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 schol- arly impact. However, the formal groundwork to reliably and validly exploit usage data is lacking, and the exact na- ture, meaning and applicability of usage-based metrics is poorly understood. The MESUR project funded by the An- drew 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 chal- lenges 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.
CITATION STYLE
Bollen, J., Van de Sompel, H., & Rodriguez, M. A. (2008). Towards usage-based impact metrics (pp. 231–240). Association for Computing Machinery (ACM). https://doi.org/10.1145/1378889.1378928
Mendeley helps you to discover research relevant for your work.