Quantified self data

Best paper award to Media Technology staff for visualizing quantified self data

Isabella Nake, Aris Alissandrakis and Janosch Zbick presented a way to give users insight into their own activity data, at the International Conference on Advances in Computer-Human Interactions (ACHI 2016).

We use an ever greater amount of apps and devices to keep track of our activities, be it music we listen to, pictures we take or physical exercises. In most cases, however, the apps or devices are in control of all information and we are limited in how to explore or interact with the data.

This is something that Isabella Nake, graduated master student of the Social Media and Web Technologies programme, together with Dr Aris Alissandrakis, Senior Lecturer at the Department of Media Technology, and Janosch Zbick, Doctoral Student, want to change. Their paper "Visualizing Quantified Self Data Using Avatars" won one of the best paper awards at the Ninth International Conference on Advances in Computer-Human Interactions (ACHI 2016) that took place 24-28 April 2016 in Venice, Italy.

The paper investigates a new approach of visualizing so-called quantified self data, in a meaningful and enjoyable way that gives the users insights into their personal data. It discusses the feasibility of creating a service that allows users to connect the activity tracking applications they already use, analyses the amount of activities, and then presents them the resulting information. The visualization is proposed as an avatar that maps the different activities the user is engaged with.

Besides the award, the authors have also received invitation to submit an extended article version of the conference paper for a journal.

More information

ACHI 2016
The submitted paper