1. May 4th:
Available Tools:
Free, Cheap, and Premium
(and how to navigate choosing between them)

2. While there are many
different digital
platforms you can use,
in the end, all tools are
visualization tools.

3. When you choose a
tool, you’re choosing
how you want to see
your data.

4. Important Considerations

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. 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. 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. 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. Who is your audience?
• You
• Specialized scholarly audience
• Other digital/multimodal scholars
• Students
• The general public

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. 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. 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. 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. 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. The choices you make
in choosing tools are an
essential part of your
documentation.

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. Many Eyes
• Free text and numerical data visualization
engine, made by IBM
• http://www-
958.ibm.com/software/analytics/manyeyes/
• Usable on Mac/PC, but only in browsers
that run Java (i.e., not Google Chrome)

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. Mapping Tools!

20. Community Walk: Free
(Ad Revenue)

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. Google Maps: Free

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. Google Earth: Free
(Paid Upgrade: Premium)

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. ArcGIS (Super-Premium)

27. Pros
• It does EVERYTHING
• No ads
• Robust functionality
• Expensive!
• Not web-based
Cons

28. MIT Simile Widgets (Free)

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. Scalar (Free)

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. Pivotal Tracker (Free/Cheap)

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. Just a few of the many places
you can check for tools:
https://www.washington.edu/itconnect/wares/uwa
re/
http://dirt.projectbamboo.org/
http://digitalhumanities.org/answers/

35. Using (new) digital
tools means that you
will inevitably need help
at some point.

36. Learning how to ask for
help is important.
Learning how to Google
for it is vital.

37. In the end, you are only
as good as your data
set.

38. Q:What makes a good
data set?
A: Knowledge of its
components; and
accessibility of metadata.

39. Metadata: data about
data

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. 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. <text xmlns="http://www.tei-c.org/ns/1.0"
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: http://www.TEIbyexample.org)

43. Depending on the decisions
you make regarding your
data, people will be able to
do different things with it.

44. Your decisions may
impact the compatibility
of your data with other
tools/platforms.

45. This is why we
emphasize that DH is a
highly social and
collaborative field.

46. DHValues (in review)

47. What do you need, as
possible practitioners
of digital humanities
scholarship?

48. Take part in the #DMDH
September Showcase!
(Show the UW community what
you’re learning)
Thanks to our sponsors!
UW Textual
Studies
Program