Abstract
Since 2009, the Public Library of Science (PLOS) has provided comprehensive article-level metrics for all publications in its PLOS journals. These PLOS articlelevel metrics (PLOS ALM) reflect the attention an individual article has received from the scientific community and other parties online and include citations, social media mentions, usage statistics, bookmarks and recommendations. Conceptually, in PLOS ALM all metrics are divided into the five categories of Viewed, Saved, Discussed, Recommended, and Cited,which represent different levels of engagement with respective articles. The Public Library of Science offers three essential ways for accessing their PLOS ALM data: visualizations on articles’ landing pages, raw metrics data via an API, and via the reporting tool PLOS ALM Reports. Moreover, the Open Source application used for collecting PLOS ALM, called Lagotto, can be installed and customized to flexibly retrieve metrics data from a large variety of sources and thus create ALM datasets. This makes PLOS ALM an interesting starting point for users who aim to establish an ALM database for their own publication corpora. Comparisons of PLOS ALM to metrics from other providers, e.g. Altmetric.com, Cross- Ref, or Plum Analytics, have shown that conceptual and technological differences between providers can lead to very different metrics values for the same articles across them. Hence, increased caution is necessary when using ALM from different providers side by side.
