On the Compatibility of Big Data Driven Research and Informed Consent: The Example of the Human Brain Project

Abstract

Big Data research is usually explorative, meaning that not all possible hypotheses are known that one may wish to test when data is made available. For the case of biomedical data this poses a significant challenge, as the originators of the data – patients or research participants – have to provide informed consent for using their data. The typically obtained “closed” or “narrow consent”, i.e. consenting to use the data in a well-defined research project, is conceptually incompatible with the explorative nature of Big Data driven research. Therefore, “open” or “broad consent” is proposed as an alternative. Nevertheless, open consent cannot justify any type of data use, but requires an “information framework” that separates legitimate from illegitimate Big Data research. For example, consent is given associated with established disease categories: a patient diagnosed with early-onset Alzheimer’s disease may consent to his personal medical information being used for any research enhancing our understanding of this particular disease. In our contribution, we address the question whether and how Big Data driven research may undermine this “information framework” of informed consent using the example of the Human Brain Project (HBP). Within the HBP, a Big Data infrastructure is currently being developed to access a multitude of clinical data related to brain diseases based on the conviction that many neurological and psychiatric disorders and diseases are ill-defined in terms of underlying mechanisms. We analyse the interrelation between effects of Big Data research and informed consent and we evaluate ethical and practical consequences.