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Dmdh workshop #6

  1. 1. May 4th: Available Tools: Free, Cheap, and Premium (and how to navigate choosing between them)
  2. 2. While there are many different digital platforms you can use, in the end, all tools are visualization tools.
  3. 3. When you choose a tool, you’re choosing how you want to see your data.
  4. 4. Important Considerations
  5. 5. Licensing • Did you pay for the tool/platform that you want to use? • Did you have to pay for it once, or do you have to renew it annually? • How will your users interact with the platform?
  6. 6. Licensing, continued • Case 1: • You probably produce many documents in Microsoft Word, and send them to other people (or print them out to give to people.) • Case 2: • You produce documents in Microsoft Word, and you want other people to edit those documents with you, using Microsoft Word’s collaborative editing features.
  7. 7. Ownership • In what space was your project built? • Your personal site? • The university’s webspace? • Where is the project supposed to “live” after completion? • Where did the funding for the project come from?
  8. 8. Platform Support & Lifespan • Who made the platform you want to use? • Is it open source? • What kind of user support is available? • How is maintenance of the platform (not your project, but the platform itself) funded? (Grants? Donations?) • Is it new and shiny? Or old and reliable?
  9. 9. Who is your audience? • You • Specialized scholarly audience • Other digital/multimodal scholars • Students • The general public
  10. 10. Flexibility • Can you import your data (i.e., prepare it outside of the platform?) • Can you export your data? • In a way that allows other people to see what the platform does? • In a way that allows you to use the data in other platforms?
  11. 11. Robustness • For a platform to be “robust,” it needs to be able to handle unexpected input or actions in a way that allows the user to fix the problem and continue with minimal fuss. • While this definition of robust is generally agreed upon, the precise standards for robustness are essentially subjective.
  12. 12. Is it robust?• If something goes wrong, does the platform return a blank screen, or crash entirely? • If something goes wrong, does the platform provide an error message that allows you to figure out what part of your input caused the problem? NOT ROBUST! ROBUST!
  13. 13. Hosting • If a platform is web-based (sometimes referred to as “server-side”), then someone else is making sure that the platform works, and gets upgraded. • Pro: you don’t have to install or maintain it. • Con: you’re dependent on being online for the platform to work. • If the platform is locally hosted (sometimes referred to as “client-side”), then it’s on your computer. • Pro: you don’t have to be online! (this is handy anytime you’re demonstrating your project outside of your home institution) • Con: you may need to have more programming skills to install and maintain the platform on your own machine/server.
  14. 14. Visibility • Some platforms may allow you to use them for free, provided you make your data public: • Are you concerned about other people accessing your data? • Could your data be considered someone else’s property?
  15. 15. The choices you make in choosing tools are an essential part of your documentation.
  16. 16. On with the tools! • Data visualization (ManyEyes) • Mapping/GIS tools(Community Walk, Google Maps, Google Earth,ArcGIS) • MIT Simile • Display (Scalar, Omeka) • Project Management (Pivotal Tracker)
  17. 17. Many Eyes • Free text and numerical data visualization engine, made by IBM • http://www- • Usable on Mac/PC, but only in browsers that run Java (i.e., not Google Chrome)
  18. 18. Pros • Easy to try out different visualizations using the same text • Easy to upload datasets • Allows visualizations to be saved and emailed to other people who can view them without a login • Access to everyone else’s data set • Only accessible online • No export capability • Dependent on Java • No privacy: your data is everyone’s data Cons
  19. 19. Mapping Tools!
  20. 20. Community Walk: Free (Ad Revenue)
  21. 21. Pros • Free! • Web-based • Reasonable range of functionality • Allows multiple maps to be created in one account • Unique site login can be shared without compromising online persona • Can’t block ads • Awkward User Interface (UI) Cons
  22. 22. Google Maps: Free
  23. 23. Pros • Free! • Web-based • Unobtrusive ads • Reasonable range of functionality • Linked to Google Account for easy portability/access • Designed for navigation • Linked to existing Google Account • Lack of functionality • Dependent on Google maintaining the tool Cons
  24. 24. Google Earth: Free (Paid Upgrade: Premium)
  25. 25. Pros • Free! • No ads • Historical map integration • Robust functionality • May need to pay for pro- account, depending on your goals • Not web-based • May be more complex than you need • Dependent on Google maintaining it Cons
  26. 26. ArcGIS (Super-Premium)
  27. 27. Pros • It does EVERYTHING • No ads • Robust functionality • Expensive! • Not web-based Cons
  28. 28. MIT Simile Widgets (Free)
  29. 29. Pros • Free! • Open access for easy collaboration • Web-based or locally hosted • Unique (no current rivals) • Highly customizable • Data can be stored in GoogleDoc • Open access and always in development (stability issues) • Requires HTML, more programming skill for customization • Documentation is spotty Cons
  30. 30. Scalar (Free)
  31. 31. Pros • Free! • Web-based • Unique in its capability for creating non-linear paths • Customizable • Supported by investment and use of multiple organizations • It’s in open beta, and still new • It requires you to host material on the Scalar website • Documentation is not yet extensive • Dependent on continued funding Cons
  32. 32. Pivotal Tracker (Free/Cheap)
  33. 33. Pros • Free (for public projects, and non-profit/academic projects) • Supported by paid users • Customizable • Sophisticated, friendly user- interface • iOS compatible • It’s project management software -- not a project platform • Dependent on your willingness to make your project public, continued funding, or academic/nonprofit status Cons
  34. 34. Just a few of the many places you can check for tools: re/
  35. 35. Using (new) digital tools means that you will inevitably need help at some point.
  36. 36. Learning how to ask for help is important. Learning how to Google for it is vital.
  37. 37. In the end, you are only as good as your data set.
  38. 38. Q:What makes a good data set? A: Knowledge of its components; and accessibility of metadata.
  39. 39. Metadata: data about data
  40. 40. What are the components of the objects you work with? • Book: words, pages, author(s), editor(s), publisher(s), reader(s), physical edition(s), digital editions, reader responses • Performance: sound/video file, performer, venue, date/time, program
  41. 41. This: Book: words, pages, author(s), editor(s), publisher(s), reader(s), physical edition(s), digital editions, reader responses gets broken down even further.
  42. 42. <text xmlns="" xml:id="d1"> <body xml:id="d2"> <div1 type="book" xml:id="d3"> <head>Songs of Innocence</head> <pb n="4"/> <div2 type="poem" xml:id="d4"> <head>Introduction</head> <lg type="stanza"> <l>Piping down the valleys wild, </l> <l>Piping songs of pleasant glee, </l> <l>On a cloud I saw a child, </l> <l>And he laughing said to me: </l> </lg> TEI Encoding of William Blake’s Songs of Innocence (from TEI By Example:
  43. 43. Depending on the decisions you make regarding your data, people will be able to do different things with it.
  44. 44. Your decisions may impact the compatibility of your data with other tools/platforms.
  45. 45. This is why we emphasize that DH is a highly social and collaborative field.
  46. 46. DHValues (in review)
  47. 47. What do you need, as possible practitioners of digital humanities scholarship?
  48. 48. Take part in the #DMDH September Showcase! (Show the UW community what you’re learning) Thanks to our sponsors! UW Textual Studies Program