We briefly review the emergence of internet research ethics (IRE) since 2000 across three stages, showing how the last, IRE 3.0, focuses on ethical challenges and issues evoked by Big Data. We explore specific examples of IRE 3.0 as occasioned by requirements for informed consent -- including Big Data analyses of a closed Facebook group -- as these show both continuity with earlier guidelines (IRE 1.0, 2.0) as well as the need for novel approaches. As a contribution to IRE 3.0, we propose a principle of data minimization in designing or setting the parameters of data collection software, as solely required by specific research questions, in order to avoid or minimize the ethical challenges that result from a default setting or temptation to collect as much data as possible. Throughout the chapter, we highlight important overlaps with the following chapter by Rensfeldt et al. We close by highlighting further prominent ethical issues in IRE 3.0, followed by a postscript on how the 2018 GDPR and responses to the Facebook and Cambridge Analytica scandals will also force further ethical reflection. [For the complete volume, "Designs for Experimentation and Inquiry: Approaching Learning and Knowing in Digital Transformation. New Perspectives on Learning and Instruction," see ED661573.]