I have asked Darius Damalakas (the Lithuanian clone of Write To Them parasykjiems.lt) to explain the international approach to the development of WTT clone websites in Central and Eastern Europe. This quote is a bit long, so I do apologise, but he did it in such a great way that I could not summarize it any better. So over to Darius:

“WTT projects can be roughly grouped into 3 big parts:
a) The government representative database
b) The mechanisms of finding a relevant representative for the end-user
c) The infrastructure of sending emails and receiving replies from gov
representatives.

First, we must understand how the countries are different in the government hierarchy. On the biggest scale we can see that every country has members of parliament (MP). However, there are countries where MPs are elected based on constituencies. Constituencies are based on territories, that is, MPS have a territory associated to them. On the other hand, there are countries where MPs are elected without any territorial association. Lastly, there are countries which have both types of MPs.

It is this primary factor (the territorial association), which is different country to country. Other levels of government representatives usually fall again in the same two categories.

If we look at Lithuanian WTT project as an example, we can observe two things:
a) Lithuania has both types of MPs )based on constituencies, and not
on territories)
b) All other representatives are strictly based on territorial regions.

It will be one of the goals to clearly analyse these differences in a meeting in Belgrade 15th of January. Every country will have to collect their own database of government representatives. The only sharing that is possible here is the information format part, that is, how and what information will be stored in the database. Also, keeping information up to date is very important, and mechanisms which facilitate process of keeping information up to date will probably save some amount of time to every country .

Next thing to discuss are the mechanisms of finding a relevant representative for the end-user. These can be grouped again into at least 2 groups, and some sub-groups:
1) Finding representative based on territory:
a) the search can be based addresses (municipality, city, street, house number) and mapping these to gov representatives;
b) the search can be based on geographical data. that is, an exact coordinates on the earth globe can be mapped to government representatives.
2) Finding representatives without any associated territory:
a) search based on topics that are interested for the user. This would be more or less like Google approach – end user types some topic, and the site scans billions of information to find a list of relevant MPs and/or other representatives;
b ) search based on some strict pre-defined list of criteria. For example, grouping MPs by the committees they are attending, by their interests, votes or anything else;
c) any other solution.

Lithuania’s approach is currently “a.1” , that is, search based on addresses. Other countries might choose different search mechanisms, but the goal is actually use several mechanisms at once. For example, Lithuania WTT will definitely use some search mechanism to find MPs not associated to any territory.

Lastly, there is the infrastructure of sending emails and receiving replies from gov representatives. This also involves publishing
replies on the site, as well as collecting various statistics for the site. This part can be shared by all projects at once, since sending
and receiving email is not different from country to country, so this part can be re-used 100%, compared to search mechanisms, which would be shared by a much smaller percentage.

To summarise, there are quite a flew places where projects can benefit if they share the same code base. Government representative databases will require a lot of effort from every country, but information update process can be facilitated by having a common process for every country. Email infrastructure as well as publishing replies and collecting statistics and search mechanisms are the key targets for sharing.”