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The impact or the quality of academic publications is traditionally measured by considering the number of times the text is cited. Nevertheless, the existing system for citation-based metrics has frequently been the target of serious criticism. Citation data provided by ISI focus on published journal articles only, and other forms of academic output, such as dissertations or monographs are mostly neglected. In addition, it normally takes a long time before citation data can become available, because of publication lags. As a result of this growing dissatisfaction with citation-based metrics, a number of research projects have begun to explore alternative methods for the measurement of academic impact. Many of these initiatives have based their findings on usage data. An important advantage of download statistics is that they can readily be applied to all electronic resources, regardless of their contents. Whereas citation analyses only reveal usage by authors of journal articles, usage data can in theory be produced by any user. An additional benefit of measuring impact via the number of downloads is the fact that usage data can become available directly after the document has been placed on-line.

Virtually all web servers that provide access to electronic resources record usage events as part of their log files. Such files usually provide detailed information on the documents that have been requested, on the users that have initiated these requests, and on the moments at which these requests took place. One important difficulty is the fact that these log files are usually structured according to a proprietary format. Before usage data from different institutions can be compared in a meaningful and consistent way, the log entries need to be standardised and normalised. Various projects have investigated how such data harmonisation can take place. In the MESUR project, usage data have been standardised by serialising the information from log files into XML files structured according to the OpenURL Context Objects schema (Bollen and Van de Sompel, 2006). This same standard is recommended in the JISC Usage Statistics Final Report. Using this metadata standard, it becomes possible to set up an infrastructure in which usage data are aggregated within a network of distributed repositories. The PIRUS-I project (Publishers and Institutional Repository Usage Statistics), which was funded by JISC, has investigated how such exchange of usage data can take place. An important outcome of this project was a range of scenarios for the "creation, recording and consolidation of individual article usage statistics that will cover the majority of current repository installations" "Developing a global standard to enable the recording, reporting and consolidation of online usage statistics for individual journal articles hosted by institutional repositories, publishers and other entities (Final Report)", p.3. <http://www.jisc.ac.uk/media/documents/programmes/pals3/pirus_finalreport.pdf>.

In Europe, at least three projects have experimented with these recommendations and have actually implemented an infrastructure for the central accumulation of usage data: The German OA-Statistics <http://www.dini.de/projekte/oa-statistik/> project, which is funded DINI (Deutsche Initiative für Netzwerk Information), has set up an infrastructure in which various certified repositories across Germany can exchange their usage data. In the Netherlands, the project Statistics on the Usage of Repositories <http://www.surffoundation.nl/nl/projecten/Pages/SURE.aspx>(SURE) has a very similar objective. The project, which is funded by SURFfoundation, aimed to find a method for the creation of reliable and mutually comparable usage statistics and has implemented a national infrastructure for the accumulation of usage data. Third, the Network of European Economists Online <http://www.neeoproject.eu/>(NEEO) is an international consortium of 18 universities which maintains a subject repository that provides access to the results of economic research. As part of this project, extensive guidelines have been developed for the creation of usage statistics.

Whereas these three projects all make use of the OpenURL Context Object standard, some subtle differences have emerged in the way in which this standard is actually used. Nevertheless, it is important to ensure that statistics are produced in exactly the same manner, since, otherwise, it would be impossible to compare metrics produced by different projects. With the support of Knowledge Exchange, a collaborative initiative for leading national science organisations in Europe, an initiative was started to align the technical specifications of these various projects. This document is a first proposal for international guidelines for the accumulation and the exchange of usage data. The proposal is based on a careful comparison of the technical specifications that have been developed by these three projects.

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To be able to compare usage data from different repositories, the data needs to be available in a uniform format. This section will provide specifications for the aspects of the usage event that need to be recorded. In addition, guidelines need to be developed for the format in which this information can be expressed. Following recommendations from MESUR and the JISC Usage Statistics Project, it will be stipulated that usage events need to be serialized in XML using the data format that is specified in the OpenURL Context Objects schema. The XML Schema for XML Context Objects can be accessed at http://www.openurl.info/registry/docs/info:ofi/fmt:xml:xsd:ctx. The specifications for the use of OpenURL ContextObject in this section are more restrictive than the original schema with respect to the occurrence and the permitted values of elements and attributes.

A distinction will be made between the core set and extensions. Data in the core set can be recorded using standard elements or attributes that are defined in the OpenURL Context Object schema. The extensions are created to record aspects of usage events which cannot be captured using the official schema. They have usually been defined in the context of individual projects to meet very specific demands. Nevertheless, some of the extensions may be relevant for other projects as well. They are included here to inform the usage statistics community what additional information could be made available. Naturally, the implementation of all the extension elements are optional.

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