  Scholarly usage data holds the potential to be used as a tool to study the
dynamics of scholarship in real time, and to form the basis for the definition
of novel metrics of scholarly impact. However, the formal groundwork to
reliably and validly exploit usage data is lacking, and the exact nature,
meaning and applicability of usage-based metrics is poorly understood. The
MESUR project funded by the Andrew W. Mellon Foundation constitutes a
systematic effort to define, validate and cross-validate a range of usage-based
metrics of scholarly impact. MESUR has collected nearly 1 billion usage events
as well as all associated bibliographic and citation data from significant
publishers, aggregators and institutional consortia to construct a large-scale
usage data reference set. This paper describes some major challenges related to
aggregating and processing usage data, and discusses preliminary results
obtained from analyzing the MESUR reference data set. The results confirm the
intrinsic value of scholarly usage data, and support the feasibility of
reliable and valid usage-based metrics of scholarly impact.
