Important Dates

Recent technological advances have introduced new types of personal sensors (wearable sensors, informational sensors) and devices (for example, Google Glass, Narrative Clip 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.

Therefore, it comes as no surprise that lifelogging is receiving increasing attention within the research community, and is fast becoming a mainstream research topic. An example is the new
lifelog evaluation task at NTCIR-12 that focuses on the evaluation of access methodologies for large lifelogs. At the same time, technologies such as the Narrative Clip wearable camera, Google Glass (II) and the quantified-self movement are motivating individuals to gather archives of personal multimodal data, unprecedented in terms of volume and variety. Apart from technical challenges arising from gathering, semantic enrichment and accessing such vast amount of data, various additional aspects need to be considered that are concerned with the impact on these new technological advances both for individuals as well as for society as a whole.

This workshop proposal aims to bring the attention of lifelogging to the attention of the ACM Multimedia audience and motivate some of the key research challenges that the community will need to address in the coming years. This follows on from a successful related workshops and panels at
JCDL 2015, iConf 2016 and fills a gap left by the ending of the SenseCam series of conferences in 2013. This workshop would be of interest to a broad spectrum of ACM MM 2016 attendees, from those interested in multimedia data analytics, search and retrieval, to those who focus on user experience, real-world applications and captology from personal data.