The TWIST Hackdays are coming
August 25 & 26 up to 100 open-minded data-aficionados, designers, developers, topic specialists, and above all citizens are meeting at the University of Zurich. What for? To make open [statistical] data used and useful.
Why you should not miss this opportunity
If you haven’t participated at a hackday yet, I’d like to share with you my personal experience of about 15 hackdays, which I’ve attended over the last 8 years: There’s hardly any other kind of event at which you will learn so much together with a diverse crowd of people. All bringing their whole self with them— not only, but also because they’re devoting their free time for it.
At a hackday more interest, passion and skills are always in need. Let others know that you’re participating, and send them our registration link.
What open data will we work with
Rule 1 of hackdays, which I’ve been enjoying, has always been, that you are not obliged to work with and on anything that you‘re not freely choosing to. We, as the organizers of the TWIST hackdays are only pointing you to data which is available, and to ideas respectively challenges we’ve been hearing about. During the last weeks we’ve been communicating about the following:
- Bring insight into public finances
- Dive into the linked open data future
- Get your hands on crowdsourced open data from «Züri wie neu»
- Give your address a position. Give your position an address
- Work with the spatially most granular statistical (open) data on the Canton of Zurich
- Contribute to a better understanding of traffic in major Swiss cities
What data are we preparing at the moment
Furthermore my colleagues at the Statistical Office of the Canton of Zurich are preparing:
- a kaggle-like machine-learning challenge with flight-data provided by the airport of Zurich. Can we successfully predict, if a flight will arrive/depart on time? If you’re experienced in modeling and machine-learning, please take a look at the data and tell us which further predictors should be added and what needs to be done to provide a “ready-to-go” ML-dataset at the hackday.
- a spatial dataset of real estate trades in the Canton of Zurich, based on the datasets of prices of single-family houses and prices of condominiums.
Now, it’s your turn
On the hackdays’ website we are curating an “Ideas & Ressources” section. News you’re always getting first via twitter: @TWIST2018.
We are looking forward to hacking together with you soon!
