Navigating in large geometric spaces-such as maps, social networks, or long documents-typically requires a sequence of pan and zoom actions. However, this strategy is often ineffective and cumbersome, especially when trying to study and compare several distant objects. We propose a new distortion technique that folds the intervening space to guarantee visibility of multiple focus regions. The folds themselves show contextual information and support unfolding and paging interactions. We conducted a study comparing the space-folding technique to existing approaches and found that participants performed significantly better with the new technique. We also describe how to implement this distortion technique and give an in-depth case study on how to apply it to the visualization of large-scale 1D time-series data.

Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a "program" that tells the computer what to do when future inputs arrive. Little research has explored how an end user can debug these programs when they make mistakes. We present our progress toward enabling end users to debug these learned programs via a Natural Programming methodology. We began with a formative study exploring how users reason about and correct a text-classification program. From the results, we derived and prototyped a concept based on "explanatory debugging", then empirically evaluated it. Our results contribute methods for exposing a learned program's logic to end users and for eliciting user corrections to improve the program's predictions.

The recent emphasis on sustainability has made consumers more aware of their responsibility for saving resources, in particular, electricity. Consumers can better understand how to save electricity by gaining awareness of their consumption beyond the typical monthly bill. We conducted a study to understand consumers' awareness of energy consumption in the home and to determine their requirements for an interactive, always-on interface for exploring data to gain awareness of home energy consumption. In this paper, we describe a three-stage approach to supporting electricity conservation routines: raise awareness, inform complex changes, and maintain sustainable routines. We then present the findings from our study to support design implications for energy consumption feedback interfaces.

Caring for the elderly is becoming a key challenge for society, given the shortage of trained personnel and the increased age of the population. Innovative approaches are needed to help the elderly remain at home longer and more safely, that is, to age in place. One popular strategy is to monitor the activity of the elderly: this focuses on obtaining information for caregivers rather than supporting the elderly directly. We propose an alternative, i.e. to enhance their inter-personal communication. We report the results of a user study with 14 independent elderly women and discuss the existing role that communication plays in maintaining their independence and wellbeing. We highlight the importance of peer support relationships, which we call PeerCare, and how awareness of each other's rhythms and routines helps them to stay in touch. We then describe the deployment of a technology probe, called markerClock, which a pair of elderly friends used to improve their awareness of each other's rhythms and routines. We conclude with a discussion of how such communication appliances enhance the awareness of rhythms and routines among elderly peers and can improve their quality of life and provide safer and more satisfying aging in place.