This is first public release of such data in Slovenia and is result of 6 months of intensive work in data reconciliation, methodology and finally – visualisation.
I helped mostly in regards with data reconciliation and can speak about the tools we used. Basic tool was Google Spreadsheet and was used as a database that everyone could contribute to and it helped us sync the data together. It also allowed for basic pivot table based visualisations. It worked mostly ok and ability to write scripts for it also helped a lot. Finally the data was moved into Semantic media wiki and visualised using d3.js.
Google Spreadsheets don’t scale. After you reach about 1000 rows with 30 columns, it becomes almost unusable slow.
This dataset is complex enough that it would benefit from automatic checks – automated reimporting into real database and basic reports – unique institution, basic pivot tables. This would help with encoding, whitespace issues that Spreadsheet doesn’t handle.
Google Spreadsheet got really good tools for pivot tables, but they’re a pain to manage if data ranges change. It can probably be further automated but I haven’t yet figured out how.
Where in Ljubljana it’s most likely that your car will be towed away? In short: city centre, beginning of Vi? and around Metelkova.
Click for interactive version
or alternative visualization
Click for interactive version
Source of this data is page from Javni Holding Ljubljana that publishes your car info and the street it was towed away from. Gašper created Scraper wiki for it and is collecting data for last 3 months (aggregated source, if you want to reuse it).
Heatmap as a visualization technique was chosen because the data itself is very fuzzy (only street names are given, without the street number). It also tells you which neighborhoods to avoid.
If you want to help us bring more of such mashups into the world, please consider adding other sources of data into si.ckan.net. These pictures are end results of one such example where data was not hidden behind a telephone or a piece of paper (in a locked filing cabinet in a disused lavatory behind a door that says “Beware of the tiger”).
Slovenian budget is a 12 billion euro monster that most citizens don’t understand or even have remote idea how it’s structured and where does their money go. As it turns out, people are just not good at taking abstract numbers to go into billions and understanding proportions and what it means to spend 50 million on one thing and 1 billion on something else.
That is what I’m trying to solve with this Visualization of budget of Slovenia for 2010. Show where the money is going as well as tell a story of a country that’s so much in debt that it would be a reason for panic if it happened to a person or a company. Yet we don’t seem to talk or address the issue that we’re 3.6 billion EUR short of making budget and that we have to borrow more money to pay our old debts.
(click on image for interactive version)
(red is debt)
Having access to experts or your own understanding of the data you’re trying to visualize is essential. In this case we had to reassemble budget since they form listing in a way that presents debt separately from the rest of the budget.
Kiberpipa is a large organization with lots of volunteers. This means that whatever you do, you’ll have organizational problems and you’ll see technology as a way to solve them. To a certain degree of course. A few years ago Boštjan and I saw this as an opportunity to reinvent the wheel and write our own groupware software. This is is how intranet project (yes, a terrible name from branding perspective) was born almost 5 years ago.
Since then a number of people have picked up the project and used it to improve their Django skills as well as help Kiberpipa get a bit more organized by a way of technology. While learning my way around some video editing software I’ve thrown together a video of commits of pieces of code into intranet’s code repository. Project used to generate frames is an open source Java based code_swarm. I’d like to encourage it to try it out and run it on your own source repositories.
This is the story of the following video. Please watch it in ‘full screen’ for the best experience: