The development of Big Data technologies has had a great impact on society and research. The ubiquity and huge quantities of human generated data, together with the enhancement of computational capabilities, hold great promises for the advancement of knowledge in numerous fields from medicine, to behavioral science, to economy. At the same time, however, Big Data is also raising numerous ethical concerns due to the unpredictability of the harm that it poses for research subjects. For this reason, policymakers and scholars, especially in the context of academic research, alike are struggling towards the appropriate ethical management and regulation of research that uses Big Data methods.
The goal of this dissertation is therefore to contribute to the development of appropriate ethics frameworks for Big Data research that will assist investigators in navigating the multifaceted ethical issues of Big Data, design ethically sound research projects and avoid regulatory drawbacks. In order to meet this objective, a mixed methods approach was followed. First, two systematic reviews on the ethical issues of Big Data were performed using the PRISMA method. Second, the opinions and attitudes of academic scholars were investigated through a qualitative interview study with Swiss and American university-based scholars working on behavioral Big Data studies.