Usage Statistics Review
The JISC Usage Statistics Review Project aimed to formulate a fundamental scheme for repository log files and to propose a standard for their aggregation to provide meaningful and comparable item-level usage statistics for electronic documents (e.g. research papers and scientific resources).
The following elements describing usage events were agreed upon during the stakeholder workshop in Berlin, which was held in the context of the project:
Compulsory items
- Who Identification of user/ session
- What Item identification
- What Type of request performed (e.g. full-text, front-page, including failed/partially fulfilled requests)
- When Date and time
- Usage event ID
Optional elements
- From where Referrer/ the referring entity
- Identity of the service
The described usage events should be exchanged in the form of OpenURL Context Objects using OAI. Automated access (e.g. robots) should be tagged. The definition of automated access has to be straightforward with the option of gradual refinement. Users have to be identified unambiguously but without recording personal data to avoid conflicts with privacy laws.
With the JISC-funded Publisher and Institutional Repository Usage Statistics (PIRUS) and the DFG-funded Open-Access-Statistics there are 2 projects which will formulate standards for usage statistics and work on their implementation. To reach broad comparability national efforts should be bundled together. A central authority – which could for example be the Digital Repository Infrastructure Vision for European Research (DRIVER) – should aggregate the usage data. As the aggregator it would have to de-duplicate the items, which are available from more than one content provider, the tagging of non-human access would be its task, and it would have to engage in the quality control of the data recording.
Policies on statistics should be formulated for the repository community as well as the publishing community. Information about statistics policies should be available on services like OpenDOAR and RoMEO.