Big Data: Technology, Law, and Ethics (FS17)

Data processing technology has gone through massive changes in the past years. Daily, billions of search queries are handled, millions of messages are posted on social networks, a myriad of shopping baskets are collected at online retailers, our smartphones continously collect movement data, and some of us subscribe to the quantified self via fitness trackers or smartwatches - Big Data is collected everywhere and at all times. The collection of these data offers enormous opportunities but also entails both ethical and legal challenges.

This course provides participants with an interdisciplinary view on Big Data and its capabilities. The course consists of two parts.

It will first introduce the technological (i.e., data processing, data storage, and data mining), legal (i.e., data protection and data ownership), and ethical (i.e, challenges to ethical values such as transparency, accountability, autonomy and solidarity that emerge from data collection and use) theoretical foundations needed to understand the Big Data phenomenon and reason about its potential and the challenges it generates.

In the second part, students will work on a cross-disciplinary Big Data project within interdisciplinary teams of students from across the University, write-up a paper or provide other scientific output on a technical, legal or ethical Big Data challenge (e.g. develop a website, wiki, app, interactive analysis, or the like) and present their findings at a one-day workshop.

Organizational matters


The workshop will take place on 15 May 2017, from 9:00am until approximately 5:15pm, in room RAA-E-29.

Each group will present the findings of their project (groups of two: 10 minute presentation; groups of three or four: 15 minute presentation), followed by a 20 minute discussion in the class.

Tentative Schedule Workshop 15 May (PDF, 16 KB)

Group and topic

Every group has to submit a one page description of the topic they want to work on.

Deadline: 3 April 2017, 23:59 CEST

Please send an e-mail to with the following information:

  • Names, matriculation numbers, fields of study of all team members
  • Topic description

The description of the topic shall address the following issues:

  • What are we doing (paper, app, topic of the paper and issues discussed)?
  • Why should we care about this problem?
  • What are we going to do and how?


Every group will be assigned one of the professors as a mentor. The mentor is available to discuss the questions the group may have at a meeting, by e-mail, or by phone.

Paper/other output

The teams will have to prepare a paper (15 pages; no more than 5,000 words, incl. footnotes) or may instead generate an alternative output (tbd with mentor).

Deadline: 10 May 2017, 23:59 CEST

In addition, all teams will have to present their findings during the workshop (15 May 2017).


Paper or other output: 70%

Presentation: 30%