Tools, Techniques, Methods for Digital Humanities Scholars

1. Visualising in Time & Space
Seeing the World
in Dynamic Dimensions
Shawn Day
Digital Humanities Observatory
DAH Spring Institute 2013 - UCC - 8 February 2013

2. Here’s What We Hope
to do in 1 Hour
• Explore Spatial and Temporal Dimensions in
Humanities Scholarship
• What Can Be Done?
• What Principles To Be Aware of?
• Some Useful Tools

3. Grounding Ourselves
• How do we get from:
• there to here
• then to now
• what can we learn from the path we take?
• What data do you have?
• What questions do you want to ask?
• Pure Speculation

5. Discovery
Browsing Objects Using
Time and Location

6. The Classic Time, Space and
Environmental Visualisation
http://www.datavis.ca/gallery/re-minard.php

7. What About the Path
and Sequence?
• Because we are representing real world
phenomenon we have have to ask what we are
seeing when we identify patterns.
• Trends
• Shifting
• Stabilising
• Cyclic vs anomalies
• Burst
https://republicofletters.stanford.edu/tools/

8. • So what we see are that there are some great visualisations out there
• and that the power exists to create them
• ...but where do they come from?
• The place we have been talking about all day
• ...good data...
• so how do we find and manipulate data related to space and time to make it
usable in such ways?

9. Data Analysis Principles
• Process is a Way of Thinking, not a Substitute for Thinking
• Data needs to be considered and reported in Context
• Look Before you Leap - Get to Know Your Data
• Question Everything - Collection, Process, Bias, etc.
• Coincidence is Not the Same as Causality
• Just Because Data Exists Doesn’t Mean its Relevant
Fern Halper - Seven Guiding Principles

10. Time
• Time series data can be continuous or discrete
• It’s usually discrete - i.e. observations exist for regularly or irregularly spaced
intervals
• Although occasionally continuous - i.e. an observation at every instant of time

11. Processing
• Balance Sources and Formatting
• Filtering
• Normalising
• De-Duplication
• Unit Conversion
• Time Zones
• Formats
• Testing and Removing or Resolving Anomalies

12. Analysis versus
Presentation
• Who is this for?
• Is it to convey a message or finding?
• Is it purely for discovery and analysis?
• Maps can be funny to manipulate
GDP Growth 2004 http://demo.intelytics.fr/bdf/#none/2000

13. But Time is ‘Funny’ and let’s
consider Back to the Future
• There can be simple sequential linear tine ... it’s the one we are most used to

14. All 3 Movies in a Fancy Timeline
http://a.yfrog.com/img806/8237/s3c.jpg

15. But with simplication we see
than time is not linear in this
case ...
http://mysticalpha.deviantart.com/art/Back-to-the-Future-Timeline-162530828

16. And it really is matter of what we
are representing
http://flickographics.com/the-delorean-travels/

17. Geospatial Visualisation
A Simple Example
• A quick example - bit of how, more about the why

18. You have this ...
Aggregate Demographic and Economic Data from US 2011 Census by Census District

19. ...and this...
US 2011 Census District Boundary files in KML

20. ... which Reveals
http://www.richblockspoorblocks.com

21. Combining Statistical Data
with Geospatial Data
to Visualise for Patterns
+ + =

22. And When You Need to Bring
Time into the Equation

23. Herodotus TimeMap

24. Temporal Tools
SIMILE Timeline TimeFlow DIpity
TimelineJS TimeMap TimeGlider

25. Spatial Tools
Google Fusion Tables Many Eyes Google Earth
Junar OpenGRASS ArcGIS Explorer

26. Data Refining and Manipulation
OpenRefine Mr Data Converter Data Wrangler
Junar R Text

27. Pulling It Together - Exhibit

28. Pulling It
Together -
NeatLine
Omeka Plugin

29. One to Watch
The Shape of What’s Coming ...
https://republicofletters.stanford.edu/tools/

30. Thank You
Shawn Day
@iridium
s.day@dho.ie