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CityRank.ch: Visualizing Global Cities

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Seth Flaxman presents on CityRank (www.cityrank.ch) at DD4D (www.dd4d.net) in Paris in June 2009

Abstract:

"In the context of data on cities, we present an example of how to make statistics relevant and meaningful to non-expert users. While the cities of the world are emerging as key players in global processes, from climate change to migration, the body of data on the cities of the world is neither extensive nor well-organized. Towards the end of organizing, understanding, and presenting this data, we have created an online framework called CityRank. To make this data relevant to users, CityRank allows users to upload new data sets and create and share personalized rankings of cities based on the data included in CityRank’s data repository."

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CityRank.ch: Visualizing Global Cities

  1. 1. Visualizing Global Citiesa dynamic tool for exploring indices of cities<br />Seth Flaxman<br />École Polytechnique Fédérale de Lausanne<br />Joint workwith Jeffrey Huang, Xavier Comtesse, & John Stephenson<br />
  2. 2. ThinkStudio<br />
  3. 3. www.cityrank.ch<br />
  4. 4. 1. cities<br />2. city data<br />3. our tool<br />4. future research<br />
  5. 5. cities<br />
  6. 6. Source: NASA Visible Earth<br />
  7. 7. Source: NASA GSFC, MITI, ERSDAC, JAROS, and U.S./Japan ASTER Science Team<br />
  8. 8. city data<br />statistics, indicators, network<br />
  9. 9. Source: Nicolas Nova on Flickr<br />
  10. 10.
  11. 11. London<br />New York<br />Hong Kong<br />London<br />New York<br />Singapore<br />London<br />New York<br />Tokyo<br />Seoul<br />Hong Kong<br />Helsinki<br />Vienna<br />Zurich<br />Geneva<br />
  12. 12. Just Landed visualization of Twitter by Jer Thorp (blprnt.com)<br />
  13. 13. our tool<br />what, how, why<br />
  14. 14. www.cityrank.ch<br />
  15. 15. Credit: Hubsquircle by Clearly Ambiguous on Flickr<br />
  16. 16. Rank Aggregation<br />
  17. 17. The Problem<br />New York<br />Geneva<br />London<br />
  18. 18. The Problem<br />New York<br />Geneva<br />London<br />
  19. 19. The Algorithm<br />London<br />Geneva<br />Chicago<br />New York<br />25<br />31.3<br />18.8<br />54.2<br />112.5<br />50<br />
  20. 20. The Solution<br />Chicago<br />New York<br />London<br />Geneva<br />25<br />112.5<br />18.8<br />54.2<br />31.3<br />50<br />Based on the rank aggregation algorithm in “Learning to rank with combinatorial Hodge theory” by Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye, 2008.<br />
  21. 21.
  22. 22. future research<br />academics, policy makers, designers<br />
  23. 23. conclusions<br />
  24. 24. www.cityrank.ch<br />
  25. 25. How can any of this be rigorous with varying definitions of what constitutes a “city?” Further, what exactly makes a city “global?”<br />Doesn’t letting users generate their own rankings undermine the authority of indicators?<br />Does the current economic crisis diminish the importance of cities?<br />How might the general public find this information or creating their own rankings useful? <br />
  26. 26. references<br />State of the World&apos;s Cities 2008-2009: Harmonious Cities, United Nations Human Settlements Programme, October 2008, www.unhabitat.org<br />Globalization and World Cities Research Network, www.lboro.ac.uk/gawc<br />Learning to rank with combinatorial Hodge theory, www.arxiv.org<br />More online: www.cityrank.ch/learn<br />
  27. 27. Indicators with Scores<br />London<br />Geneva<br />Chicago<br />New York<br />Average Comparisons<br />
  28. 28. The Result<br />Aggregated Ranking<br />Chicago<br />New York<br />London<br />Geneva<br />

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