An Introduction to Structured       Data Presentation                  New Perspectives on Old Data                       ...
Objective      To appreciate the variety of structured data   presentation tools available to digital humanities   scholar...
Agenda  Data Presentation versus Data Analysis?  The Readings    Exhibit Thesis    The Data Vis Challenge to the Humanitie...
The Two Faces of Data Visualisation   One of the keys to good visualization is understanding   what your immediate (and lo...
Information Visualisation:Challenge for the Humanities   To use the vast stores of digitised data we are   collecting we n...
The Challenges   Developing new genres for complex info   presentation   creating a literacy that has same rigour and   ri...
The Opportunity   Balance complexity with conciseness   Balance accuracy with essence   Speak authoritatively, yet inspire...
A Short History   Originated in Computer Science   Disseminated into broader scientific realm   A late comer to the humanit...
William Playfair (1758 - 1823)   bar chart   pie chart   time series                            This is a file from the Wik...
John Snow (1813 - 1858)   Dot Plot   Spatial Analysis                          This is a file from the Wikimedia Commons
Charles Minard (1781 - 1870)   Flow Diagram   Multi-Vector Information Visualisation                                   Thi...
Tools for collection are far more successful to date              than those for exploration
New Influences  Simulation - 3D What if?  Monitor - Real time data  Collabouration - Many Eyes
The Challenges to the Use ofVisualisation   Too Easy to confuse, miscommunicate or   downright lie   Break or lack basic v...
Structured Data Presentation Tools(a tiny subset)   Webservices              Frameworks     TimeFlow                Gephi ...
TimeFlow
Google FusionTables
Many Eyes
Hands-On Exercise: Simile Exhibit
Looking at Exhibit
Setup and Preparation   Do Not Use Safari - Firefox or Chrome should be              X   fine   You can find instructions at...
Background on ExhibitExhibit was developed at MIT to provide alightweight framework for the presentation,searching and fac...
So What?...   Little programming (JavaScript Template);   No database (JSON text);   a series of useful ‘instantly interac...
Background  http://www.simile-widgets.org/exhibit/  A couple examples…    Canadian Network for Economic History    Comox V...
Exhibit in a Nutshell
The Simplest Exhibit<html>!   <head>!   !      <title>MIT Nobel Prize Winners</title>!   !      <link href="nobelists.js" ...
The Data    {"items" : [               {     type :                  "Nobelist",                     label :              ...
The Simplest View
Add Faceted Browsing   Explore data in   context   Filter data by   attributes
Faceted Browsing Code<div ex:role="facet" ex:expression=".discipline" ex:facetLabel="Discipline"></div><div ex:role="facet...
Add Search and Sort
Search Code <div ex:role="facet" ex:facetClass="TextSearch"></div>
Add a Table View
Table Code <div ex:role="exhibit-view” ex:viewClass="Exhibit.TabularView” ex:columns=".label, .imageURL, .discipline, .nob...
Add a Timeline
Timeline Code   <script src="http://static.simile.mit.edu/exhibit/   extensions-2.0/time/time-extension.js"    type="text/...
Add a Map View
Wrapup: Exhibit   Pros                    Cons     Simple                  Limited Scalability     Lightweight            ...
Moving Beyond with Exhibit   Ensemble Project Advanced Tutorial:   http://ensemble.ljmu.ac.uk/q/calbooklet
OMEKA for Curated Collections   http://omeka.net
Omeka Basics                                                           OAI/PMHExhibitMetadata                 Page        ...
OMEKA  http://iridium.omeka.net/exhibits/show/  carlingford/day1  http://www.omeka.net/dashboard  Omeka.org versus Omeka.n...
Where to go next   http://datajournalism.stanford.edu/   Bamboo - DIRT (Digital Research Toolkit)   Timeline Tools   Visua...
Academic Visualisation?There’s lots of published papers out there...what can you do with them?                            ...
The Life on An Idea through Citations
Data Visualisation Lessons from Tufte 1.   Show the Data 2.   Provoke Thought about the Subject at Hand 3.   Avoid Distort...
What Visual Techniques Exist?   Connecting your data with the right visualisation   What is your message?   How do we know...
What Visual Techniques Exist? Connecting your data with the right visualisation
Thanks for your attention
Structured Data Presentation
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Structured Data Presentation

  1. 1. An Introduction to Structured Data Presentation New Perspectives on Old Data Shawn Day Digital Humanities Observatory 14 November 2012http://www.slideshare.net/shawnday/structured-data-presentation
  2. 2. Objective To appreciate the variety of structured data presentation tools available to digital humanities scholars and to be able to judge between them.
  3. 3. Agenda Data Presentation versus Data Analysis? The Readings Exhibit Thesis The Data Vis Challenge to the Humanities Products to be have an awareness of Hands On Install and Config Exhibit OMEKA?
  4. 4. The Two Faces of Data Visualisation One of the keys to good visualization is understanding what your immediate (and longer term) goals are. Are you visualizing data to understand what’s in it, or are you trying to communicate meaning to others? You - Visualisation for Data Analysis Others - Visualisation for Presentation
  5. 5. Information Visualisation:Challenge for the Humanities To use the vast stores of digitised data we are collecting we need to develop a digital fluency Access Exploration Visualisation Analysis Collabouration
  6. 6. The Challenges Developing new genres for complex info presentation creating a literacy that has same rigour and richness as current scholarship expanding text-based pedagogy to include simulation, animation and spatial and geographic representation
  7. 7. The Opportunity Balance complexity with conciseness Balance accuracy with essence Speak authoritatively, yet inspire exploration and personal insight
  8. 8. A Short History Originated in Computer Science Disseminated into broader scientific realm A late comer to the humanities Tufte: concise - clear - accurate
  9. 9. William Playfair (1758 - 1823) bar chart pie chart time series This is a file from the Wikimedia Commons.
  10. 10. John Snow (1813 - 1858) Dot Plot Spatial Analysis This is a file from the Wikimedia Commons
  11. 11. Charles Minard (1781 - 1870) Flow Diagram Multi-Vector Information Visualisation This is a file from the Wikimedia Commons
  12. 12. Tools for collection are far more successful to date than those for exploration
  13. 13. New Influences Simulation - 3D What if? Monitor - Real time data Collabouration - Many Eyes
  14. 14. The Challenges to the Use ofVisualisation Too Easy to confuse, miscommunicate or downright lie Break or lack basic visual design principles Fail to understand the data, the audience or the problem being solved Fail to appreciate the visceral or emotional power of graphics Lack of technical skills in this domain
  15. 15. Structured Data Presentation Tools(a tiny subset) Webservices Frameworks TimeFlow Gephi Google Fusion Tables Exhibit (Exercise) Many Eyes GraphViz Prefuse Hosted D3 Omeka (Omeka) Processing
  16. 16. TimeFlow
  17. 17. Google FusionTables
  18. 18. Many Eyes
  19. 19. Hands-On Exercise: Simile Exhibit
  20. 20. Looking at Exhibit
  21. 21. Setup and Preparation Do Not Use Safari - Firefox or Chrome should be X fine You can find instructions at: http://myeye.ie/ftp1/ exhibit/recipe.txt Need to copy datafiles: http://myeye.ie/ftp1/exhibit/nobelists.js?action=raw http://myeye.ie/ftp1/exhibit/index1.html
  22. 22. Background on ExhibitExhibit was developed at MIT to provide alightweight framework for the presentation,searching and faceted browsing of digital collections.Exhibit lets you easily create web pages withadvanced text search and filtering functionalities,with interactive maps, timelines, and othervisualizations
  23. 23. So What?... Little programming (JavaScript Template); No database (JSON text); a series of useful ‘instantly interactive’ visualisations.
  24. 24. Background http://www.simile-widgets.org/exhibit/ A couple examples… Canadian Network for Economic History Comox Valley Crime Stoppers Research at the DHO DHO: Discovery
  25. 25. Exhibit in a Nutshell
  26. 26. The Simplest Exhibit<html>! <head>! ! <title>MIT Nobel Prize Winners</title>! ! <link href="nobelists.js" type="application/json" rel="exhibit/data" />! ! <script src=http://static.simile.mit.edu/exhibit/api-2.0/exhibit-api.js type="text/javascript"></ script>! <style></style>! </head>! <body>! ! <h1>MIT Nobel Prize Winners</h1>! ! <table width="100%”>! ! <tr valign="top”>! ! <td ex:role="viewPanel”><div ex:role="view"></div></td><td width="25%”>browsing controls here… </ td></tr></table></body></html>
  27. 27. The Data {"items" : [ { type : "Nobelist", label : "Burton Richter",! ! ! latlng: "42.359089,-71.093412", discipline : "Physics", shared : "yes", "last-name" : "Richter", "nobel-year" : "1976", relationship : "alumni", "co-winner" : "Samuel C.C. Ting", "relationship-detail" : "MIT S.B. 1952, Ph.D. 1956", imageURL : "http://nobelprize.org/nobel_prizes/ physics/laureates/1976/richter_thumb.jpg" }, ……… ]}
  28. 28. The Simplest View
  29. 29. Add Faceted Browsing Explore data in context Filter data by attributes
  30. 30. Faceted Browsing Code<div ex:role="facet" ex:expression=".discipline" ex:facetLabel="Discipline"></div><div ex:role="facet" ex:expression=".relationship" ex:facetLabel="Relationship"></div><div ex:role="facet" ex:expression=".shared" ex:facetLabel="Shared?"></div><div ex:role="facet" ex:expression=".deceased" ex:facetLabel="Deceased?"></div>
  31. 31. Add Search and Sort
  32. 32. Search Code <div ex:role="facet" ex:facetClass="TextSearch"></div>
  33. 33. Add a Table View
  34. 34. Table Code <div ex:role="exhibit-view” ex:viewClass="Exhibit.TabularView” ex:columns=".label, .imageURL, .discipline, .nobel- year, .relationship-detail” ex:columnLabels="name, photo, discipline, year, relationship with MIT” ex:columnFormats="list, image, list, list, list” ex:sortColumn="3” ex:sortAscending="false"> </div>
  35. 35. Add a Timeline
  36. 36. Timeline Code <script src="http://static.simile.mit.edu/exhibit/ extensions-2.0/time/time-extension.js" type="text/javascript"></script> +<div ex:role="view" ex:viewClass="Timeline" ex:start=".nobel-year" ex:colorKey=".discipline"></div>
  37. 37. Add a Map View
  38. 38. Wrapup: Exhibit Pros Cons Simple Limited Scalability Lightweight Some cross-browser No server required issues A host of Restrictions on Look visualisations and Feel Embeddable in other Extensive systems - customisation means ExhibitPress getting into code Here comes Exhibit 3
  39. 39. Moving Beyond with Exhibit Ensemble Project Advanced Tutorial: http://ensemble.ljmu.ac.uk/q/calbooklet
  40. 40. OMEKA for Curated Collections http://omeka.net
  41. 41. Omeka Basics OAI/PMHExhibitMetadata Page CSVSection PageSection Page etc... PageCollection(s) Metadata Tag(s) Type Metadata Tag(s) Type Metadata Tag(s) TypeItem Item Item Representations Representations Representations
  42. 42. OMEKA http://iridium.omeka.net/exhibits/show/ carlingford/day1 http://www.omeka.net/dashboard Omeka.org versus Omeka.net Sign-Up at: http://www.omeka.net
  43. 43. Where to go next http://datajournalism.stanford.edu/ Bamboo - DIRT (Digital Research Toolkit) Timeline Tools Visualisation in Education Visual Complexity
  44. 44. Academic Visualisation?There’s lots of published papers out there...what can you do with them? http://www.autodeskresearch.com/projects/citeology
  45. 45. The Life on An Idea through Citations
  46. 46. Data Visualisation Lessons from Tufte 1. Show the Data 2. Provoke Thought about the Subject at Hand 3. Avoid Distorting the Data 4. Present Many Numbers in a Small Space 5. Make Large Datasets Coherent 6. Encourage Eyes to Compare Data 7. Reveal Data at Several Levels of Detail 8. Serve a Reasonably Clear Purpose 9. Be Closely Integrated with Statistical and Verbal Descriptions of the Dataset
  47. 47. What Visual Techniques Exist? Connecting your data with the right visualisation What is your message? How do we know what we might use? Start with your Exploratory/Research/Analytical Environment (last seminar) How do visuals fit into your narrative?
  48. 48. What Visual Techniques Exist? Connecting your data with the right visualisation
  49. 49. Thanks for your attention

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