass Sie...
    Ihre Nachricht erscheint hier
Keine Downloads

Views

Gesamtviews
31,604
Bei Slideshare
26,766
Aus Einbettungen
4,838
Anzahl an Einbettungen
29

Aktionen

Geteilt
Downloads
722
Kommentare
2
Gefällt mir
86

Einbettungen 4,838

http://blogger.ghostweather.com 3,460
http://www.scoop.it 659
https://twitter.com 386
http://architects.dzone.com 140
http://www.social-computing.com 42
http://7959064_7f65e7b2781bd08c8564c8cfea0d5bdaadcdc528.blogspot.com 36
http://ars-uns.blogspot.com.ar 23
http://ars-uns.blogspot.com.es 14
http://tweetedtimes.com 11
http://ars-uns.blogspot.com 9
http://ukituki.tumblr.com 8
https://si0.twimg.com 8
http://www.twylah.com 5
http://www.newsblur.com 5
http://kred.com 4
https://reader.aol.de 4
http://twitter.com 3
http://www.pinterest.com 3
http://ranksit.com 3
http://pinterest.com 3
http://ars-uns.blogspot.com.br 2
http://feeds.feedburner.com 2
http://abtasty.com 2
http://www.dzone.com 1
http://cloud.feedly.com 1
http://ars-uns.blogspot.mx 1
http://prlog.ru 1
http://www.slashdocs.com 1
http://ars-uns.blogspot.in 1

Inhalte melden

Als unangemessen gemeldet Als unangemessen melden
Als unangemessen melden

Wählen Sie Ihren Grund, warum Sie diese Präsentation als unangemessen melden.

Löschen
    No notes for slide
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • Shows relationships – real or accidental; “the gestalt”\n
  • Ordering is critical, shows strength of relationships\n
  • Order critical, shows relationships between groups; it can all be made to “fit”\n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n

Transcript

  • 1. Visualizing Networks Beyond the “Hairball” Lynn Cherny @arnicas O’Reilly Strata NYC 2012
  • 2. Visualizing Networks Beyond the “Hairball” Lynn Cherny @arnicas O’Reilly Strata NYC 2012
  • 3. PS(A): I AM NOT JASONSUNDRAMHe could not make it, and asked me to take over. 2
  • 4. The Hairball: A Metaphor for Complexityhttp://www.nd.edu/~networks/Publication%20Categories/01%20Review%20Articles/ScaleFree_Scientific%20Ameri%20288,%2060-69%20(2003).pdf
  • 5. http://www.nd.edu/~networks/Publication%20Categories/01%20Review%20Articles/ScaleFree_Scientific%20Ameri%20288,%2060-69%20(2003).pdf
  • 6. http://www.linkedin.com/today/post/article/20121016185655-10842349-the-hidden-power-
  • 7. WHAT IS A NETWORK?It’s not a visualization. Think of it as a data structure.
  • 8. Data relationship: entities + relationshipsto other objects (node/edge, vertex/link)Nodes and Edges may have attributes, eg. gender, age, weight, tv prefs connection date, frequency of contact, type of exchange, directionality of relationship attributes may be calculated from network itself
  • 9. Lane Harrison: http://blog.visual.ly/network-visualizations/
  • 10. Lane Harrison: http://blog.visual.ly/network-visualizations/
  • 11. Lane Harrison: http://blog.visual.ly/network-visualizations/
  • 12. Best! A User Study on Visualizing Directed Edges in Graphs” Danny Holten and Jarke J. van Wijk, 27th SIGCHI Conference on Human Factors in Computing Systems (Proceedings of CHI 2009),http://blog.visual.ly/network-visualizations/ 9
  • 13. 10
  • 14. 10
  • 15. 10
  • 16. It’s a natural human trait to see visual similarity and proximity asmeaningful.Be very careful about your display choices and layout methods! 10
  • 17. Reading a network visualization There’s obviously something important going on here, structurally....
  • 18. Reading a network visualization Lo o k a t th is o utl ier cas e! There’s obviously something important going on here, structurally....
  • 19. Reading a network visualization à Lo o age k a mé n ere t th A ver h is o i s o utl tro ier cas e! There’s obviously something important going on here, structurally....
  • 20. S? MIReading a network visualization à Lo o age k a mé n ere t th A ver h is o i s o utl tro ier cas e! There’s obviously something important going on here, structurally....Using a “random” Gephi layout on the dolphins
  • 21. S? MIReading a network visualization à Lo o age k a mé n ere t th A ver h is o i s o utl tro ier cas e! Rando m! There’s obviously something important going on here, structurally....Using a “random” Gephi layout on the dolphins
  • 22. Design Examples s! lp h in o it h D w
  • 23. The Dolphins of Doubtful Soundhttp://www.doc.govt.nz/documents/conservation/native-animals/marine-mammals/abundance-population-structure-bottlenose-dolphins-doubtful-dusky-sounds.pdf
  • 24. “The bottlenose dolphin community of DoubtfulSound features a large proportion of long-lastingassociations. Can geographic isolation explain thisunique trait?”David Lusseau et al. BEHAVIORAL ECOLOGY ANDSOCIOBIOLOGY Volume 54, Number 4 (2003)http://www.springerlink.com/content/pepxvj4lu42ur2gw/
  • 25. “The bottlenose dolphin community of DoubtfulSound features a large proportion of long-lastingassociations. Can geographic isolation explain thisunique trait?” ! ti tle p er l pa tua ac e ThDavid Lusseau et al. BEHAVIORAL ECOLOGY ANDSOCIOBIOLOGY Volume 54, Number 4 (2003)http://www.springerlink.com/content/pepxvj4lu42ur2gw/
  • 26. “SF” “ULT” 2 hung outD. Lusseau, Evidence for Social Role in a Dolphin Social Network.Evol Ecol (2007) 21:357–366
  • 27. Citation: Lusseau D (2007) Why Are Male Social Relationships Complex in the Doubtful Sound Bottlenose Dolphin Population?. PLoS ONE 2(4):e348. doi:10.1371/journal.pone.0000348
  • 28. Citation: Lusseau D (2007) Why Are Male Social Relationships Complex in the Doubtful Sound Bottlenose Dolphin Population?. PLoS ONE 2(4):e348. doi:10.1371/journal.pone.0000348 define relationship Using “mirroring” to
  • 29. Citation: Lusseau D (2007) Why Are Male Social Relationships Complex in the Doubtful Sound Bottlenose Dolphin Population?. PLoS ONE 2(4):e348. doi:10.1371/journal.pone.0000348 define edges “headbutting” to define relationship UsingUsing “mirroring” to
  • 30. TOOLS FOR TODAYCreating network layouts... 17
  • 31. Gephi 18
  • 32. Or “D3” (d3js.org)• A “build it yourself” svg-based visualization library• Import graphs as (or parse to create) a json node-link structure
  • 33. Making a NetworkWho is your audience? What’s the goal? Exploration / Iterative visualization during data analysis? End-user communication?
  • 34. Making a NetworkWho is your audience? What’s the goal? Exploration / Iterative visualization during data analysis? End-user communication? Layout choices: by hand, algorithmic, style... Understand the global and local context with some stats about actors and roles in the network Improve your layout with stats / attributes - inherent (such as gender) or calculated (e.g., degree) Add interactivity for end users if appropriate
  • 35. J Bertin: Semiologyof Graphics Linear Circular Irregular Regular (Tree) 3D Matrix / BipartiteBertin, J. Semiology of Graphics: Diagrams,Networks, Maps (1967)
  • 36. Algorithmic ApproachesFrank van Ham talk slides: http://bit.ly/s6udpy
  • 37. (Trees are a whole other subject)Treevis.net: http://www.informatik.uni-rostock.de/~hs162/treeposter/poster.html
  • 38. MATRIX LAYOUTS /REPRESENTATIONS
  • 39. http://barabasilab.neu.edu/networksciencebook/download/network_science_October_2012.pdf
  • 40. Real social networks are generally quite sparse.http://www.cise.ufl.edu/research/sparse/matrices/Newman/dolphins.html
  • 41. D3 demo by me http://www.ghostweather.com/essays/talks/networkx/adjacency.html
  • 42. NodeTrix: A Hybrid Visualization of Social Networks. Nathalie Henry, Jean-Daniel Fekete, andMichael J. McGuffin. (2007) http://arxiv.org/abs/0705.0599
  • 43. http://semilattice.net/eyeodiff/
  • 44. http://semilattice.net/eyeodiff/
  • 45. ARC / LINEAR LAYOUTS
  • 46. Philipp Steinweber and Andreas Koller Similar Diversity, 2007For a D3 example in another domain: http://tradearc.laserdeathstehr.com/
  • 47. http://www.openbible.info/blog/2010/04/bible-cross-references-visualization/
  • 48. Hive PlotsD3: http://bost.ocks.org/mike/hive/
  • 49. http://mariandoerk.de/pivotpaths/
  • 50. Design Interlude
  • 51. Bertin’s Thought ProcessBertin, J. Semiology of Graphics: Diagrams, Networks, Maps (1967)
  • 52. (P) Paris(Z) Paris Suburbs(+50) Communes of >50K(+10) Communes of >10K(-10) Communes of <10K(R) Rural
  • 53. CIRCULAR / CHORD LAYOUTS
  • 54. “If its Circos pro bab rou ly d nd, o it Circ os ” canhttp://circos.ca/images/
  • 55. Simple Orderings of Nodes Circular Layout “Dual Circle” layout with Sorted by ordered by Degree most popular dolphin in center Modularity 41Dolphins colored by modularity class (community) in Gephi
  • 56. http://www.ghostweather.com/essays/talks/networkx/chord.html
  • 57. http://www.ghostweather.com/essays/talks/networkx/chord.html
  • 58. Hierarchical Edge Bundling"Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data”, Danny Holten, IEEETransactions on Visualization and Computer Graphics (TVCG; Proceedings of Vis/InfoVis 2006), Vol. 12, No. 5,
  • 59. A D3 Example by M. BostockD3: http://bl.ocks.org/1044242
  • 60. A very short detour into maps...
  • 61. 46Flow Map Layout, Phan et al (2005) http://graphics.stanford.edu/papers/flow_map_layout/
  • 62. 46Flow Map Layout, Phan et al (2005) http://graphics.stanford.edu/papers/flow_map_layout/
  • 63. "Force-Directed Edge Bundling for Graph Visualization”,Danny Holten and Jarke J. van Wijk, 11th Eurographics/IEEE-VGTC Symposium on Visualization (ComputerGraphics Forum; Proceedings of EuroVis 2009), Pages 983 - 990, 2009.
  • 64. Divided Edge Bundling for Directional Network DataDavid Selassie, Brandon Heller, Jeffrey HeerIEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2011 48
  • 65. Design Example
  • 66. 50http://jeromecukier.net/projects/agot/places.html
  • 67. 50http://jeromecukier.net/projects/agot/places.html
  • 68. 51Jerome’s version with the map is not available online, sorry.
  • 69. Yet Another Design Example
  • 70. Moritz Stefaner’s Muesli Problemhttps://speakerdeck.com/u/moritzstefaner/p/omg-its-all-connected
  • 71. https://speakerdeck.com/u/moritzstefaner/p/omg-its-all-connected
  • 72. s li ke iou ch lic u m ot de o “ To s, n h!” el f o om oug ims hr en to h us m i tz or -Mhttps://speakerdeck.com/u/moritzstefaner/p/omg-its-all-connected
  • 73. Finalhttps://speakerdeck.com/u/moritzstefaner/p/omg-its-all-connected
  • 74. ALGORITHMIC LAYOUTSGephi / D3.js / Other tools
  • 75. Gephi  Sigma.jsGephi.org: Open source, runs on Mac, Linux, PC Can be run from a python-esque console plugin or UI Can be run “headless” for layouts (Jason Sundram) https://github.com/jsundram/pygephi Plugins include a Neo4j graph db access, and streaming supportSigma.js : Will display a gexf gephi layout file with minimal work, using a plugin interpreter for sigma Also offers a force-directed layout plugin for graphs without x&y coords Does CANVAS drawing, not SVG
  • 76. http://www.barabasilab.com/pubs/CCNR-ALB_Publications/200705-14_PNAS-HumanDisease/Suppl/
  • 77. Movie:Sigma.js version of the Gephi export http://exploringdata.github.com/vis/human-disease-
  • 78. Using Sigma.js basic_sigma.js<div class="sigma-expand“ function init() { // Instanciate sigma.js and customize rendering : id="sigma-example"></div> var sigInst = sigma.init(document.getElementById(sigma-example)) .drawingProperties({ defaultLabelColor: #fff, defaultLabelSize: 14, defaultLabelBGColor: #fff, defaultLabelHoverColor: #000, labelThreshold: 6, defaultEdgeType: curve }).graphProperties({ minNodeSize: 0.5, maxNodeSize: 5, minEdgeSize: 1, maxEdgeSize: 1 }).mouseProperties({ Where maxRatio: 32 }); to put // Parse a GEXF encoded file to fill the graph the<script src="../js/sigma.min.js"></script> // (requires "sigma.parseGexf.js" to be included)<script src="../js/sigma.parseGexf.js"></script> sigInst.parseGexf(color_by_mod.gexf); graph<script src="basic_sigma.js"></script> // Draw the graph : sigInst.draw(); } Your graph if (document.addEventListener) { document.addEventListener("DOMContentLoaded", init, false); } else { window.onload = init; } In sigma.js’s github (under plugins!)
  • 79. Sample Layout Plugins in Gephihttps://gephi.org/tutorials/gephi-tutorial-layouts.pdf
  • 80. Gephi Plugin Layout Details Layout Complexity Graph Size Author Comment Circular O(N) 1 to 1M nodes Matt Groeninger Used to show distribution, ordered layout Radial Axis O(N) 1 to 1M nodes Matt Groeninger Show ordered groups (homophily) Force Atlas O(N²) 1 to 10K nodes Mathieu Jacomy Slow, but uses edge weight and few biases Force Atlas 2 O(N*log(N)) 1 to 1M nodes Mathieu (does not use Jacomy weight) OpenOrd O(N*log(N)) 100 to 1M nodes S. Martin, W. M. Focus on clustering Brown, R. Klavans, (uses edge weight) Yifan Hu O(N*log(N)) 100 to 100K nodes and K. Boyack Yifan Hu (no edge weight) Fruchterman- O(N²) 1 to 1K nodes Fruchterman & Particle system, slow Rheingold Rheingold! (no edge weight) GeoLayout O(N) 1 to 1M nodes Alexis Jacomy Uses Lat/Long for layouthttps://gephi.org/2011/new-tutorial-layouts-in-gephi/
  • 81. Dolphins AgainOpenOrd + “No Overlap” ForceAtlas2 63
  • 82. Dolphins AgainOpenOrd + “No Overlap” ForceAtlas2 63
  • 83. Dolphins AgainOpenOrd + “No Overlap” ForceAtlas2 63
  • 84. Unweighted dolphins, Force AtlasWeight 2: Force Atlas Weight 4: Force Atlas 64
  • 85. Unweighted dolphins, Force AtlasWeight 2: Force Atlas Weight 4: Force Atlas Weight 4: Yifan Hu 64
  • 86. Canvas/SVG benchmarks from the d3.js group: https://docs.google.com/spreadsheet/ ccc?Nick Diakapolous: http://nad.webfactional.com/ntap/graphscale/ key=0AtvlFoSBUC5kdEZJNVFySG9wSHZk
  • 87. Canvas/SVG benchmarks from the d3.js group: https://docs.google.com/spreadsheet/ ccc?Nick Diakapolous: http://nad.webfactional.com/ntap/graphscale/ key=0AtvlFoSBUC5kdEZJNVFySG9wSHZk
  • 88. SIMPLE CALCULATIONS ONNETWORKS CAN TELL YOUOften you need to visualize the structure/role of the graphelements as part of the visualization: So, do some simplemath.
  • 89. Degree (In, Out) “Degree” is a measure of the edges in (directed), out (directed), or total (in directed or undirected graphs) to a node “Hub” nodes have high in- degree. In scale-free networks, we see preferential attachment to the popular kids.http://mlg.ucd.ie/files/summer/tutorial.pdf
  • 90. Scale-free NetworksImage from Lada Adamic’s SNA Course on Coursera pdf 3D
  • 91. The Threat of Hub-LossAlbert-László Barabási and Eric Bonabeau, Scale-Free Networks, 2003.http://www.scientificamerican.com/article.cfm?id=scale-free-networks
  • 92. Visualization Aside: If Some Names are Huge, the Others are Invisible-? 70Correcting for text size by degree display issue
  • 93. Visualization Aside: If Some Names are Huge, the Others are Invisible-? Gephi Panel 70Correcting for text size by degree display issue
  • 94. Visualization Aside: If Some Names are Huge, the Others are Invisible-? Gephi Panel 70Correcting for text size by degree display issue
  • 95. Visualization Aside: If Some Names are Huge, the Others are Invisible-? Gephi Panel 70Correcting for text size by degree display issue
  • 96. Betweenness A measure of connectedness between (sub)components of the graph “Betweenness centrality thus tends to pick out boundary individuals who play the role of brokers between communities.”Lusseau and Newman. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1810112/pdf/15801609.pdf http://en.wikipedia.org/wiki/Centrality#Betweenness_centrality
  • 97. Judging By Eye Will Probably BeWrong... 72
  • 98. Judging By Eye Will Probably BeWrong... ? This one? 72
  • 99. Judging By Eye Will Probably BeWrong... ? This one? Sized by Betweenness 72
  • 100. Eigenvector Centrality Intuition: A node is important if it is connected to other important nodes A node with a small number of influential contacts may outrank one with a larger number of mediocre contactshttp://mlg.ucd.ie/files/summer/tutorial.pdf http://demonstrations.wolfram.com/
  • 101. PagerankWikipedia image
  • 102. Community Detection E.g., the Louvain method, in Gephi as “Modularity.” Many layout algorithms help you intuit these structures, but don’t rely on perception of layout!http://en.wikipedia.org/wiki/File:Network_Community_Structure.png
  • 103. Citation: Lusseau D (2007) Why Are Male Social Relationships Complex in the Doubtful SoundBottlenose Dolphin Population?. PLoS ONE 2(4): e348. doi:10.1371/journal.pone.0000348
  • 104. Citation: Lusseau D (2007) Why Are Male Social Relationships Complex in the Doubtful SoundBottlenose Dolphin Population?. PLoS ONE 2(4): e348. doi:10.1371/journal.pone.0000348 77
  • 105. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 106. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 107. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 108. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 109. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 110. Identifying the role that animals play in their social networks (2004)D Lusseau, MEJ NewmanProceedings of the Royal Society of London. Series B: Biological Sciences
  • 111. Eduarda Mendes Rodrigues, Natasa Milic-Frayling, Marc Smith, Ben Shneiderman, Derek Hansen, Group-in-a-box Layout for Multi-faceted Analysis of Communities. IEEE Third International Conference on Social
  • 112. http://mbostock.github.com/d3/talk/20111116/force-collapsible.html
  • 113. http://mbostock.github.com/d3/talk/20111116/force-collapsible.html
  • 114. Movie:Ger Hobbelt D3: http://bl.ocks.org/3616279
  • 115. Movie:Ger Hobbelt D3: http://bl.ocks.org/3616279
  • 116. Design Example
  • 117. 100 nodes, size by degree, Clustered by partition, no edges shaded by Betweenness, in until you click on one, node size is a d3.js force directed layout. choice of attributes, nodes represented by labels/colors….http://www.ghostweather.com/essays/talks/networkx/ http://www.ghostweather.com/essays/talks/networkx/
  • 118. Movie: 84http://www.ghostweather.com/essays/talks/networkx/force_fonts.html
  • 119. Movie: by @moebio 85http://intuitionanalytics.com/pleiades/
  • 120. ! LOLSO YOU WANT TO LAY IT OUTYOURSELF...Perfectionist? Artist? Don’t like algorithms? 86
  • 121. Jeff Heer: http://hci.stanford.edu/courses/cs448b/f11/lectures/CS448B-20111110-
  • 122. Design Examples
  • 123. Conspiracy Theorist Mark Learning from Lombardi: http://benfry.com/exd09/
  • 124. Conspiracy Theorist Mark Learning from Lombardi: http://benfry.com/exd09/
  • 125. Stefanie Posavechttp://www.itsbeenreal.co.uk/index.php?/wwwords/literary-
  • 126. Roche Applied Science Biochemical Pathways Map: http://web.expasy.org/cgi-bin/pathways/
  • 127. Roche Applied Science Biochemical Pathways Map: http://web.expasy.org/cgi-bin/pathways/
  • 128. Hybrid Method: Use algorithmic layout, and then adjust nodes byGer Hobbelt in D3: http://bl.ocks.org/3637711
  • 129. Tweaking your layout is addictive! Yo ned wa u r ha ! ve ! be enJason Davies: http://www.jasondavies.com/planarity/
  • 130. STEP BACK, SCALE UP... 94
  • 131. C.Dunne & B.Shneiderman. Network Motif Simplification. http://hcil2.cs.umd.edu/trs/
  • 132. GraphPrism: Compact Visualization of Network StructureSanjay Kairam, Diana MacLean, Manolis Savva, Jeffrey HeerAdvanced Visual Interfaces, 2012
  • 133. 97http://openaccess.city.ac.uk/1324/
  • 134. Video: 98http://graphics.wsj.com/political-moneyball/
  • 135. Wrap it up on design...
  • 136. RemindersChoose your visual encodings, layout,interaction to make it a visualization,rather than raw data vomit. Take care: people will infer things from proximity/similarity even if it was not intended!Do data analysis / reduction - whywould you want to show 1T of networkdata?Allow interactivity if needed for endusers. Help people find things in your network!
  • 137. RemindersChoose your visual encodings, layout,interaction to make it a visualization,rather than raw data vomit. Take care: people will infer things from To ot sci proximity/similarity even if it was not =N o m wa ce d intended! at uc al en a h d goDo data analysis / reduction - why at ys ! awould you want to show 1T of network o ddata?Allow interactivity if needed for endusers. Help people find things in your network!
  • 138. More Reminders!Different layouts communicate differentthings to your viewer - choose wiselyReducing noise: Don’t show edges (perhaps on demand) Show details only on demand: zoom in Cluster your nodes/edges Consider if it has to be a “network” display at all: Is it the stats you care about? Or the hairball? 101
  • 139. The Map is Not the Territory…Forest Pitts (thanks to Noah Friedkin) http://www.analytictech.com/networks/pitts.htm
  • 140. The Map is Not the Territory…Forest Pitts (thanks to Noah Friedkin) http://www.analytictech.com/networks/pitts.htm
  • 141. www.Visualcomplexity.com
  • 142. Thanks! @arnicas lynn@ghostweather.comAnd thanks to twitter vis friends for content: @jsundram, @laneharrison, @moritz_stefaner, @jcukier,@jeff1024, @vlandham, @moebio, @jeffrey_heer, @mbostock, @eagereyes, @jasondavies, @stefpos, @sarahslo, @ndiakopoulos, @gephi
  • 143. A Few More ReferencesJeff Heer class slides: http:// Robert Kosara’s post: http://hci.stanford.edu/courses/cs448b/ eagereyes.org/techniques/graphs-w09/lectures/20090204- hairballGraphsAndTrees.pdf Lane Harrison’s post: http://A great in-progress book on networks: blog.visual.ly/network-http://barabasilab.neu.edu/ visualizations/networksciencebook/ MS Lima’s book Visual ComplexityMark Newman’s many papers: http:// Jason Sundram’s tool to drive Gephiwww-personal.umich.edu/~mejn/ layout from command line: https://Eyeo Festival videos from Moritz github.com/jsundram/pygephiStefaner, Manuel Lima, Stefanie A couple articles on communityPosavec structure:Journal of Graph Algorithms and Overlapping Community DetectionApplications: http://jgaa.info/ in Networks: State of the Arthome.html and Comparative Study by JieruiJim Vallandingham’s D3 network Xie, Stephen Kelley, Boleslaw K.tutorials: http://flowingdata.com/ Szymanski2012/08/02/how-to-make-an- Empirical Comparison ofinteractive-network-visualization/, Algorithms for Network