The defining characteristic of the 21st century might very well be the omnipresence of digital data. The continuous, voluminous and heterogeneous stream of data generated by sensors and people is rapidly transforming how we experience, how we analyse and how we interact with the people and things around us. Citizens, enterprises, governments and scientists are confronted with the potential blessings, as well as challenges, that “Big Data” provides for understanding the world around us.
“Big Data” is a term that is difficult to define, hence the Big Question structure of the course provides a suitable way of approaching this topic that crosses disciplines. This course aims to let students discover for themselves what “Big Data” entails and encourages them to reflect on that experience.
Central to the course are therefore a series of real-life case studies related to key cultural, social and environmental issues in contemporary society. The case studies will lead the students to experience, first-hand, different techniques for data collection and storage, data visualisation and analytics, and hypothesis definition and communication. These steps are grounded in “data-driven knowledge discovery,” also referred to as “abductive reasoning,” which starts with data describing a phenomenon and continues with defining a hypothesis that explains the data. Is “Big Data” an exciting new way to discover new things about ourselves and the world around us, or does it hamper our privacy and lead us to follow invisible patterns that in the end prove to be terribly wrong?
The course is framed as applied data science, with a focus on tackling societal and scientific problems, from a geographic perspective. Students gain a theoretical and practical understanding of the impact of data in society. They take part in practical use cases and present their group work online.