Towards Context-Aware Assistance for Smart Self-Management of Knowledge Workers

Lambusch, Fabienne and Fellmann, Michael (2018) Towards Context-Aware Assistance for Smart Self-Management of Knowledge Workers. In: Joint Proceedings of the BIR 2018 Short Papers, Workshops and Doctoral Consortium, 24-26 Sept 2018, Stockholm, Sweden.

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Abstract

The development of the knowledge-based society and ubiquitous information technology offer individuals a variety of personal and professional possibilities. At the same time, increasing flexibility in modern everyday life can lead to high working pressure and blurring boundaries between life domains. Thus, self-management skills steadily grow in importance. These skills are not only important for productivity, but also for health and wellbeing. The availability of various small sensors and their easy integration into everyday life enables new kinds of data collection. Data ranging from heart rate to location can be analysed and combined with data about tasks and time schedule to provide guidance in self-management. However, up to now it is unclear how such a guidance based on sensor information could be designed and how it can positively contribute to self-management. In our research, we hence provide a first contribution towards context-aware assistance for self-management of knowledge workers. To do so, we first devise a scenario to show how such a system could positively contribute to self-management via a set of interventions based on sensor data. We then present an architecture that conceptualises a context-aware system integrating several data sources along with descriptions of implementation options of such a system. With this, we intend to provide an overview on the design space relevant for the construction of such systems. This overview is meant to inform and inspire the future design of concrete systems that assist knowledge workers in the enhancement of their self-management skills.

Item Type: Conference or Workshop Item (Paper)
Depositing User: Nikola Ivanovic
Date Deposited: 16 Jan 2019 09:15
Last Modified: 16 Jan 2019 09:15
URI: http://eprints.win.informatik.uni-rostock.de/id/eprint/626

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