Network Mapping & Data Storytelling for Beginners


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5-hour Workshop about network mapping and data storytelling.
This includes examples about data, networks, visualization, etc.

Given on Jan 31st, 2013 during a lecture in the Master Information, Technology and Territories in the Institute of Geography and Social Sciences, Toulouse 2 University. France.

Many thanks to @graphcommons for the inspiration.

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Network Mapping & Data Storytelling for Beginners

  1. 1. DATA & VISUALIZATION INVESTIGATING ClémentCOMPLEX TERRITORIES Renaud Toulouse 2 University - Oct 2013 @clemsos
  2. 2. ABOUT MEClément RenaudphD Social networks and urbanspaces in ChinaCo-founder Sharism Lab #@sharismlab journalism visualization@clemsos social China
  3. 3. TODAY CLASS: OBJECTIVESWhat is data and Achievement how people use it MAP A NETWORKHow it relates to territories 1) Identify a caseShowcase some examples 2) Find data you needIntroduce tools 3) Map it
  4. 4. TODAY CLASS: DETAILS Data Morning Duration: 2x3h Some definitions Data & territoriesWorkshop: Network mapping Materials: Slides (here) Notes Viz Afternoon Visualization Tools gallery Workshop: Visualize it
  5. 5. DATA,NETWORKS, PART 1 : Definitions ETC.
  6. 6. WHAT IS DATA?DATA :- Factual information, especially information organized for analysis or used to reason or make decisions- Information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful- Information in numerical form that can be digitally transmitted or processed F r o m M e r r i a m - We b s t e r
  7. 7. SOMEDATALook at those
  8. 8. DATA=DIGITAL INFORMATION Written info in huge amounts Quantification of its subject / object Storage - in computers databases Can be processed by machines Huge trend in early 21st Century: business, ad, indsutry, science, etc.
  9. 9. WHAT IS AT STAKE WITH DATA?Objectivize things to provide new understandingA « facts are sacred » approach towards complex questions and problem-solvingApply scientific method to interrogate any kind of beings, objects, ideas, etc.
  10. 10. HANDLE COMPLEXITYLinked Data Cloud
  11. 11. HANDLE COMPLEXITYProblem:Most of data is made by machines,for machines.How can we access it?How can we understand it?
  12. 12. THE DATA SCIENCE METHOD From raw data1. Statistics: Studying to images2. Data Munging: Suffering3. Visualization: Storytelling Mike @dataspora , Sexy Data Geeks. 2009
  13. 13. DATASCIENCEMethodologyforinvestigationExamples:DNABrain studiesSocial NetworksAnalysis…
  14. 14.
  15. 15. VISUALIZATION“The brain doesn’t just process informationthat comes though the eyes. It also createsmental visual images that allow us toreason and plan actions that facilitatesurvival.” A. Cairo, The Functional Art - 2013
  17. 17. LINKEDINNETWORKVi s u a l i z a t i o nof myprofessionaln e t wo r k u s i n gLinkedin LabsFacebookn e t wo r k g r a p hcan begeneratedusingN e t vi z z
  18. 18. SEATTLEBANDMAPThe SeattleBand Mapexplores howbands from thePacificNorthwest areinterconnectedthroughpersonalrelationshipsandcollaborations.h t t p : / / w w w. s e a t
  19. 19. MUSEMuse is ani n t e r a ct i vevi s u a l i z a t i o n o fscientificpublications toe xp l o r e t h ecollaborationsb e t we e ni n s t i t u ti o n s .h t t p : // t i l l n a g e l .c o m / 2010/ 11/muse/
  20. 20. KIVAMAPMapping 2005-2 0 11 K i vaa c t i vi t y ( m i c r o -loans andp a yb a c k )Vi d e o f r o mh t t p : // vi m e o . c om/28413747
  22. 22. SURROUNDED BY NETWORKSThe model of a network is everywhere : cities, DNA, social relationships, Internet, etc.Question is : « What connects? » - and how.What is this strange relationship that links data to networks?
  23. 23. IDENTIFY A NETWORK Questions:MAP THE CLASSROOM AS A What is theNETWORK structure of the network? What are theWHAT CONNECTS different kinds of data we canIN THIS identify?CLASSROOM? How is the data produced? exchanged?
  24. 24. MAP YOUR OWN NETWORK ! Civil Society NGO-STK-Network Workshop in Istanbul by @graphcommons
  25. 25. CONNECTIONS Transmission Networks Something actually flows. Interaction Networks Connection is an event, with a specific time. Attribution Networks Connection is an expression of a relationship. Affiliation Networks Connection is a belonging to a group or category.
  26. 26. MAP YOUR OWN NETWORKSObjectivesIdentify an interesting network related to a specificterritoryEx: Food waste in Toulouse, actors in job research,etc.DeliveriesDraw an extensive map of this networkUse colors, dots, line, weight to represent things
  27. 27. SOME DIRECTIVESWhere to start a graph? You can start with the first thing that comes to your mind, then grow and tweak the map step by step from there.Where to stop a graph? Putting a definitive graph title and considering only the strong connections help to limit your network maps scope. Connection w eight Strong connections bring closer the two end nodes, and reveal tight clusters. In fact, strong ties are more transitive than weak ties. Collaborative mapping more fruitful and complete graphs, in fact, it is great for brain storming From
  29. 29. What is the story you want DATAto tell us? VISUALIZA TION Te l l yo u r s t o r y What is the specific focusThe example of the Arab yo u wa n t t o take out of thisSpring data set?
  30. 30. EVENTSTIMELINEArab spring: ani n t e r a ct i vetimeline ofMiddle EastprotestsS e e l i ve o nthe Guardian
  31. 31. THEREVOLUTIONSWERETWEETEDI n f o r ma t i o nF l o ws D u r i n gt h e 2 0 11Tu n i s i a n a n dE g yp t i a nR e vo l u t i onsh t t p : // www. d a na h . o r g / p r o j e c ts/IJOC-ArabSpring/
  32. 32. NEWSPAPERANALYSISSpanish frontpagen e ws p a p e ra n a l ys i s d u r i n gthe ArabS p r i ngh t t p : // www. i e c ah . o r g / we b / vi s ual/egipto-libia-s i r i a - ot r os . ht m
  33. 33. WIKIPEDIAEDITSWikipediaEdits Duringthe Middle-E a s t P r o t e s tsh t t p : // www. yo utu b e . c o m/ wa t c h? v= z 3 Wo 2 2 j l 4 Ac
  34. 34. IS THISTHE SAMESTORY?Identifyd i ff e r e n c e sand commonp o i n t s?W h at a r e k e yelements tos u c c e ss i neach piece?How has thedata beenproduced?
  35. 35. OTHER RECENTS EVENTSSandy storm - Power Cut Blackout map based on Tweets by Social Flow
  36. 36. IMPORTANCE OF DATA LOCALLY Crisis management Urban planning Transportation Transparency Participation Recollection Space design Coverage Etc. NYC Subway Map Update
  37. 37. ABOUT OPEN DATA Made publicly  Open government available (release, initiative access,  Code for America documentation…)  US political tradition Open Data is not based on only governmental accountability data  Obama campaign has Mutual economic interests
  38. 38. OPEN DATA IN FRANCE OpenData 71 Rennes Collective ActionTop-down initiative Citizen-basedPublic funding No fundingNational target Local targetCons ConsNobody use this data Illegal practicesUnsustainable Unclear programPros ProsNice data platform Data is in use
  40. 40. WORKFLOW: CREATE A DATAVIZ Objectives: extract, process, visualize, publish Tools : Web-based, softwares, languages Ben Fry, Computational Design. 2004
  41. 41. DEFINE A DATAVIZ PROJECT You may find data in weird places.A story tends to Draft, draft, draft1. begin somewhere Chose your tools based on your2. tell something (team) skills.3. end. Mind the time spent!These apply for a map, a graph, a Be kind to yourvisualization, etc. readers
  42. 42. STEP BY STEP How it should work: How it really works 1. Great, I have some nice1. Define project data/a brilliant idea ! 2. Let’s try some tools2. Find data 3. Well, I just waste 3 hours on tutorials3. Draft something visual 4. I should do something4. Define tools & time easier 5. Another 2 hours on5. Clean and refine data google 6. What was this brilliant6. Visualize idea again? 7. I should post this link7. Publish on Facebook 8. It’s late already. Let’s8. Promote just forget about this dataviz thing….
  44. 44. WEB-BASED: GOOGLE FUSION TABLESEasy maps & graph Example
  46. 46. SOFTWARE: ADOBE ILLUSTRATORGraphic design and vectors
  47. 47. SOFTWARE: TILEMILLDraw Beautiful Maps
  48. 48. SOFTWARE: GEPHI Photoshop for Network Graph
  49. 49. LANGUAGE: R Statistics on Steroids
  50. 50. LANGUAGE: PROCESSINGInteractive Awesomeness
  52. 52. DESIGN A VISUALIZATION!Based on your network map, imagine a specific storyyou want to tell or a specific idea you want toinvestigate with data.A story 5 min PresentationA titleA visualization draftA list of possible data sources & how to get it  Where to find interesting?  Can you access it? If not, imagine a way to get this data  Licensing, ownership & privacy issues
  53. 53. YOUR DATA STORYYou have to put together a 5 min presentationabout your data storyYou have to show:A storyA titleA visualization draftHow do you plan to get your data?(Some existing data, if possible)
  54. 54. COURT OF ATTENDEESFor each presentation, we split the attendees in 2 groups: pros & consThe groups should change each time (one time pros, one time cons). Pros Cons What is so great about Why is this presentation this presentation? so awful?          
  55. 55. THANKS ! SEE YOU ONLINE BYE @clemsos