Abstract
Cyclic voltammetry (CV) is a valuable tool for electrochemistry, providing qualitative and quantitative information about redox processes occurring in solution. Despite its ubiquity, the lack of standardized reporting and sharing protocols, commonly adopted, significantly hinders data reusability and reproducibility. Here, we present DUCK (Database Utility for Cyclovoltammetry Knowledge), a comprehensive platform for organizing, analyzing and exploring CV data through ontology-based knowledge graphs. The system comprises three components: (1) CVOnto, a formal ontology for electrochemical CV measurement data, (2) DUCK-KG, an automated tool for the generation of knowledge graphs from experimental metadata, and (3) DUCK-Viz, an interactive web interface for visualization and analysis of CV data. We demonstrate applicability across two distinct domains: 130 CV experiments from electrodeposition studies in traditional laboratories, and 79 automated measurements from metal-ligand complexes in self-driving laboratories, performing Bayesian optimization workflows. The application to these two paradigms demonstrates DUCK's potential as a unified platform implementing FAIR data principles for the electrochemistry community.