Towards Reproducibility in Scientific Workflows: An Infrastructure-Based Approach

Abstract EN

It is commonly agreed that in silico scientific experiments should be executableand repeatable processes.

Most of the current approaches for computationalexperiment conservation and reproducibility have focused so far on two of the maincomponents of the experiment, namely, data and method.

In this paper, we propose a new approach that addresses the third cornerstone ofexperimental reproducibility: the equipment.

This work focuses on the equipment ofa computational experiment, that is, the set of software and hardware componentsthat are involved in the execution of a scientific workflow.

In order to demonstratethe feasibility of our proposal, we describe a use case scenario on the Text Analyticsdomain and the application of our approach to it.

From the original workflow, wedocument its execution environment, by means of a set of semantic models and acatalogue of resources, and generate an equivalent infrastructure for reexecuting it.