Since their codification in 2016, the FAIR Data Principles have provided a framework and a banner around which those involved in scholarly communications have rallied to improve the state and status of non-article based research outputs. Yet, although this has led to new investments, products and services around FAIR, many stakeholders – both organisational and individual – are uncertain how to navigate effectively through the new requirements. This is especially critical for the ongoing tension between research outputs and the evaluation of both outputs and researchers themselves. This presentation clarifies key FAIR requirements as evidenced by work done to date. It also highlights ongoing challenges and posits next steps for reflection, implementation and further discussion.