Big Data and Data Reuse: A Taxonomy of Data Reuse for Balancing Big Data Benefits and Personal Data Protection

Abstract

The emergence of Big Data has amounted to the complexity of the discussion on data reuse. The benefits of Big Data lie in the possibilities to discover novel trends, patterns and relationships by combining very large amounts of data from different sources. 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. Substantial loss of economic and social benefits of Big Data may be the result. In order to avoid this, the reuse of data could be encouraged. Data reuse, when done properly, may be both privacy preserving and economically and socially beneficial. In this paper, 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 recontextualisation. From the data subject’s perspective, we distinguish data sharing and data portability. It is argued that forms of data reuse that stay close to the awareness and intentions of data subjects should be approached less tight (for instance, by assuming informed consent), whereas forms of data reuse that are ‘at a distance’, i.e., 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).