Next Expedition

What:Making fresh data for the Open Food Data Hackdays.
How:Join our workshop and help to collect and prepare open data.
When:Wednesday, August 15, 2018, 16:00 - 18:30
Where:Bern, Switzerland.
Requirements:A reasonably modern laptop, experience with spreadsheets. Data science skills would be a bonus.
  I have a question Get started !

Learn to work with open data and help to prepare resources for the upcoming Open Food Data x Smart Kitchen Hackdays in this Data Expedition facilitated by the Swiss School of Data chapter. The workshop will be followed by Open Data Beer from 18:30. Whether you are a data connaisseur or beginner, we wish to involve people with all kinds of skills at this event - this pre-event is the perfect chance to get ready for a hackathon!

Register now!  

TIP: please register separately at food.opendata.ch if you wish to also participate in the Hackdays on September 7-9.


Get started

In our Data Expedition, you can learn to work with open data and collect resources for the upcoming Open Food Hackdays. The first step is to register for the workshop at Eventbrite. Meanwhile, in the #Expedition channel of our virtual community (sign up here to our Mattermost open chat server), as well as through the discussion forum, we will be sharing updates on our progress. With these three steps, you too can take part:

1. Check Datacentral

At openfood.schoolofdata.ch (“Datacentral”) and github/foodopendata you can see the list of datasets already prepared in the form of Data Packages, each in a GitHub repository. Look around to understand what is meant by Open Food Data. Think about some questions you would like to ask, issues you care about. Run some additional searches on data portals or search engines. If you have an idea, or find something interesting, hold onto it for the next step.

2. Make a suggestion

Ideas you share by contacting us or raising an issue on GitHub will go into a master list. This is a public process and requires some moderation. In particular, we are looking for sources of data which are relatively up to date, with potential for new applications, and which are as free as possible of restrictions and accessibility issues - in the ideal case, open according to the Open Definition. From the best data we discover together, we aim to create as many Data Packages as possible.

3. Package the data

From the master list we will download and test datasets, do some minor clean-up if necessary, check the licenses, create and validate a Data Package, and document any issues in a README. Data Packages currently being created or updated that we are looking for help with are listed in GitHub:

If there is a dataset you wish to see supported at github/foodopendata, you can also fork our boilerplate and start a Data Package yourself. If you publish it online, send us the URL for feedback and inclusion in the master list and Datacentral.

Tips and tools

There are lots of resources in our Forum, and you may also find our data wrangling Toolbox and information on Data Packages useful. By this time you may have other things to share or ask, so let’s chat. Then come to the Hackdays and make something amazing!


Any questions?