Hi all, I am entering to an unfamiliar territory and trying to compose a web page analysis list for elections related websites. So far I have read Pippa Norris books, and some stuff found in google searches. What is bothering me is that e-democracy seems to be dealing with participational issues in the web environment rather than how web supports traditional elections. But maybe I am unable to come up with right search terms or have understood notions of e-democracy wrong? can someone point me to a book/article or even keywords what to look for? I am open to all kind of suggestions. Gratefully, Pille Vengerfeldt PhD student from Estonia

I'm not sure what you tying to capture here. When you say you have data that shows gross traffic - but I wonder what that traffic is. A few thoughts on this (dredging my old ISP days): Data on the internet flows either within networks (Autonomous Systems - generally switched flow) or between networks (where routing comes into play at peering points (either public or private) / NAPs (Network Access Point) see BGP generally). But if we look at flow between say London and Paris one could try to estimate data going into LINX (the main London NAP) and out of SFINX (the Paris one). But in Europe there are lots of international / pan European single AS networks, so this traffic will not show up on in some analysis unless it has to ingress or exit from / to a peer. Then there is the fact that traffic that does exit at say LINX may in fact just be hoping transatlantic. And lastly there are many more peering points just in the two cities I have mentioned. Unless things have moved on since I looked at this stuff, you can't geographically source IP packets across networks (if you have your own network sure you can do that). I'm sure you can get data that basically shows very gross traffic in and out of the major 'nodes' around the world so you could work out relative traffic levels, but an actual city to city matrix flow - I'd love to see that, in fact I'd possibly pay good money to see that. Sorry if this misses the point and /or I'm a few years behind in the tech. Ren www.renreynolds.com -----Original Message----- From: air-l-admin@aoir.org [mailto:air-l-admin@aoir.org] On Behalf Of Justin Rosenthal Sent: 19 May 2004 21:28 To: air-l@aoir.org Subject: [Air-l] Data Hello all, I am interested in hearing any thoughts you have on a data problem that I have, that I am sure many of you have approached, and which is, of course, a result of the structure of the Internet itself. In my ideal world, I would be able to build a relational database of data traffic between the largest cities worldwide. The data I have found shows gross data traffic between nodes, which includes traffic originated in third-party cities and destined for fourth-party cities, for example, and which does not provide an estimate of the traffic originated in 3 and destined for 4. This means that the data doesn't relate every node in the city system to every other in terms of network traffic inbound and outbound. Have you approached this problem? Do you have any thoughts on how currently available data can be patched for network analysis, or how such a relational database could be built in the future? Many thanks, Justin _____________________________________ Justin Rosenthal MA Candidate - Social Science University of Chicago jrr@uchicago.edu _______________________________________________ Air-l mailing list Air-l@aoir.org http://www.aoir.org/mailman/listinfo/air-l

I am interested in hearing any thoughts you have on a data problem that I have, that I am sure many of you have approached, and which is, of course, a result of the structure of the Internet itself. In my ideal world, I would be able to build a relational database of data traffic between the largest cities worldwide.

Social problem the first - the information you'd most like to have is closely guarded by the involved companies. They keep it secret so that other companies can't deduce all of their peering agreements and thereby figure out how best to 'take advantage' of network position for profit. This is a pretty common problem for a decentralized network, in my experience.

The data I have found shows gross data traffic between nodes, which includes traffic originated in third-party cities and destined for fourth-party cities, for example, and which does not provide an estimate of the traffic originated in 3 and destined for 4. This means that the data doesn't relate every node in the city system to every other in terms of network traffic inbound and outbound.

right - the nodes which are most easily measured/evaluated (the network hubs) don't actually act as termination points for a whole lot of traffic. they're just points in the system as a whole, with peers that serve endpoints but are not backbone nodes themselves.

Have you approached this problem? Do you have any thoughts on how currently available data can be patched for network analysis, or how such a relational database could be built in the future?

a graph-like structure is good for this, IMHO. something like this: sourcenode destnode measurement eval.date sourcenode destnode measurement eval.date sourcenode destnode measurement eval.date ad nauseum. you may need some more values, depending on what it is that you're wanting to do. but that general form (spreadsheet-like) is one of the simpler structures to store in a database, and reformatting those tables into something that tools like UCINet or Pajek can display is not such a terrible task. elijah