Multi-touch and tangible interfaces provide unique opportunities for enhancing learning and discovery with big data. However, existing interaction techniques have limitations when manipulating large data sets. Our goal is to define novel interaction techniques for multi-touch and tangible interfaces, which support the construction of complex queries for big data. In this paper, we present results from a study, which investigates the use of gestural interaction with active tokens for manipulating large data sets. In particular, we studied user expectations of a hybrid tangible and gestural language engaging this space. Our main results include a vocabulary of user-defined gestures for interaction with active tokens, which extends beyond familiar multi-touch gestures; characterization of the design space of gestural interaction with active tokens; and insight into participants' mental models, including common metaphors. We also present implications for the design of multi-touch and tangible interfaces with active tokens.

The dramatic growth in the availability of personal genomic data to non-experts, and the use of digital media for delivering personal genomic information, raise important HCI questions. We seek to advance the theory and practice of HCI by investigating fundamental issues concerning non-expert interaction with complex scientific information. Specifically, we explore how people use interactive tools to engage with their personal genomic information.We present findings from a study of 63 early adopters of personal genomics, which highlight users' motivations, information practices, and needs.