Presentation held at XSEDE'14 - Atlanta, USA Abstract - Reproducibility of published results is a cornerstone in scientific publishing and progress. Currently, most of the approaches in computational science conservation, in particular for scientific workflow executions, have been focused on data, code, and the workflow description, but not on the underlying infrastructure. we propose a logical-oriented approach to conserve computational environments, where the capabilities of the resources (virtual machines (VM)) are semantically described. We propose to describe the resources involved in the execution of the experiment, using a set of semantic vocabularies, and use those descriptions to define the infrastructure specification. This specification can then be used to derive the set of instructions that can be executed to obtain a new equivalent infrastructure. More information: www.rafaelsilva.com

1. Leveraging Semantics to Improve Reproducibility
in Scientific Workflows
Idafen
Santana-­‐Perez1,
Rafael
Ferreira
da
Silva2,
Mats
Rynge2
Ewa
Deelman2,
María
S.
Pérez-­‐Hernández1,
Oscar
Corcho1
1Ontology Engineering Group, Universidad Politécnica de Madrid, Madrid, Spain
2University of Southern California, Information Sciences Institute, Marina Del Rey, CA, USA
The
reproducibility@XSEDE
workshop
July
14th
2014,
Atlanta,
GA

2. 2
Introduction
• Scientific workflows are a useful representation for managing the
execution of large-scale computations
• Facilitates the creation and management of the computation
• Provenance is captured at runtime
• Are data, code, and the workflow description enough to
achieve reproducibility?
• What about the underlying infrastructure?
• Two approaches for conserving the environment of an experiment
• Physical conservation: the real object is conserved
• Logical conservation: the object description is conserved (Semantics)

3. 3
Semantic Modeling
• We propose a logical-oriented approach to conserve computational
environments
• The capabilities of the resources are semantically described
• We propose semantic models for describing the main domains of a
computational infrastructure and how it is related to the workflow:
Overview of the Ontology Network

4. 4
Reproducibility Process
• Experiment Setup
• Montage Workflow (Astronomy)
• Pegasus Workflow Management System
• Workflow execution on FutureGrid
• Semantic Analysis
• Annotations generated using WICUS
• Infrastructure specification translated as
a PRECIP script
Overview of the reproducibility process
for scientific workflows

5. Leveraging Semantics to Improve Reproducibility in Scientific Workflows
Thank
you
Research Object http://pegasus.isi.edu/publications/xsede-reproducibility
PRECIP http://pegasus.isi.edu/precip
WICUS http://purl.org/net/wicus
Pegasus WMS http://pegasus.isi.edu
rafsilva@isi.edu
“Semantic annotations combined with scripting functionality is a strong approach for attaining
reproducibility of computational environments.”