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Visualising Data                   Seeing is BelievingRichard Ingram@richardjingram
Observe
Observe   Analyse
It’s worked to our adaptive advantage in competition with other animal species.
We’ve developed a greater variety of ways to   communicate and express ourselves.
Paleolithic painting of giant elkLascaux, southwestern France (c. 15,300 BC)
Upper Paleolithic painting of bisonAltamira cave, northern Spain (c. 23,000 BC – c. 33,000 BC)
Da Vinci’s Vitruvian ManPen and ink on paper (c. 1487)
Florence Nightingale’s coxcomb diagramShowed the causes of death in the British Army in the Crimea (1858)
Copernicus’s heliocentric universe diagramHe literally moved heaven and earth to draw it (c. 1543)
Ptolemy’s theory of a heliocentric universeEverything revolved around us, and that suited just fine.
On the Revolutions of the Celestial SpheresContains thousands of years worth of astrological data (c. 1543)
The data delugePower to the people
“The release of data is acornerstone of how tostrengthen the role of citizensand government, and recast therelationship be...
“Having the data is notenough.You have to show itin ways that people bothenjoy and understand.”              ~ Dr. Hans Ro...
Free tools for data extraction, exploration             and visualisation   Gephi (gephi.org)   Google Chart Tools (develo...
Tableau Public                 Lucid Charttableausoftware.com/public/    lucidchart.comGoogle Chart Tools             Many...
Gephigephi.org
OpenStreetMap       Google Fusion Tablesopenstreetmap.org   google.com/fusiontables/
ScraperWikiscraperwiki.com
Visualising data...  ...allows us to quickly explore and analysepossible relationships between things and how             ...
Visualising data...  ...can be an effective way to amplify and      simplify the communication of ourrecommendations and a...
Visualising dataThe hidden people networks
Internal author interviewsWho to speak to? Org charts can help.
Internal author interviewsHow do we reveal those hidden relationships?
SociogramVisualises the structure and patterns of group interactions.                              Connection
 (Edge)                                 Person
 (Node)
SociogramVisualises the structure and patterns of group interactions.                              Connection
 (Edge)                                 Person
 (Node)
SociogramCan reveal community clusters and calculate networkscience parameters like degrees of separation.                ...
                                  connections
 =
                                  Higher
 degree
SociogramCan reveal community clusters and calculate networkscience parameters like degrees of separation.                ...
                                  connections
 =
                                  Higher
 degree
SociogramCan reveal community clusters and calculate networkscience parameters like betweenness centrality.               ...
 network
                                                                    importance
                              =
 Higher
 betweenness
SociogramCan reveal community clusters and calculate networkscience parameters like betweenness centrality.               ...
 network
                                                                    importance
                              =
 Higher
 betweenness
Log file entries    Whoa, what in the name of thunder does this all mean?#Fields: date time c-ip cs-username s-ip s-port cs...
Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed...
Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed...
Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed...
Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed...
Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed...
Log file entries    We want to locate authors accessing the same content    within a certain timeframe.#Fields: date time c...
Log file entries    We want to locate authors accessing the same content    within a certain timeframe.2012-09-03 00:10:39 ...
Log file entries      We want to locate authors accessing the same content      within a certain timeframe.00:10:39 XXX.XXX...
Log file entriesWe return to the relative safety of the spreadsheet.
Log file entriesWe return to the relative safety of the spreadsheet.
Log file entriesWe return to the relative safety of the spreadsheet.
Gephigephi.org
Big messLet’s run a layout algorithm.
That’s better...But who are the most influential?
So, what did we learn?
We were able to easily spot the differentcommunity clusters to which people were              connected.
Visualising the log file data helped us create an              alternative org chart.
Using network science parameters we sawwhich individuals held the most influence over               multiple groups.
Visualising dataRelationships between content
For many of us, published web content is increasinglyformed of flexible modules scattered across documentsand locations, bu...
Frequently trodden pathsMapping the movement of users between web pages.
Frequently trodden pathsWeightier nodes and edges indicate key paths and stops.
Frequently trodden paths            Weightier nodes and edges indicate key paths and stops.Page
 (Node)
Frequently trodden paths            Weightier nodes and edges indicate key paths and stops.                               ...
 flow                                                           (Edge)Page
 (Node)
Frequently trodden paths            Weightier nodes and edges indicate key paths and stops.                               ...
 flow                                                           (Edge)Page
 (Node)
Frequently trodden paths            Weightier nodes and edges indicate key paths and stops.                               ...
 flow                                                           (Edge)Page
 (Node)
Dorian Taylordoriantaylor.org
Web server logsStore information on each request we make.     Referring Resource                New request       (Previou...
Web server logs    Haven’t we been here before? Not quite.XX.XXX.XXX.86 [30/Aug/2012:11:09:27 +0100] GET /contact-us/ HTTP...
Web server logs: a closer look  Important elements in bold: client ip address, next  page and previous page:XX.XXX.XXX.86 ...
Web server logs: a closer look  Important elements in bold: client ip address, next  page and previous page:XX.XXX.XXX.86 ...
Web server logs: a closer look  Important elements in bold: client ip address, next  page and previous page:XX.XXX.XXX.86 ...
Web server logs: a closer look  Important elements in bold: client ip address, next  page and previous page:XX.XXX.XXX.86 ...
Web server logsCleaning up the data.Most non-human activity can be removed by searchingfor:     Bingbot (google.com/bot.ht...
Web server logsExtract the URL data and add to a spreadsheet.
Web server logsExtract the URL data and add to a spreadsheet.
Web server logsExtract the URL data and add to a spreadsheet.
Cross Country Coaches The entirely fictitious UK-wide bus and coach operator.   Airports                               Attr...
Cross Country Coaches The entirely fictitious UK-wide bus and coach operator.   Airports                                  A...
Gephigephi.org
An even bigger messLet’s run a layout algorithm.
That’s better...Let’s pick out the influential pages.
Export node dataThis will come in handy later
So, what did we learn?
Visualising the web server log data providedus with a different perspective of the stories         we’re telling our audie...
Filtering the data took away the visualcomplexity and revealed to us the key paths                 and stops.
Exporting the node data generated a page-  level inventory of the most frequently             accessed content.
Visualising dataPlaying with numbers
Utilising internal dataBringing data from your own investigations into play.
Exported node tableManually feed in data from your own investigations.
Exported node tableManually feed in data from your own investigations.
Exported node tableManually feed in data from your own investigations.
Exported node tableManually feed in data from your own investigations.
Exported node tableManually feed in data from your own investigations.
Exported node tableManually feed in data from your own investigations.
Exported node tableAutomatically feed in data from your own investigations.       Exported node table                     ...
Google Fusion Tablesgoogle.com/fusiontables/
What can we do with this additional data?
Tableau Publictableausoftware.com/public/
Q. Is there a perceived difference in thequality of content maintained in-house and         through external partners?
Cross Country Coaches The entirely fictitious UK-wide bus and coach operator.   Airports                               Attr...
Cross Country Coaches The entirely fictitious UK-wide bus and coach operator.   Airports                               Attr...
Utilising external dataBringing public data into play.
VisitBritain.orgDomestic tourism statistics
Regional breakdown of tourism valueOnly available in handy PDF format [!].
PDF to Excel Online    Zamzarpdftoexcelonline.com   zamzar.com
Google Fusion Tablesgoogle.com/fusiontables/
Priorities?
So, what did we learn?
Furnishing our exported node table withdata from our own investigations allowed for        deeper dives into our sample.
Importing external data provided us with    possible new angles and ideas.
Adding interactive elements helped usdevelop a basic narrative around our data.
Visualising data  You can do it!
Don’t be afraid of data. Treat it as something         to play with and explore.
Dont worry about not having all theanswers. Uncertainly can be a great way of          raising new questions.
Create something that could be of use toothers and you might find you get help and            cooperation back.
Thank you.Richard Ingram@richardjingram
Recommended readingSemiology of Graphics: Diagrams, Networks, Mapsby Jacques BertinThe Data Journalism Handbook FREE!edite...
Image sources and creditsMount Teide (palmstorys.com/bilder/Englishversions/Tenerife.html)Stratovolcano cross-section by W...
Image sources and credits cont...On the revolutions of the celestial spheres (http://ads.harvard.edu/books/1543droc.book/)...
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
Visualising data: Seeing is Believing - CS Forum 2012
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Visualising data: Seeing is Believing - CS Forum 2012

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When patterns and connections are revealed between numbers, content and people that might otherwise be too abstract or scattered to be grasped, we’re able to make better sense of where we are, what it might mean and what needs to be done.

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Visualising data: Seeing is Believing - CS Forum 2012

  1. Visualising Data Seeing is BelievingRichard Ingram@richardjingram
  2. Observe
  3. Observe Analyse
  4. It’s worked to our adaptive advantage in competition with other animal species.
  5. We’ve developed a greater variety of ways to communicate and express ourselves.
  6. Paleolithic painting of giant elkLascaux, southwestern France (c. 15,300 BC)
  7. Upper Paleolithic painting of bisonAltamira cave, northern Spain (c. 23,000 BC – c. 33,000 BC)
  8. Da Vinci’s Vitruvian ManPen and ink on paper (c. 1487)
  9. Florence Nightingale’s coxcomb diagramShowed the causes of death in the British Army in the Crimea (1858)
  10. Copernicus’s heliocentric universe diagramHe literally moved heaven and earth to draw it (c. 1543)
  11. Ptolemy’s theory of a heliocentric universeEverything revolved around us, and that suited just fine.
  12. On the Revolutions of the Celestial SpheresContains thousands of years worth of astrological data (c. 1543)
  13. The data delugePower to the people
  14. “The release of data is acornerstone of how tostrengthen the role of citizensand government, and recast therelationship between the two.” ~ Sir Tim Berners-Lee Interview with The Guardian (2010)
  15. “Having the data is notenough.You have to show itin ways that people bothenjoy and understand.” ~ Dr. Hans Rosling The Joy Of Stats (BBC Television, 2011)
  16. Free tools for data extraction, exploration and visualisation Gephi (gephi.org) Google Chart Tools (developers.google.com/chart/) Google Fusion Tables (google.com/fusiontables/) Google Refine (code.google.com/p/google-refine/) Lucid Chart (lucidchart.com) ManyEyes (www-958.ibm.com) OpenStreetMap (openstreetmap.org) ScraperWiki (scraperwiki.com) Tableau Public (tableausoftware.com/public/)
  17. Tableau Public Lucid Charttableausoftware.com/public/ lucidchart.comGoogle Chart Tools ManyEyesdevelopers.google.com/chart/ www-958.ibm.com
  18. Gephigephi.org
  19. OpenStreetMap Google Fusion Tablesopenstreetmap.org google.com/fusiontables/
  20. ScraperWikiscraperwiki.com
  21. Visualising data... ...allows us to quickly explore and analysepossible relationships between things and how they vary together.
  22. Visualising data... ...can be an effective way to amplify and simplify the communication of ourrecommendations and arguments to other audiences.
  23. Visualising dataThe hidden people networks
  24. Internal author interviewsWho to speak to? Org charts can help.
  25. Internal author interviewsHow do we reveal those hidden relationships?
  26. SociogramVisualises the structure and patterns of group interactions. Connection
  27.  (Edge) Person
  28.  (Node)
  29. SociogramVisualises the structure and patterns of group interactions. Connection
  30.  (Edge) Person
  31.  (Node)
  32. SociogramCan reveal community clusters and calculate networkscience parameters like degrees of separation. More
  33.   connections
  34.  =
  35.   Higher
  36.  degree
  37. SociogramCan reveal community clusters and calculate networkscience parameters like degrees of separation. More
  38.   connections
  39.  =
  40.   Higher
  41.  degree
  42. SociogramCan reveal community clusters and calculate networkscience parameters like betweenness centrality. Higher
  43.  network
  44.   importance
  45.   =
  46.  Higher
  47.  betweenness
  48. SociogramCan reveal community clusters and calculate networkscience parameters like betweenness centrality. Higher
  49.  network
  50.   importance
  51.   =
  52.  Higher
  53.  betweenness
  54. Log file entries Whoa, what in the name of thunder does this all mean?#Fields: date time c-ip cs-username s-ip s-port cs-method cs-uri-stem cs-uri-querysc-status cs(User-Agent)2012-09-03 00:10:19 XXX.XXX.X.211 clarke_n XXX.XXX.X.103 80 GET /admin/pages/content.php?id=84 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:10:39 XXX.XXX.X.17 olson_b XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:11:12 XXX.XXX.X.40 zajac_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:20 XXX.XXX.X.29 arecchi_f XXX.XXX.X.103 80 GET /admin/pages/content.php?id=168 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:50 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:52 XXX.XXX.X.178 harding_a XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:14:38 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=73 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  55. Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed:2012-09-03 00:09:53 XXX.XXX.X.104russell_g XXX.XXX.X.103 80 GET /admin/pages/content.php?id=12Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  56. Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed:2012-09-03 00:09:53 XXX.XXX.X.104russell_g XXX.XXX.X.103 80 GET /admin/pages/content.php?id=12Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  57. Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed:2012-09-03 00:09:53 XXX.XXX.X.104russell_g XXX.XXX.X.103 80 GET /admin/pages/content.php?id=12Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  58. Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed:2012-09-03 00:09:53 XXX.XXX.X.104russell_g XXX.XXX.X.103 80 GET /admin/pages/content.php?id=12Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  59. Log file entries: a closer lookImportant elements in bold: date/time stamp,client ip address, username, and contentaccessed:2012-09-03 00:09:53 XXX.XXX.X.104russell_g XXX.XXX.X.103 80 GET /admin/pages/content.php?id=12Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  60. Log file entries We want to locate authors accessing the same content within a certain timeframe.#Fields: date time c-ip cs-username s-ip s-port cs-method cs-uri-stem cs-uri-querysc-status cs(User-Agent)2012-09-03 00:10:19 XXX.XXX.X.211 clarke_n XXX.XXX.X.103 80 GET /admin/pages/content.php?id=84 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:10:39 XXX.XXX.X.17 olson_b XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:11:12 XXX.XXX.X.40 zajac_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:20 XXX.XXX.X.29 arecchi_f XXX.XXX.X.103 80 GET /admin/pages/content.php?id=168 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:50 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:52 XXX.XXX.X.178 harding_a XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:14:38 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=73 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  61. Log file entries We want to locate authors accessing the same content within a certain timeframe.2012-09-03 00:10:39 XXX.XXX.X.17 olson_b XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:11:12 XXX.XXX.X.40 zajac_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:50 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)2012-09-03 00:13:52 XXX.XXX.X.178 harding_a XXX.XXX.X.103 80 GET /admin/pages/content.php?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-ac7+i686;+Nav)
  62. Log file entries We want to locate authors accessing the same content within a certain timeframe.00:10:39 XXX.XXX.X.17 olson_b XXX.XXX.X.103 80 GET /admin/page?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-av)00:11:12 XXX.XXX.X.40 zajac_s XXX.XXX.X.103 80 GET /admin/page?id=37 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-av)00:13:50 XXX.XXX.X.107 chalmers_s XXX.XXX.X.103 80 GET /admin/?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-av)00:13:52 XXX.XXX.X.178 harding_a XXX.XXX.X.103 80 GET /admin/p?id=174 Cmd=contents 200 Mozilla/4.76+[en]+(X11;+U;+Linux+2.4.9-av)
  63. Log file entriesWe return to the relative safety of the spreadsheet.
  64. Log file entriesWe return to the relative safety of the spreadsheet.
  65. Log file entriesWe return to the relative safety of the spreadsheet.
  66. Gephigephi.org
  67. Big messLet’s run a layout algorithm.
  68. That’s better...But who are the most influential?
  69. So, what did we learn?
  70. We were able to easily spot the differentcommunity clusters to which people were connected.
  71. Visualising the log file data helped us create an alternative org chart.
  72. Using network science parameters we sawwhich individuals held the most influence over multiple groups.
  73. Visualising dataRelationships between content
  74. For many of us, published web content is increasinglyformed of flexible modules scattered across documentsand locations, but they are seldom read that way.
  75. Frequently trodden pathsMapping the movement of users between web pages.
  76. Frequently trodden pathsWeightier nodes and edges indicate key paths and stops.
  77. Frequently trodden paths Weightier nodes and edges indicate key paths and stops.Page
  78.  (Node)
  79. Frequently trodden paths Weightier nodes and edges indicate key paths and stops. User
  80.  flow (Edge)Page
  81.  (Node)
  82. Frequently trodden paths Weightier nodes and edges indicate key paths and stops. User
  83.  flow (Edge)Page
  84.  (Node)
  85. Frequently trodden paths Weightier nodes and edges indicate key paths and stops. User
  86.  flow (Edge)Page
  87.  (Node)
  88. Dorian Taylordoriantaylor.org
  89. Web server logsStore information on each request we make. Referring Resource New request (Previous page) (Next page) Source: doriantaylor.com/visualizing-paths-through-the-web
  90. Web server logs Haven’t we been here before? Not quite.XX.XXX.XXX.86 [30/Aug/2012:11:09:27 +0100] GET /contact-us/ HTTP/1.1 200 14728 -http://www.crosscountrycoaches.com/destinations/ Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100] GET / HTTP/1.1 200 12007 - http://www.crosscountrycoaches.com/destinations/ Mozilla/5.0 (Windows NT 6.0; rv:14.0)Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100] GET /contact-us/view-your-ticket/ HTTP/1.1200 14084 - http://www.crosscountrycoaches.com/ Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:37 +0100] GET /services/ HTTP/1.1 200 13428 -http://www.crosscountrycoaches.com/ Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:38 +0100] GET /login/ HTTP/1.1 200 17284 - http://www.crosscountrycoaches.com/services/ Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100] GET /reprint-your-ticket/ HTTP/1.1 20027788 - http://www.crosscountrycoaches.com/services/ Mozilla/5.0 (Windows NT 6.0;rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100] GET /services/terms-and-conditions/ HTTP/1.1 200 11638 - http://www.crosscountrycoaches.com/reprint-your-ticket/ Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1
  91. Web server logs: a closer look Important elements in bold: client ip address, next page and previous page:XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100]GET /contact-us/view-your-ticket/ HTTP/1.1 20014084 - http://www.crosscountrycoaches.com/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100]GET /reprint-your-ticket/ HTTP/1.1 200 27788 -http://www.crosscountrycoaches.com/services/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1
  92. Web server logs: a closer look Important elements in bold: client ip address, next page and previous page:XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100]GET /contact-us/view-your-ticket/ HTTP/1.1 20014084 - http://www.crosscountrycoaches.com/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100]GET /reprint-your-ticket/ HTTP/1.1 200 27788 -http://www.crosscountrycoaches.com/services/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1
  93. Web server logs: a closer look Important elements in bold: client ip address, next page and previous page:XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100]GET /contact-us/view-your-ticket/ HTTP/1.1 20014084 - http://www.crosscountrycoaches.com/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100]GET /reprint-your-ticket/ HTTP/1.1 200 27788 -http://www.crosscountrycoaches.com/services/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1
  94. Web server logs: a closer look Important elements in bold: client ip address, next page and previous page:XX.XXX.XXX.86 [30/Aug/2012:11:09:29 +0100]GET /contact-us/view-your-ticket/ HTTP/1.1 20014084 - http://www.crosscountrycoaches.com/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1XX.XXX.XXX.86 [30/Aug/2012:11:09:42 +0100]GET /reprint-your-ticket/ HTTP/1.1 200 27788 -http://www.crosscountrycoaches.com/services/Mozilla/5.0 (Windows NT 6.0; rv:14.0) Gecko/20100101 Firefox/14.0.1
  95. Web server logsCleaning up the data.Most non-human activity can be removed by searchingfor: Bingbot (google.com/bot.html) Googlebot (bing.com/bingbot.htm) Any mentions of ‘bots’, ‘spiders’, and ‘crawlers’
  96. Web server logsExtract the URL data and add to a spreadsheet.
  97. Web server logsExtract the URL data and add to a spreadsheet.
  98. Web server logsExtract the URL data and add to a spreadsheet.
  99. Cross Country Coaches The entirely fictitious UK-wide bus and coach operator. Airports Attractions Holiday camps andDirect to terminal amusement parks Day trips EventsTowns and cities Sports and music
  100. Cross Country Coaches The entirely fictitious UK-wide bus and coach operator. Airports Attractions Holiday camps andDirect to terminal amusement parks Journey Planner Purchasing e-tickets Day trips EventsTowns and cities Sports and music
  101. Gephigephi.org
  102. An even bigger messLet’s run a layout algorithm.
  103. That’s better...Let’s pick out the influential pages.
  104. Export node dataThis will come in handy later
  105. So, what did we learn?
  106. Visualising the web server log data providedus with a different perspective of the stories we’re telling our audiences.
  107. Filtering the data took away the visualcomplexity and revealed to us the key paths and stops.
  108. Exporting the node data generated a page- level inventory of the most frequently accessed content.
  109. Visualising dataPlaying with numbers
  110. Utilising internal dataBringing data from your own investigations into play.
  111. Exported node tableManually feed in data from your own investigations.
  112. Exported node tableManually feed in data from your own investigations.
  113. Exported node tableManually feed in data from your own investigations.
  114. Exported node tableManually feed in data from your own investigations.
  115. Exported node tableManually feed in data from your own investigations.
  116. Exported node tableManually feed in data from your own investigations.
  117. Exported node tableAutomatically feed in data from your own investigations. Exported node table + Content inventory = Extended node table
  118. Google Fusion Tablesgoogle.com/fusiontables/
  119. What can we do with this additional data?
  120. Tableau Publictableausoftware.com/public/
  121. Q. Is there a perceived difference in thequality of content maintained in-house and through external partners?
  122. Cross Country Coaches The entirely fictitious UK-wide bus and coach operator. Airports Attractions Holiday camps andDirect to terminal amusement parks Day trips EventsTowns and cities Sports and music
  123. Cross Country Coaches The entirely fictitious UK-wide bus and coach operator. Airports Attractions Holiday camps andDirect to terminal amusement parks Day trips EventsTowns and cities Sports and music
  124. Utilising external dataBringing public data into play.
  125. VisitBritain.orgDomestic tourism statistics
  126. Regional breakdown of tourism valueOnly available in handy PDF format [!].
  127. PDF to Excel Online Zamzarpdftoexcelonline.com zamzar.com
  128. Google Fusion Tablesgoogle.com/fusiontables/
  129. Priorities?
  130. So, what did we learn?
  131. Furnishing our exported node table withdata from our own investigations allowed for deeper dives into our sample.
  132. Importing external data provided us with possible new angles and ideas.
  133. Adding interactive elements helped usdevelop a basic narrative around our data.
  134. Visualising data You can do it!
  135. Don’t be afraid of data. Treat it as something to play with and explore.
  136. Dont worry about not having all theanswers. Uncertainly can be a great way of raising new questions.
  137. Create something that could be of use toothers and you might find you get help and cooperation back.
  138. Thank you.Richard Ingram@richardjingram
  139. Recommended readingSemiology of Graphics: Diagrams, Networks, Mapsby Jacques BertinThe Data Journalism Handbook FREE!edited by Jonathan Gray, Liliana Bounegru, and Lucy ChambersDesigning Data Visualizationsby Noah Iliinsky and Julie SteeleInformation is Beautifulby David McCandlessEnvisioning Informationby Edward R. Tufte
  140. Image sources and creditsMount Teide (palmstorys.com/bilder/Englishversions/Tenerife.html)Stratovolcano cross-section by Woudloper (http://commons.wikimedia.org/wiki/File:Stratovolcano_cross-section.svg)The Expression of the Emotions in Man and Animals (various) (http://commons.wikimedia.org/wiki/The_Expression_of_the_Emotions_in_Man_and_Animals)Paleolithic painting of giant elk (http://commons.wikimedia.org/wiki/File:Lascaus,_Megaloceros.jpg)Upper Paleolithic painting of bison by Ramessos (http://commons.wikimedia.org/wiki/File:AltamiraBison.jpg)Vitruvian Man (http://commons.wikimedia.org/wiki/File:Da_Vinci_Vitruve_Luc_Viatour.jpg)Diagram of the causes of mortality in the army in the East (http://commons.wikimedia.org/wiki/File:Nightingale-mortality.jpg)
  141. Image sources and credits cont...On the revolutions of the celestial spheres (http://ads.harvard.edu/books/1543droc.book/)Geocentric model of the solar system (http://commons.wikimedia.org/wiki/File:Ptolemy_Sky.jpg)Tim Berners-Lee by Silvio Tanaka (http://commons.wikimedia.org/wiki/File:Tim_Berners-Lee_CP.jpg)Hans Rosling (http://novartisfoundation.org/platform/content/element/3967/2336.jpg)Nicolaus Copernicus (http://commons.wikimedia.org/wiki/File:Nikolaus_Kopernikus.jpg)Isaac Newton (http://commons.wikimedia.org/wiki/File:Sir_Isaac_Newton_by_Sir_Godfrey_Kneller,_Bt.jpg)

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