LAD: an application design model to support the analysis of large-scale personal data collections generated by lifelogging

Abstract

Lifelogging is a form of personal data collection which seeks to capture the totality of one’s experience through intelligent technology and sensors. Yet despite notable advancement in such technologies, there remain persistent challenges to developing interactive systems to analyse the types of large-scale personal collections often generated by lifelogging. In response to this, we present the Lifelog Application Design (LAD) model which is intended to address these challenges and support the design of more novel interactive systems that may target a broader range of application use cases. The model is deliberately structured to remain impartial to the specific personal data, technology platform, or application criterion, to provide maximum utility across the domain. We demonstrate this utility by exploring two case studies and a retrospective analysis of VRLE, a real-world application prototype developed to examine the potential of large-scale personal data retrieval in virtual reality. This work is based on the accumulation of insights garnered from involvement in a number of collaborative lifelogging projects over the past decade. It is our goal to encourage future researchers to utilise the LAD model to support the design and development of their own application prototypes and further solidify the model’s contribution to the domain as a whole.