New course on Big Data

In the academic year 2017-18, I’ll be giving a course to Masters students in Computer Science at the Faculty of Science and Engineering of the University of Groningen. It will replace another elective course that focused on ethics, and I’m hoping that it will provide students with the opportunity to explore epistemological issues around Big Data using STS concepts and approaches. Developing the course is a lot of fun and a great opportunity to consolidate many of the insights we are developing in Energysense. Plus, one of the assignments will be doing an interview, so we’ll touch on some ethnographic skills as well.

Course description

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Data seems to be everywhere in contemporary society.  Precisely because of this ubiquity, it is important to consider how data is created and used, and how it circulates, so that we can understand the implications for business, for private and public life, and for what we know about ourselves and the world.

A new course at the Faculty of Science and Engineering, University of Groningen, will equip students to reflect and act on issues around big data. Big data is a phenomenon that affects all kinds of sectors, from energy to banking to sports to neuroscience. It has a history going back several decades and has been shaped by tools and institutions, with the result that ‘big data’ has its own biases and tendencies. It is therefore crucial to  analyse how big data approaches are a specific way of creating knowledge and how this knowledge is used. In particular, we will trace how new forms of measurement yield data, that are then combined with particular kinds of statistics and database logics.

We will also cover the reasons underlying the hypes and hope around data, the new forms of ‘value’ attached to data, and the emergence of particular movements (‘open data’; neveragain.tech, responsible data science).

A number of skills will be integrated into the course, providing a basis for dealing with data issues as a researcher or professional working intensively with data. This course will enable students to reflect and act, when it comes to issues such as visualisations, design of privacy-enhancing technologies, or the value of correlation.

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