Towards reusability of computational experiments: Capturing and sharing Research Objects from knowledge discovery processes

Abstract

Calls for more reproducible research by sharing code and data are released in a large number of fields from biomedical science to signal processing. At the same time, the urge to solve data analysis bottlenecks in the biomedical field generates the need for more interactive data analytics solutions. These interactive solutions are oriented towards wet lab users whereas bioinformaticians favor custom analysis tools. In this position paper we elaborate on why Reproducible Research, by presenting code and data sharing as a gold standard for reproducibility misses important challenges in data analytics. We suggest new ways to design interactive tools embedding constraints of reusability with data exploration. Finally, we seek to integrate our solution with Research Objects as they are expected to bring promising advances in reusability and partial reproducibility of computational work.