From a user's perspective, rapid-publication "megajournals" like PLoS ONE share a common problem with preprint servers like arXiv or the Social Science Research Network: without traditional quality indicators, researchers are left having to make sense of an ever-growing pile of undifferentiated articles. Readers need better mechanisms at the article level to enable them to see in a moment how one paper relates to others in terms of citation, usage, and other indicators of quality so that they can easily make informed choices about which papers are most relevant to their own research and interests. This two-year grant to the Public Library of Science supports efforts to develop, deploy, and promote just such article-level metrics both for PLoS and for the wider academic community. Funds will support three related activities. First, the PLoS team will extend their existing publishing platform to pull in data well beyond basic download counts, from inbound web links to usage statistics via popular research management platforms like Mendeley and Zotero. Second, PLoS will substantially refine the interfaces used to present that data, testing a number of design approaches to determine what visualizations are most helpful to their users. Finally, PLoS will launch a substantial outreach program, circulating white papers and engaging both open-access and commercial publishers in a broad conversation about article-level metrics adoption. Code developed through this grant will be released under a free/open-source license.