NACIS 2016 Presentation
Joanna Merson, Arizona State University
Animation offers a captivating and informative avenue for representing dynamic data in cartography. Likewise, leading cartographic research aims to improve animation use through data and user evaluation to establish best-practice guidelines. But how many of these guidelines actually reach the research community? This question is investigated using a content analysis determine how cartographic animation is used in major geography journals in the past 5 years. I specifically examine what types of animation are used, the purpose behind their use, and the congruence between the animations and the data represented. This analysis is used to examine both how cartographic animation is used outside of the cartographic research community, and if in the era of digital maps, there is a need for better facilitating methods for including animations in academic publications.
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Determining current uses of cartographic animation in geography through a journal content analysis
1. Determining current uses of
cartographic animation
in academic geography
through a journal content analysis
@JoannaMerson
2. Academic publications
Non - academic
Publications
Work by cool people who
study how to or professionally make
cool maps and visualizations
Where do we find animated cartography?
3. Finding animation in
academic cartography…
SELECT * FROM journals
WHERE
CONTAINS (animated map or
dynamic map)
…I wish
9. Figure 5. Panels from example dynamic spatial history visualization
that is both an analytic tool and research outcome.
“
”
Simon Gregory L, 2014, “Vulnerability-in-Production : A Spatial History of Nature, Affluence, and Fire in Oakland, California.” Annals of the Association of
American Geographers 104 (February 2015): 37–41.
Keyword in context
10. Whitson Risa, 2010, “‘The Reality of Today Has Required Us to Change’: Negotiating Gender Through Informal Work in Contemporary Argentina.” Annals
of the Association of American Geographers 100 (1): 159–181.
Keyword in context
Men tend to enter the informal economy with the potential of earning
more than were they to work formally; they participate in dynamic,
growth-oriented jobs; and they maintain control over their own labor and
resources.
“
”
12. 2. Content Analysis
• Application domain
• Purpose
• Style
• Data structures
• Data/animation congruence
• Presentation type
• Other themes
13. Keyword in context
An animation by season of the violence (thirty-two map frames for eight years)
is available for download from our web site at
http://www.colorado.edu/ibs/waroutcomes/maps/allEventsAnimation.avi.
“
”O’Loughlin, John, and Frank D.W. Witmer. 2011. “The Localized Geographies of Violence in the North Caucasus of Russia, 1999–2007.” Annals of the
Association of American Geographers 101 (1): 178–201.
16. Arts Budgets Children Education
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FILM TAX WOMEN STUDENTS
SHOW PROGRAM PEOPLE SCHOOLS
MUSIC BUDGET CHILD EDUCATION
MOVIE BILLION YEARS TEACHERS
PLAY FEDERAL FAMILIES HIGH
MUSICAL YEAR WORK PUBLIC
BEST SPENDING PARENTS TEACHER
ACTOR NEW SAYS BENNETT
FIRST STATE FAMILY MANIGAT
17. Training data themes
GIScience Earth Systems Space/Time Models
Spatial Change Agents
Data Climate Model
Analysis Environmental Models
GIS Land Information
Information Global Movement
Research Systems Map
Time Model Time
Vulnerability Growth Spatial
Geographic Study Maps
Computational Area Agent
Science Economic Space
19. Committee:
Elizabeth Wentz Chair, ASU GeoPlan
Alan MacEachren Penn State
Ross Maciejewski ASU Computer science
Serge Rey ASU GeoPlan
Student collaborators:
Catherine Musili ASU GeoPlan
Morgan Klass ASU GeoPlan
Fred Morstatter ASU Computer Science
Acknowledgements
20. Questions?
10 min is short so I’m sure there
won’t be much time for questions.
Connect with me in person or online!
@JoannaMerson
jmerson@asu.edu
Notas del editor
I am Ph D student
Why?
Where do we see cartographic products?
Last year I was talking about methods for assessing animation.
At PCD we saw great animation from Ken and ? At ESRI
Committee said prove it
Where: Human, physical
IF from 1.6 (professional geographer) to 13.5 (nature geoscience)
What:
application domain (the sub field)
Purpose (explanatory/exploratory)
style of animation implementation. The possible categories are: time lapse, interaction facilitation, and animated symbology.
Data structure type of temporal data structure and spatial data structure expressed. (continuous/network etc)
level of congruence between the nature of the animation and the nature of the phenomena being symbolized.
how the animation was presented/referred to.
Image source: http://www.discoveryresearchgroup.com/content-analysis
Results is 3,000+ articles.
Keyword in context content analysis
Why this method?
Codebook= rule set that can be tested for inter-coder reliability
500 hits, to train on
Most hits was Dynamic. 500 to 25 papers
Content Analysis Method -> Keyword in context
Image source: http://www.discoveryresearchgroup.com/content-analysis
Application domain (the sub field)
Purpose (explanatory/exploratory)
style of animation implementation. The possible categories are: time lapse, interaction facilitation, and animated symbology.
Data structure type of temporal data structure and spatial data structure expressed. (continuous/network etc)
level of congruence between the nature of the animation and the nature of the phenomena being symbolized.
how the animation was presented/referred to.
In progress – see you at AAG.
Software is MaxQDA
Unit of analysis: each article
the reason that animation was used for the research presented
Demonstrate Concepts - Code:
Detailed Description: the author describes using the animation demonstrative purposes.
Inclusion Criteria: the author describes using animation to help convey a message.
Exclusion criteria:
Typical exemplar: “created an animation to demonstrate“
Animation used for an exploratory purpose
Tool: McCallum, Andrew Kachites. "MALLET: A Machine Learning for Language Toolkit." http://mallet.cs.umass.edu. 2002.
Image source: http://www.cs.princeton.edu/~blei/kdd-tutorial.pdf
Image: D.M. Blei (2012) http://www.cs.princeton.edu/~blei/kdd-tutorial.pdf
Blei David M, Andrew Y Ng and Michael I Jordan, 2003, “Latent Dirichlet Allocation.” Journal of Machine Learning Research 3: 993–1022.
