Advances in digital capture and storage technologies mean
that it is now possible to capture and store one’s entire life experiences in a Human Digital Memory (HDM). However,
these vast personal archives are of little benefit if an individual cannot locate and retrieve significant items from
them. While potentially offering exciting opportunities to
support a user in their activities by providing access to information stored from previous experiences, we believe that the features of HDM datasets present new research challenges for information retrieval which must be addressed if these possibilities are to be realised. Specifically we postulate that effective retrieval from HDMs must exploit the rich sources of context data which can be captured and associated with items stored within them. User’s memories
of experiences stored within their memory archive will often
be linked to these context features. We suggest how such
contextual metadata can be exploited within the retrieval
process