Footprint Tracker: reviewing lifelogs and reconstructing daily experiences
This addresses the challenge of memory recall in everyday life for researchers and users of mobile technologies, but appears incremental as it builds on existing methods like Experience Sampling and Day Reconstruction.
The paper tackles the problem of reconstructing daily experiences from memory by introducing Footprint Tracker, a web application that uses passively logged visual, location, and context data to assist users, and reports on a field study to evaluate its effectiveness.
With the increasing emphasis on how mobile technologies are experienced in everyday life, researchers are increasingly emphasizing the use of in-situ methods such as Experience Sampling and Day Reconstruction. In our line of research we explore the concept of Technology-Assisted Reconstruction, in which passively logged behavior data assist in the later reconstruction of daily experiences. In this paper we introduce Footprint tracker, a web application that supports participants in reviewing lifelogs and reconstructing their daily experiences. We focus on three kinds of data: visual (as captured through Microsoft's sensecam), location, and context (i.e., SMS and calls received and made). We describe how Footprint Tracker supports the user in reviewing these lifelogs and outline a field study that attempts to inquire into whether and how this data support reconstruction from memory.