Article-Level Metrics

Traditionally, the impact of research articles has been measured by the publication journal. But a more informative view is one that examines the overall performance and reach of the articles themselves. Article-Level Metrics (ALM) capture the manifold ways in which research is disseminated and used.


From: Fenner M, Lin J (2013). Altmetrics in Evolution: Defining & Redefining the Ontology of Article-Level Metrics.

Data-Level Metrics

The collection of metrics shouldn't be limited to journal articles, but should include all relevant research outputs, e.g. datasets (data-level metrics) and software (software-level metrics).


Lagotto is an Open Source application started in March 2009 by the Open Access publisher Public Library of Science (PLOS). Lagotto retrieves data from a wide set of services (sources). Some of these sources represent the actual channels where users are directly viewing, sharing, discussing, citing, recommending the works (e.g., Twitter and Mendeley). Others are third-party vendors which provide this information (e.g., CrossRef for citations).

For Publishers and Providers

Detailed instructions on how to install and setup Lagotto are available in the documentation, and the installation and setup can be done in under an hour.

The following organizations are using Lagotto (live status information available here):

For Users

Users can access the data via the API, or via one of the client applications:

For Developers

We always welcome feedback and code contributions, and we have a growing list of contributors. For questions or comments regarding Lagotto, visit the Lagotto support forum or use the Github issue tracker.