Achieving Reproducibility Incorporating Service Versioning into Provenance Model

Authors

  • Dayang Hanani Abang Ibrahim Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300 Sarawak, Malaysia.
  • Nadianatra Musa Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300 Sarawak, Malaysia.
  • Chiew Kang Leng Department of Computational Science and Mathematics, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300 Sarawak, Malaysia.
  • Jane Labadin Department of Computational Science and Mathematics, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300 Sarawak, Malaysia.
  • Johari Abdullah Department of Computer System and Communication Technology, Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300 Sarawak, Malaysia.
  • Sarina Sulaiman UTM Big Data Centre, Universiti Teknologi Malaysia, Skudai, 81310 Johor, Malaysia.

Keywords:

Reproducibility, Provenance, Provenance Model, Service Versioning, Web Services Architecture,

Abstract

Reproducibility has long been a cornerstone of science. Underpinning reproducibility is provenance, which has the potential to provide scientists with a complete understanding of data generated in e-experiments, including the services that were produced and consumed. This paper explores the issues of service versioning in provenance to achieve reproducibility. Current provenance model does not directly support service versioning. Therefore, this paper introduces an enhancement of a provenance model to incorporate service versioning mechanism that provides a way to access multiple versions of the same service so that researcher can compare one version to another, and understand their effects on processing data. The enhanced provenance model is able to track the changes of the same service (versions of the same service) over time and correlates versioned services with the results they generate.

References

G. Pizzi, A. Cepellotti, R. Sabatini, N. Marzari, and B. Kozinsky, “AiiDA: automated interactive infrastructure and database for computational science,” Comput. Mater. Sci., vol. 111, pp. 218–230, Jan. 2016.

R. S. Barga, Y. L. Simmhan, E. Chinthaka, S. S. Sahoo, J. Jackson, and N. Araujo, “Provenance for Scientific Workflows Towards Reproducible Research.,” IEEE Data Eng Bull, vol. 33, no. 3, pp. 50– 58, 2010.

S. Fomel and G. Hennenfent, “Reproducible Computational Experiments using Scons,” in 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP ’07, 2007, vol. 4, p. IV-1257-IV-1260.

S. Woodman, H. Hiden, P. Watson, and P. Missier, “Achieving Reproducibility by Combining Provenance with Service and Workflow Versioning,” in Proceedings of the 6th Workshop on Workflows in Support of Large-scale Science, New York, NY, USA, 2011, pp. 127– 136.

D. A. Kolb, Experiential Learning: Experience as the Source of Learning and Development. FT Press, 2014.

G. C. Bowker, “The new knowledge economy and science and technology policy,” in Science and Technology Policy - Volume I, vol. 1, 2004.

Y. L. Simmhan, B. Plale, and D. Gannon, “A Survey of Data Provenance in e-Science,” SIGMOD Rec, vol. 34, no. 3, pp. 31–36, Sep. 2005.

S. Sahoo and A. Sheth, “Provenir Ontology: Towards a Framework for eScience Provenance Management,” Knoesis Publ., Oct. 2009.

L. Moreau et al., “The Open Provenance Model core specification (v1.1),” Future Gener. Comput. Syst., vol. 27, no. 6, pp. 743–756, Jun. 2011.

P. Missier, K. Belhajjame, and J. Cheney, “The W3C PROV Family of Specifications for Modelling Provenance Metadata,” in Proceedings of the 16th International Conference on Extending Database Technology, New York, NY, USA, 2013, pp. 773–776.

“The ProvONE Data Model for Scientific Workflow Provenance.” [Online]. Available: http://vcvcomputing.com/provone/provone.html. [Accessed: 29-Apr-2017].

A. Prabhune, A. Zweig, R. Stotzka, M. Gertz, and J. Hesser, “Prov2ONE: An Algorithm for Automatically Constructing ProvONE Provenance Graphs,” in Provenance and Annotation of Data and Processes, 2016, pp. 204–208.

“The UDDI XML.” [Online]. Available: http://uddi.xml.org/uddi-org. [Accessed: 29-Apr-2017].

“XML WSDL.” [Online]. Available: https://www.w3schools.com/xml/xml_wsdl.asp. [Accessed: 29-Apr-2017].

R. Fang et al., “A Version-aware Approach for Web Service Directory,” in IEEE International Conference on Web Services (ICWS 2007), 2007, pp. 406–413.

D. Frank, L. Lam, L. Fong, R. Fang, and M. Khangaonkar, “Using an Interface Proxy to Host Versioned Web Services,” in 2008 IEEE International Conference on Services Computing, 2008, vol. 2, pp. 325–332.

K. Wolstencroft et al., “The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud,” Nucleic Acids Res., vol. 41, no. W1, pp. W557–W561, Jul. 2013.

D. H. AbangIbrahim, “The Exploitation of Provenance and Versioning in the Reproduction of e-Experiments,” PhD Thesis, University of Newcastle.United Kingdom, UK, 2016.

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Published

2017-09-15

How to Cite

Abang Ibrahim, D. H., Musa, N., Leng, C. K., Labadin, J., Abdullah, J., & Sulaiman, S. (2017). Achieving Reproducibility Incorporating Service Versioning into Provenance Model. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-10), 131–138. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2716

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