Bowdoin: Data Driven Socities 2014 - Representation 02/03/14

433 views

Published on

Data Driven Societies
Digital & Computational Studies
Bowdoin College
February 3, 2014
Professors Gieseking & Gaze

Lecture Slides "Keeping it Real and Honest: Representing Data"

Published in: Education, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
433
On SlideShare
0
From Embeds
0
Number of Embeds
130
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Bowdoin: Data Driven Socities 2014 - Representation 02/03/14

  1. 1. Data Driven Societies: Representation Professors Gaze & Gieseking
  2. 2. What is representation? ✦ Using signs, terms, characters, images, etc., that stand in for or take the place of something else
  3. 3. Kurgan: The Necessity of Interpretation ✦ Remote sensing acquisition of information about an object or phenomenon without making actual physical contact with the object or experience ✦ Global positioning systems (GPS) - space-based satellite navigation
  4. 4. Politics of Representation ✦ Transparency, freedom of inquiry, and openness sit alongside militarization, security, and official qualities of aerial photography ✦ “There is no absolute scale, just as there is no natural or logical starting or stopping point for the zoom.” (Kurgan 20) ✦ “The View from Nowhere” - Svetlana Alpers ✦ “God’s eye view” - Donna Haraway
  5. 5. Kurgan: Million Dollar Blocks http://www.propertyshark.com/
  6. 6. Kurgan: Million Dollar Blocks GoogleMaps
  7. 7. Kurgan: Million Dollar Blocks npr.org
  8. 8. Kurgan: Million Dollar Blocks nytimes.com
  9. 9. Fighting Crime with Social Networks Radil, Steven M., Colin Flint, and George E. Tita. 2010. “Spatializing Social Networks: Using Social Network Analysis to Investigate Geographies of Gang Rivalry, Territoriality, and Violence in Los Angeles.” Annals of the Association of American Geographers 100 (2): 307–26.
  10. 10. Visualize This Visualization is what happens when you make the jump from raw data to bar graphs, line charts, and dot plots. —Nathan Yau, Data Points (2013, 92)
  11. 11. Visualize This To put it another way, there is no such thing as raw data. Data are always translated such that they might be presented. The images, lists, graphs, and maps that represent those data are all interpretations. … The phrase ‘data visualization,’ in that sense, is a bit redundant: data are already a visualization. —Laura Kurgan, Close Up at a Distance (2013, 35)
  12. 12. Next Class: Feb. 5 ✦ Readings: Cohen only, do not read the Illinsky ✦ Quiz: email you the list of terms this afternoon ✦ Blog: next post due now on 2-10, email you the detailed instructions this afternoon ✦ Course topic: on Wednesday, we shift from a focus on Data to Privacy

×