Measuring Informational Distance Between Cities

May 22, 2008  |  Mapping

Bestiario, the group behind 6pli, recently put up their piece that maps informational distance between cities. At the base is a freely rotating globe. Arcs, whose strength and height represent strength of relationship, connect cities. The metric to determine strength of relationship takes several contexts into account - Google searches for individual cities, cities together, and geographical proximity. Bestiario implemented the piece in actionscript and used their own 3d framework (in Spanish).

[Thanks, Santiago]

11 Comments

  • what the fck … that is really beautifull!!! good job! can someone translate it to spanish ;-)

  • what the fck … that is really beautifull!!! good job! can someone translate it to spanish ;-)

  • I’m sorry but this is one of the worst cases of visualisation I’ve seen recently. There is no way to actually see which two cities are connected and to visually compare two different pairs of cities. The only thing I can tell is that London & New York seem to have a pretty strong connection, which is expected anyway!

    What would have been rather straightforward to show on a flat world map gets destroyed because of a flashy 3d viz. I wish they put the raw data somewhere so people could experiment with different alternatives.

  • I’m sorry but this is one of the worst cases of visualisation I’ve seen recently. There is no way to actually see which two cities are connected and to visually compare two different pairs of cities. The only thing I can tell is that London & New York seem to have a pretty strong connection, which is expected anyway!

    What would have been rather straightforward to show on a flat world map gets destroyed because of a flashy 3d viz. I wish they put the raw data somewhere so people could experiment with different alternatives.

  • Alexander: I agree with you. Information Distances is only an experiment. And is not really about visualization, but about different ways to look for, create or transform data, and how to interpret it.

    It is also what I call a “exquisite fetus”, that is an incomplete work where people can see different potentialities and opportunities.

  • Alexander: I agree with you. Information Distances is only an experiment. And is not really about visualization, but about different ways to look for, create or transform data, and how to interpret it.

    It is also what I call a “exquisite fetus”, that is an incomplete work where people can see different potentialities and opportunities.

  • Alexander: I agree with you. Information Distances is only an experiment. And is not really about visualization, but about different ways to look for, create or transform data, and how to interpret it.

    It is also what I call a “exquisite fetus”, that is an incomplete work where people can see different potentialities and opportunities.

  • Hi Santiago,

    I do agree that it’s a great idea to look into how cities may be related. I also really appreciate that you publish your algorithm. Is there any chance that you can also publish the results of the calculation for the pairs of cities that you currently have, so that people can experiment with other kinds of visualisation?

    Cheers,
    Alex

  • Hi Santiago,

    I do agree that it’s a great idea to look into how cities may be related. I also really appreciate that you publish your algorithm. Is there any chance that you can also publish the results of the calculation for the pairs of cities that you currently have, so that people can experiment with other kinds of visualisation?

    Cheers,
    Alex

  • Alex,

    I first thought that explain the algorithm was much more than putting the data (in some way the first contains the second). But is true that code this is not so simple (there are some math issues, and some technical issues.. for example I had to use a php on server to access google info because of permissions).

    So, now it is possible to download the table of pairs of cities, with geographical coordinates, google distances, informational distances and weight of relations (see below the explanation).

    One of the purposes of publish experiments and drafts is to generate this kind of dialogue and reflexion.

    Thanks,

    Santiago

  • Hi Santiago,

    many thanks for making the data available. As soon as I find some time I will experiment with some different visualisations, and if anything interesting comes out of it I’m going to blog about it & let you know (and of course I will always acknowledge your contribution of the data)

    Regards,
    Alex

Copyright © 2007-2014 FlowingData. All rights reserved. Hosted by Linode.