Title: Managing data provenance for bioinformatics workflows using AProvBio

Authors: Rodrigo Almeida; Waldeyr Mendes Cordeiro Da Silva; Klayton Castro; Aletéia Patricia Favacho De Araújo; Maria Emília Machado Telles Walter; Sergio Lifschitz; Maristela Holanda

Addresses: Department of Computer Science, University of Brasília, Brasília, 70910-900, Brazil ' Federal Institute of Goiás IFG, Formosa, Brazil ' Department of Computer Science, University of Brasília, Brasília, 70910-900, Brazil ' Department of Computer Science, University of Brasília, Brasília, 70910-900, Brazil ' Department of Computer Science, University of Brasília, Brasília, 70910-900, Brazil ' Pontifical Catholic University of Rio de Janeiro, Department of Informatics, Rio de Janeiro, Brazil ' Department of Computer Science, University of Brasília, Brasília, 70910-900, Brazil

Abstract: Scientific experiments in bioinformatics are often executed as computational workflows. Data provenance involves documenting the history, and the paths of the input data, from the beginning to the end of an experiment. AProvBio is an architecture that enables the capture and storage of data provenance for bioinformatics workflows using the PROV-DM standard model. AProvBio works with three types of data provenance: prospect, retrospect, and the user-defined type. Given how graphs conveniently express PROV-DM, we have designed and implemented a simulator for storing the data provenance in a graph database system. This paper presents details and implementation aspects of our architecture, and an evaluation of AProvBio through the carrying out of two real case scenarios.

Keywords: bioinformatics; scientific workflows; data provenance; PROV-DM; graph database.

DOI: 10.1504/IJCBDD.2019.099761

International Journal of Computational Biology and Drug Design, 2019 Vol.12 No.2, pp.153 - 170

Received: 27 Feb 2018
Accepted: 27 Jun 2018
Published online: 21 May 2019 *

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