We introduce FitYou, an interactive dashboard for health data visualizations from wearable devices. It supports the exploration of health trends and health attribute correlations. Wearable devices are small enough to wear on the body and that can be equipped with sensors to track various physical and physiological attributes like heart rate, steps taken, and sleep quality, to just mention a few. By exploiting those attribute values we can visually monitor health-related issues, for example during sports activities like training, a sports competition, or a rehabilitation phase. Activity levels are hard to detect without such support but can help to improve someone’s overall well-being. We illustrate the usefulness of FitYou by means of some application examples. Finally, we discuss the challenges and limitations of the dashboard by focusing on algorithmic, visual, and perceptual issues.

Geospatial planning drives the population-resource-environment system and guarantees sustainable development. In Switzerland, the development of vacancies can be observed in various municipalities. Hence, no optimal geospatial planning is taking place. In this paper, a visual representation in combination with cluster analysis is presented to give the planners support in geospatial shaping. These methods allow to identify commonalities in municipalities and reveal potential options for a geospatial development. For this purpose, public data for eight municipalities are gathered from the Swiss Federal Statistical Office and Open Street Map. Our results give clear commonalities for each municipality and allow to determine the places which have more development resources.

The number π has motivated mathematicians and math enthusiasts for millennia. John Venn was one of the first to use visualizations with π. In this paper, we use visualizations to reveal patterns in the first 62.8 trillion digits of π. We computed the distribution of natural numbers and identified the longest sequences of the Fibonacci sequence, the longest sequences of the natural numbers and identified the longest series of the same digit. We observed that no regular distribution of the natural numbers appears.

Public transport maps are typically designed in a way to support route finding tasks for passengers while they also provide an overview about stations, metro lines, and city-specific attractions. Most of those maps are designed as a static representation, maybe placed in a metro station or printed in a travel guide. In this paper we describe a dynamic, interactive public transport map visualization enhanced by additional views for the dynamic passenger data on different levels of temporal granularity. Moreover, we also allow extra statistical information in form of density plots, calendar-based visualizations, and line graphs. All this information is linked to the contextual metro map to give a viewer insights into the relations between time points and typical routes taken by the passengers. We illustrate the usefulness of our interactive visualization by applying it to the railway system of Hamburg in Germany while also taking into account the extra passenger data. As another indication for the usefulness of the interactively enhanced metro maps we conducted a user experiment with 20 participants.