Databases are key to knowledge management and to implement FAIR (Findable, Accessible, Interoperable, and Reusable) principles in scientific research. However, most experimental sorption data remain underused owing to heterogeneous reporting practices, incomplete metadata, or lack of standardization. Furthermore, existing sorption databases often focus primarily on distribution coefficients (K d ), with a limited description of the broader physicochemical context, thereby restricting their applicability to comprehensive geochemical analyses. This study proposes a structured framework for the generation and organization of sorption data to guide experimentalists in producing reusable datasets. The framework defines key principles for the construction of sorption databases, including the types of data to be collected (e.g., distribution coefficients, K d , and relevant geochemical parameters), as well as the distinction between measured and derived data. The methodology is demonstrated using experimental sorption data on cesium retention in crystalline rocks, comprising approximately 1000 K d values, complemented by detailed physicochemical information on the experimental conditions, aqueous chemistry, and solid properties. Example applications, ranging from statistical analyses to sorption modelling, illustrate the potential of the approach and highlight the added value of comprehensive and well-structured datasets. The proposed framework can be further developed to foster more systematic and collaborative approaches to experimental data management, and can be applied to other radionuclides and materials.
Missana et al. (Tue,) studied this question.