Formulation of FAIR Metrics for Primary Research Articles

Measuring the merits of a scholarly article only by how often other articles or social media posts cite it creates a perverse incentive for authors to avoid citing potential rivals. To uphold established standards of scholarship, institutions should also consider one or more metrics of how appropriately an article cites relevant prior work. This paper describes the general characteristics of the FAIR Attribution to Indexed Reports (FAIR) family of metrics, which we have designed for this purpose. We formulate five FAIR metrics suitable for use with primary research articles. Two measure adherence to best practices: number of correctly attributed background statements and number of genuinely original claims. Three measure specific deviations from best practices: number of misattributed background statements, number of background statements with missing references, and number of claims falsely indicated as original. We conclude with a discussion of plans to implement a web application for calculating metric values of scholarly works described by records in Nexus-PORTAL-DOORS System (NPDS) servers.