The document discusses an app that recommends solvents for recrystallizing compounds by using open data sources and algorithms. It summarizes how the app works by looking up solvent properties like boiling point and solubility to predict recrystallization yield. The discussion emphasizes the importance of open data, models and software in chemistry. It provides examples of using open data sources and models to predict properties, validate data, and enable new applications. The conclusions advocate for more openness in chemistry to make science more efficient.