Big data and data reuse: a taxonomy of data reuse for balancing big data benefits and personal data protection

Current personal data protection requirements like data minimization and purpose specification are potentially inimical to Big Data as they limit the size and use of Big Data. Potential benefits of Big Data to discover novel trends, patterns, and relationships may not materialize. Substantial loss of economic and social benefits of Big Data may be the result. In order to realize Big Data benefits, the reuse of data could be encouraged. Data reuse, when done properly, may be both privacy preserving and economically and socially beneficial. In this article, we provide a taxonomy of data reuse from both the data controller's and the data subject's perspective that may be useful to determine the extent to which data reuse should be allowed and under which conditions. From the data controller's perspective, we distinguish data recycling, data repurposing, and data recontextualization. From the data subject's perspective, we distinguish data sharing and data portability. Forms of data reuse that stay close to the awareness and intentions of data subjects should be approached less restrictively (for instance, by assuming informed consent), whereas for forms of data reuse that are 'at a distance', ie, in which awareness and transparency may be lacking and data subject's rights may prove more difficult to exercise, more restrictions, and additional protection should be considered (for instance, by requiring explicit consent).