Observatorio de I+D+i UPM

Memorias de investigación
Thesis:
Conservation of computational scientific environments for workflow-based experiments using ontologies
Year:2016
Research Areas
  • Information technology and adata processing,
  • Computer systems
Information
Abstract
Reproducibility of scientific studies and results is a goal that every scientist must pursuit when announcing research outcomes. The rise of computational science, as a way of conducting empirical studies by using mathematical models and simulations, have opened a new range of challenges in this context. The adoption of workflows as a way of detailing the scientific procedure of these experiments, along with the experimental data conservation initiatives that have been undertaken during last decades, have partially eased this problem. However, in order to fully address it, the conservation and reproducibility of the computational equipment related to them must be also considered. The wide range of software and hardware resources required to execute a scientific workflow implies that a comprehensive description detailing what those resources are and how they are arranged is necessary. In this thesis we address the issue of reproducibility of execution environments for scientific workflows, by documenting them in a formalized way, which can be later used to obtain and equivalent one. In order to do so, we propose a set of semantic models for representing and relating the relevant information of those environments, as well as a set of tools that uses these models for generating a description of the infrastructure, and an algorithmic process that consumes these descriptions for deriving a new execution environment specification, which can be enacted into a new equivalent one using virtualization solutions. We apply these three contributions to a set of representative scientific experiments, belonging to different scientific domains, and exposing different software and hardware requirements. The obtained results prove the feasibility of the proposed approach, by successfully reproducing the target experiments under different virtualization environments.
International
Si
Type
Doctoral
Mark Rating
Sobresaliente cum laude
Date
22/01/2016
Participants
  • Director: Maria de los Santos Perez Hernandez (UPM)
  • Autor: Idafen Santana Perez (UPM)
  • Director: Oscar Corcho Garcia (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)