Investigation of the descriptors to make the scientific workflows reproducible

The complexity of the scientific workflows and the continuously changing nature of the environment makes it hard or even prevents to reproduce the workflows or share their results in the scientist's community. The main factors which can influence the reproducibility are the descriptors (resources, system variables, code variables, inputs, parameters etc. required to re-execute the workflow) that are continuously changing in time or become unavailable during the years (typically third party resources). The ultimate goal of my research is to reveal the behavior of the crucial descriptors which can prevent the reproducibility and to find the relationship between the change of the descriptors and the change of the result. Based on the nature of the change, and its relation to the result evaluation can be performed to replace the missing descriptor values with simulated ones. In this way we intend to support the scientist to create a reproducible scientific workflow. In addition, with determining the probability of the reproducibility we can also help the scientists to find the most suitable scientific workflow in a repository which they can reuse and create their own experiment.