Recent technological advances have introduced new types of personal sensors (wearable sensors, informational sensors) and devices (for example Google Glass or Apple’s iWatch) which allow the individual to compile vast archives of personal data, commonly referred to as lifelogs. Captured over a long period of time, these heterogeneous digital lifelogs can provide a detailed picture of the activities of an individual and will require search, summarisation and knowledge extraction tools to allow the users or practitioners to extract value from the data. However, there are significant challenges to be addressed, concerning the gathering, enriching, searching and visualising of such data. This special session aims to bring together interdisciplinary researchers and practitioners to discuss approaches to lifelog data analytics and the applications of same in a discussion-focused special session, and to debate the opportunities and challenges for researchers in this new and challenging area. The disciplines involved include multimedia analytics, wearable and ubiquitous computing, HCI, information retrieval, cognitive science and healthcare and wellness.
The main topics of interest include:
- – Tools supporting the creation of lifelogs and personal data archives
- – Multimedia data analytics and semantic enrichment for lifelog and quantified- self data
- – User experience design for accessing personal data archives
- – Privacy and data security challenges of personal data archives
- – Applications of lifelogging and experiences of same
- – Experiences of lifelogging and quantified -self activities
- – Ethical issues arising from lifelogging and personal data gathering
- – Digital preservation and maintenance of personal data archives
Session organizers:
- –Xavier Giro-i-Nieto (Universitat Politecnica de Catalunya, Spain)
- –Petia Radeva (University of Barcelona, Spain)
- –David J. Crandall (Indiana University, USA)
- –Giovanni Farinella (University of Catania, Italy)
- –Duc Tien Dang Nguyen (Dublin City University, Ireland)
- –Mariella Dimiccoli (Computer Vision Centre, Universitat de Barcelona, Spain)
- –Cathal Gurrin (Dublin City University, Ireland)
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