Online Expedition

TLDR: An online Expedition to prepare data for the 2018 Open Food Data Hackdays starts on January 9. Find out how to join in and contribute!

What:Making fresh data for the Open Food Data Hackdays.
How:Join the virtual workshop preparing Data Packages.
Requirements:A computer and Internet connection.
  I have a question Get started !

Start the new year with a virtual Data Expedition, building up on our workshops last year. Learn to work with open data and help to prepare resources for the upcoming Open Food Hackdays. We wish to involve people with all kinds of skills at this event, whether you are a data connaisseur or just a beginner. Registration is not required if you just want to help with this Expedition, but please register at food.opendata.ch if you wish to also participate in the Hackdays.

Let’s get started!

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. Visit 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 in this form 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. You can also share your tips by chat or e-mail.

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.

You may 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?