• ownership rights
• non-personal data
• intellectual property
• industrial data
• big data

The aim of this study is to analyse the complex relationship between non-personal data and law. Non-personal data, also known as industrial data, are mainly machine-generated or collected through sensor and represent an important source of valuable knowledge for businesses, especially in the light of better, cheaper and quicker production processes.
Non-personal data can be contextualised in relation to the wider big data environment, with all its social, economic and legal implications. We will therefore gradually shape the topic from the general big data perspective to the more specific perspective focused on industrial data. The main purpose is to find a potential legal framework for non-personal data, as at present the subject matter has not been addressed by specific legal norms yet. This study will in particular highlight the intricated relationship between law and technology against the backdrop of the difficult balance between regulating and fostering innovation.
The basic question behind this study is: who owns industrial data?
First of all we will test some of the existing IP categories in relation to their suitability for protecting non-personal data. In particular the analysis regards the database protection scheme, the trade secret regime and some aspects of patent law.
Following the partially unsatisfactory outcome of the intellectual property test, the study attempts to find an alternative approach, namely the protection of non-personal data in the form of proprietary rights. The practical example of the automotive industry perfectly shows the difficulties in allocating ownership between different stakeholders involved in production processes. We analyse the merits and demerits of different points of view on the topic. Although it might be too premature to favour one specific approach, some proposals are more appropriate than others.