Standardization efforts and the exchange of protocols to generate data in the life sciences have become a necessity for large scale projects and multinational collaborations. Data in the life sciences are highly context dependent and the processes by which the data were generated need to be well documented. Reproducing, sharing and integrating results across projects is thus a major challenge. The same arguments apply to scientific results that are based on mathematical models and computer simulations. To this end, we develop model management solutions, methods and tools for reusable and reproducible experiments.