Multi-Mode Tensor Representation of Motion Data

In this paper, we investigate how a multilinear model can be used to represent human motion data. Based on technical modes (referring to degrees of freedom and number of frames) and natural modes that typically appear in the context of a motion capture session (referring to actor, style, and repetition), the motion data is encoded in form of a high-order tensor. This tensor is then reduced by using N-mode singular value decomposition. Our experiments show that the reduced model approximates the original motion better then previously introduced PCA-based approaches. Furthermore, we discuss how the tensor representation may be used as a valuable tool for the synthesis of new motions.

Privacy as human flourishing: Could a shift towards virtue ethics strengthen privacy protection in the age of Big Data?

Privacy is commonly seen as an instrumental value in relation to negative freedom, human dignity and personal autonomy. Article 8 ECHR, protecting the right to privacy, was originally coined as a doctrine protecting the negative freedom of citizens in vertical relations, that is between citizen and state. Over the years, the Court has extended privacy protection to horizontal relations and has gradually accepted that individual autonomy is an equally important value underlying the right to privacy. However, in most of the recent cases regarding Article 8 ECHR, the Court goes beyond the protection of negative freedom and individual autonomy and instead focuses self-expression, personal development and human flourishing. Accepting this virtue ethical notion, in addition to the traditional Kantian focus on individual autonomy and human dignity, as a core value of Article 8 ECHR may prove vital for the protection of privacy in the age of Big Data.

Ten Questions for Future Regulation of Big Data: A Comparative and Empirical Legal Study

Much has been written about Big Data from a technical, economical, juridical and ethical perspective. Still, very little empirical and comparative data is available on how Big Data is approached and regulated in Europe and beyond. This contribution makes a first effort to fill that gap by presenting the reactions to a survey on Big Data from the Data Protection Authorities of fourteen European countries and a comparative legal research of eleven countries. This contribution presents those results, addressing 10 challenges for the regulation of Big Data.