Light dosimetry aims to measure personal light exposure with wearable sensors, which is a complex multistep procedure. The resulting data may be used to investigate non-visual effects of light in real-life settings, to validate laboratory findings and answer questions pertaining to implications in applied contexts. However, personal light exposure patterns are usually complex and can be quantified in many ways. Various measurement and analysis methods have been applied across previous studies, complicating comparability and interpretation of results. To improve the quality and comparability of light-dosimetry research, a framework with consensus guidelines for light-dosimetry procedures is needed. To provide the groundwork towards such a framework, we reviewed previous light-dosimetry studies to identify considerations regarding measurement and data quantification. Here, we review metrics for quantifying light-dosimetry data in terms of the characteristics known to modulate non-visual responses. Overall, various metrics have been employed across studies, with several metrics for each characteristic. We provide a description of each metric, discuss their properties and provide example calculations for the application to light-dosimetry data. Moreover, we propose considerations for data quantification and possible research strategies for future studies. To facilitate exploration and use of the identified metrics, corresponding functions are provided in an openly accessible R-package.