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

Visualising in Time & SpaceSeeing the Worldin Dynamic Dimensions

Shawn DayDigital Humanities ObservatoryDAH Spring Institute 2013 - UCC - 8 February 2013

Page 2: Visualising Space and Time

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

Page 3: Visualising Space and Time

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

Page 4: Visualising Space and Time
Page 5: Visualising Space and Time

Discovery

Browsing Objects Using Time and Location

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The Classic Time, Space and Environmental Visualisation

http://www.datavis.ca/gallery/re-minard.php

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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/

Page 8: Visualising Space and Time

• 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?

Page 9: Visualising Space and Time

• 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

Data Analysis Principles

Fern Halper - Seven Guiding Principles

Page 10: Visualising Space and Time

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

Page 11: Visualising Space and Time

Processing

• Balance Sources and Formatting

• Filtering

• Normalising

• De-Duplication

• Unit Conversion

• Time Zones

• Formats

• Testing and Removing or Resolving Anomalies

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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

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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

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But with simplication we see than time is not linear in this case ...

http://mysticalpha.deviantart.com/art/Back-to-the-Future-Timeline-162530828

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And it really is matter of what we are representing

http://flickographics.com/the-delorean-travels/

Page 17: Visualising Space and Time

Geospatial VisualisationA Simple Example

• A quick example - bit of how, more about the why

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You have this ...

Aggregate Demographic and Economic Data from US 2011 Census by Census District

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...and this...

US 2011 Census District Boundary files in KML

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Combining Statistical Datawith Geospatial Datato Visualise for Patterns

+ + =

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And When You Need to Bring Time into the Equation

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One to Watch

The Shape of What’s Coming ...

https://republicofletters.stanford.edu/tools/