Data interpretation involves translating statistically significant results into meaningful insights: transforming values into pathways and mechanisms, and organizing scattered facts into a coherent story. While high-quality data generation in metabolomics is achievable, standardizing interpretation remains challenging. Justin van der Hooft (Wageningen), Bart Ghesquière (Leuven), and Alice Limonciel (Innsbruck) will discuss their individual projects and methodologies, highlighting both the successes and challenges of data interpretation. They will share their latest tools designed to maximize the impact of metabolomics on research and health.