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Abstract
We are living in an era of social media such as online communities and social networking sites. Exposing or sharing personal information with these communities has risks as well as benefits and there is always a trade off between the risks versus the benefits of using these technologies. Life-logs are pervasive tools or systems which sense and capture contextual information from the user's environment in a continuous manner. A life-log produces a dataset, which consists of continuous streams of sensor data. Sharing this information has a wide range of advantages for both user and society. On the other hand, in terms of individual privacy, life-log information is very sensitive. Although social media enable users to share their information, due to life-log data structure, current sharing models are not capable of handling life-log information while maintaining user privacy. Our approach here is to describe the sharing of life-log information with society based on the identification of associated risks and benefits. Subsequently, based on the identified risks, we propose a data model for sharing life-log information. This data model has been designed to reduce the potential risks of life-logs. Furthermore, ethics for providing and using life-logs will be discussed. These ethics focus on reducing risks as much as possible while sharing life-log information.
Acknowledgements
We acknowledge Dr Shahin Gheitanchi from the Communications Research group at the University of Sussex and Prof. Wolfgang Klas from the Department of Distributed and Multimedia Systems at the University of Vienna for their helpful hints and feedback on this research.
Notes
7. Java Script Object Notation
8. Relational Database Management Systems
