  Digital traces of our lives are now constantly produced by various connected
devices, internet services and interactions. Our actions result in a multitude
of heterogeneous data objects, or traces, kept in various locations in the
cloud or on local devices. Users have very few tools to organize, understand,
and search the digital traces they produce. We propose a simple but flexible
data model to aggregate, organize, and find personal information within a
collection of a user's personal digital traces. Our model uses as basic
dimensions the six questions: what, when, where, who, why, and how. These
natural questions model universal aspects of a personal data collection and
serve as unifying features of each personal data object, regardless of its
source. We propose indexing and search techniques to aid users in searching for
their past information in their unified personal digital data sets using our
model. Experiments performed over real user data from a variety of data sources
such as Facebook, Dropbox, and Gmail show that our approach significantly
improves search accuracy when compared with traditional search tools.
