by OKFN, Michael Bauer, Lucy Chambers, Laura Newman, Friedrich Lindenberg, School of Data and Lisa Evans
In this session we will start expeditions into different datasets. The data we'll explore and cartograph will range from financial to environmental and geographical data - and possibly beyond! Participants will join an expedition and discover and map the landscape that they find. Throughout, there will be an emphasis on developing and improving data wrangling skills and techniques.
After a short round of introductions of different expedition areas, we will form expedition teams, set out to explore the data at hand, create an expedition journal and map out the landscape we find. The expeditions will be supported by Open Knowledge Foundation sherpas, spirit guides and compass readers, who will pull explorers out of the ditch whenever stuck.
Currently we are preparing to set out to three distinct expeditions:
What is a ‘Data Expedition’?
Data expeditions are a experimental concept we at the School of Data have decided to try. They are hands on workshops with guidance and direction – however the participants (adventurers) are not lectured, they learn data-wrangling skills by being confronted with real life data, problems and questions. Our sherpas will guide their pack to useful data sources, tools and resources to help climb the data mountian, but exact routes taken and questions answered will be determined by the participants. In a Data Expedition, the amount you learn depends only on your ambition, we’re aiming to teach you how to learn, not to spoonfeed you answers. Be aware that if you keep wandering off into the woods there might be dragons (just to bring you back on the road).
Who can participate?
We’re looking for Adventurers and Explorers with skillsets ranging from storytelling via heavy code-forging to graphic design. All skill levels are needed and the more diverse the party the better chance to survive and complete the expeditions. Teaming up with people having different skillsets and levels will be beneficial for participants.
Will anyone die in the process?
Hopefully not. Data is generally safer than real blizzards, but can be equally overwhelming.
Take-aways:
Who should come?