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structural models of scholarly influence from said usage data, and surveying a range of impact metrics from the usage and citation it collected.


FIGURE 3-2 Modeling the scholarly communication process — the MESUR ontology.2

So far, the MESUR project has collected more than one billion usage events3 from publishers, aggregators and institutions serving the scientific community. These include: BioMedCentral, Blackwell, the University of California, EBSCO Publishing, Elsevier, Emerald, Ingenta, J- STOR, the Los Alamos National Laboratory, Zetoc project of the University of Manchester, Thomson, the University of Pennsylvania, and the University of Texas.

This data provided to the project has to conform to specific requirements, which were fortunately met by all our providers. In particular, we required that the data had an anonymous but unique user identifier, unique document identifiers, data and time of the user request to the second, an indicator of the type of request, and a session identifier, generated by the provider’s server, which indicates whether the same user accesses other documents within the same session.

The latter is an important element of the MESUR approach. We are not just interested in total downloads, but their context, the structural features of how people access scholarly communication items over time. We therefore required session identifiers, meaning that if users access a document at a particular time, they are assigned a session identifier before they move on to the next document. They maintain this session identifier throughout their movement from one


2 Marko A Rodriguez, Johan Bollen and Herbert Van de Sompel. A Practical Ontology for the Large-Scale Modeling of Scholarly Artifacts and their Usage, In Proceedings of the Joint Conference on Digital Libraries 2007, Vancouver, June 2007.

3 Data from more than 110,000 journals, newspapers and magazines, along with publisher-provided usage reports covering more than 2,000 institutions, is being ingested and normalized in MESUR’s databases, resulting in large- scale, longitudinal maps of the scholarly community and a survey of more than 40 different metrics of scholarly impact.

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