  Numerous applications capture in digital form aspects of people's lives. The
resulting data, which we call Personal Digital Traces - PDTs, can be used to
help reconstruct people's episodic memories and connect to their past personal
events. This reconstruction has several applications, from helping patients
with neurodegenerative diseases recall past events to gathering clues from
multiple sources to identify recent contacts and places visited - a critical
new application for the current health crisis. This paper takes steps towards
integrating, connecting and summarizing the heterogeneous collection of data
into episodic narratives using scripts - prototypical plans for everyday
activities. Specifically, we propose a matching algorithm that groups several
digital traces from many different sources into script instances (episodes),
and we provide a technique for ranking the likelihood of candidate episodes. We
report on the results of a study based on the personal data of real users,
which gives evidence that our episode reconstruction technique 1) successfully
integrates and combines traces from different sources into coherent episodes,
and 2) augments users' memory of their past actions.
