Managing Hypothesis of Scientific Experiments with PhenoManager - Ramos, Leonardo; Porto, Fabio; de Oliveira, Daniel (Journal of Information and Data Management, 2021)
Scientific research based on computer simulations is complex since it may involve managing the enormous volumes of data and metadata produced during the life cycle of a scientific experiment, from the formulation of hypotheses to its final evaluation. This wealth of data needs to be structured and managed in a way that makes sense to scientists so that relevant knowledge can be extracted to contribute to the scientific research process. In addition, when it comes to the scope of the scientific project as a whole, it may be associated with several different scientific experiments, which in turn may require executions of different scientific workflows, which makes the task rather arduous. All of this can become even more difficult if we consider that the project tasks must be associated with the execution of such simulations (which may take hours or even days), that the hypotheses of a phenomenon need validation and replication, and that the project team may be geographically dispersed. This article presents an approach called PhenoManager that aims at helping scientists managing their scientific projects and the cycle of the scientific method as a whole. PhenoManager can assist the scientist in structuring, validating, and reproducing hypotheses of a phenomenon through configurable computational models in the approach. For the evaluation of this article was used SciPhy, a scientific workflow in the field of bioinformatics, concluding that the proposed approach brings gains without considerable performance losses.