MESUR: MEtrics from Scholarly Usage of Resources
The project's major objective is enriching the toolkit used for the assessment of the impact of scholarly communication items, and hence of scholars, with metrics that derive from usage data. The project has created a semantic model of the scholarly communication process, and an associated large-scale semantic store that relates a range of bibliographic, citation and usage data obtained from a variety of sources. After mapping the structure of the scholarly community on the basis of the established reference data set, MESUR will conduct an investigation into the definition and validation of a range of usage-based metrics. The defined metrics will be cross-validated, resulting in the formulation of guidelines and recommendations.
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Funding: The Andrew W. Mellon Foundation
Timeline: October 2006 - October 2008
Principal investigator: Johan Bollen
Institution: Los Alamos National Laboratory
Team: Digital Library Research & Prototyping Team of the LANL Research Library
People: Johan Bollen is the Principal Investigator, Herbert Van de Sompel serves as an architectural consultant, and Aric Hagberg of the LANL Mathematical Modeling and Analysis group serves as modeling consultants. Marko A. Rodriguez, a recent PhD graduate at the University of California Santa Cruz and now LANL post-doc at the LANL Center for Non-Linear Science, has supported the project's research and development. Ryan Chute of the LANL Research Library is now the project’s main developer and database manager.
The MESUR data base:
The MESUR data base now contains 1B usage events (2002-2007) obtained from 6 significant publishers, 4 large institutional consortia and 4 significant aggregators! The collected usage data spans more than 100,000 serials (including newspapers, magazines, etc.) and is related to journal citation data that spans about 10,000 journals and nearly 10 years (1996-2006). In addition we have obtained significant publisher-provided COUNTER usage reports that span nearly 2000 institutions worldwide. The data is being ingested into a combination of relational and semantic web databases, the latter of which is now estimated to result in nearly 10 billion semantic statements (triples). MESUR is now producing large-scale, longitudinal maps of the scholarly community and a survey of more than 60 different metrics of scholarly impact.