A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientific Workflows: A Case Study

  • Idafen Santana-Perez
  • Rafael Ferreira da Silva
  • Mats Rynge
  • Ewa Deelman
  • María S. Pérez-Hernández
  • Oscar Corcho
Conference paper

DOI: 10.1007/978-3-319-14325-5_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8805)
Cite this paper as:
Santana-Perez I., Ferreira da Silva R., Rynge M., Deelman E., Pérez-Hernández M.S., Corcho O. (2014) A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientific Workflows: A Case Study. In: Lopes L. et al. (eds) Euro-Par 2014: Parallel Processing Workshops. Euro-Par 2014. Lecture Notes in Computer Science, vol 8805. Springer, Cham

Abstract

Reproducible research in scientific workflows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and final results, improves understanding, and permits replaying a workflow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We define a process for documenting the workflow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation using a real workflow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predefined virtual machine image on both computing platforms.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Idafen Santana-Perez
    • 1
  • Rafael Ferreira da Silva
    • 2
  • Mats Rynge
    • 2
  • Ewa Deelman
    • 2
  • María S. Pérez-Hernández
    • 1
  • Oscar Corcho
    • 1
  1. 1.Ontology Engineering GroupUniversidad Politécnica de MadridMadridSpain
  2. 2.USC Information Sciences InstituteMarina Del ReyUSA

Personalised recommendations