Social scientists are beginning to openly share anonymous (or shared-with-permission) data on how people learn, form categories, navigate the social world, and more. But uploading a dataset is just the beginning - how do we (as learners, scientists, and makers) actually discover and use these datasets? A key step is to build consensus (and technical specifications) for how we structure/document our data so we can find what we're interested in and extend each others' work in unexpected directions.
This session consist of a roundtable on the principles of FAIR (Findable, Accessible, Interoperable, Reusable) sharing, and then an open-tinkering time where participants 'test-drive' these principles by identifying datasets to play with, what we need to make them usable, and what we can imaging building.
This is a Learning Forum session.