What are article level metrics?
Article level metrics can be broadly described as measures that characterize the use, influence, or popularity of a single article in a scholarly journal. These metrics offer users the opportunity to discover the wider impact of individual articles in a way that was not previously possible.
The availability of article level metrics is not new; they have mostly been accessible to users direct from third-party services. The aggregation of these data and the addition of usage information is a new service that IOP Publishing (IOP) is offering as a direct result of requests from the scientific community.
IOP and article level metrics
In the fall of 2012, IOP added article level metrics to over 30 journals on IOPscience. The data currently available to users is a mixture of article usage data from the IOPscience server logs and data collected from third parties such as Mendeley and CiteULike.
To see examples of IOP’s implementation of article level metrics, we invite you to browse the metrics page for the following articles:
How will this system be used?
Article level metrics are another tool in the toolbox available to scholars, funding agencies, and universities to help understand how individual articles are being used in close to real time. The potential use cases are varied but could involve:
Article level metrics are not meant to displace other methods of assessing value but instead are meant to augment the datasets currently available to form a more complete picture of usage.
Where can I find out more?
More information can be found by visiting the IOPscience information page on article level metrics. On this page, you can read about the power (and limitation) of IOP’s implementation of article level metrics and find links to even more information.