Personal Informatics at UbiComp2014

At the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2014) we had the 5th international workshop on Personal Informatics.

pi_ubicomp2014This year the workshop was framed as the “Disasters in Personal Informatics: The Unpublished Stories of Failure and Lessons Learned”. The idea was to stimulate a discussion on the challenges involved in conducting research in personal informatics. Nine interesting papers were discussed in three themes as part of the workshop program: Personal Informatics in Life, Data Collection and Quality, and Engagement in Longitudinal Studies.

My PhD student Andrea Cuttone and I presented our work: “The Long Tail Issue in Large Scale Deployment of Personal Informatics” discussing issues in carrying out Personal Informatics research as part of our large-scale SensibleDTU study.

Personal Informatics Workshop @ CHI2013

As part of the ACM CHI2013 conference we held our two day Personal Informatics Workshop and hackathon. We had a record number of submissions and accepted 24 papers. Google had kindly sponsored the workshop with a number of self-tracking devices that participants could use as part of their hackathon projects.


During the two day hackathon five groups developed personal informatics concepts and systems and we concluded the workshop with a joint meetup with the local Quantified Self Paris Meetup Group where the groups presented their results.


QS Spiral: Visualizing Periodic Quantified Self Data

As part of the Personal Informatics Workshop at CHI2013 we presented our paper QS Spiral: Visualizing Periodic Quantified Self Data. The paper is co-authored with Andrea Cuttone and Sune Lehmann.

spiral1 spiral2

In the paper we propose an interactive visualization technique QS Spiral that aims to capture the periodic properties of quantified self data and let the user explore those recurring patterns. The approach is based on time-series data visualized as a spiral structure. The interactivity includes the possibility of varying the time span and the time frame shown, allowing for different levels of detail and the discoverability of repetitive patterns in the data on multiple scales.