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Scientific Programming
Volume 2015, Article ID 243180, 11 pages
http://dx.doi.org/10.1155/2015/243180
Research Article

Towards Reproducibility in Scientific Workflows: An Infrastructure-Based Approach

Ontology Engineering Group (OEG), Universidad Politécnica de Madrid, Avenida Montepríncipe, s/n, 28660 Boadilla del Monte, Spain

Received 12 September 2014; Accepted 3 February 2015

Academic Editor: Gianluigi Greco

Copyright © 2015 Idafen Santana-Perez and María S. Pérez-Hernández. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

It is commonly agreed that in silico scientific experiments should be executable and repeatable processes. Most of the current approaches for computational experiment conservation and reproducibility have focused so far on two of the main components of the experiment, namely, data and method. In this paper, we propose a new approach that addresses the third cornerstone of experimental reproducibility: the equipment. This work focuses on the equipment of a computational experiment, that is, the set of software and hardware components that are involved in the execution of a scientific workflow. In order to demonstrate the feasibility of our proposal, we describe a use case scenario on the Text Analytics domain and the application of our approach to it. From the original workflow, we document its execution environment, by means of a set of semantic models and a catalogue of resources, and generate an equivalent infrastructure for reexecuting it.