The Data Perspective of Sensor-enabled Personal Work Support Systems

Abstract

In today’s working world, work intensification and blurring boundaries between life domains pose major challenges. Stress resulting from high working pressure combined with a lack of opportunities for recre-ation can cause serious physical and mental health problems. As sensor technology has become ubiqui-tous and enables new kinds of data collection, it can serve as a foundation for sensor-enabled personal work support systems (SPWSS) assisting users in coping with high work demands while considering individual resources. Such systems could interpret collected data and generate recommendations geared towards maintaining the user’s health, productiveness and wellbeing. However, building systems of this type is a complex task due to the large number of sensors, devices, and software components that have to be integrated. Moreover, this kind of work support relies on processing personal and intimate data from users and thus, require the willingness to share these data. As a first step towards building SPWSS, we investigate the data perspective of such systems. In doing so, we present an architecture of connected devices. Since the willingness of users to share their personal data is a crucial prerequisite for such sys-tems, we furthermore present results from an empirical investigation concerning the willingness of users to share selected data for specific purposes.