Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications

M.R. Huq, Andreas Wombacher, Peter M.G. Apers

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

One of the major requirements for e-science applications handling sensor data, is reproducibility of results. Several optimization and scalability problems exist where the reproducibility of results remains guaranteed. Firstly, various data streams need to be coordinated to optimize the accuracy and processing of the results. Secondly, because of the high volume of streaming data and a series of processing steps to be performed on that data, demand for disk space may grow unacceptably high. Lastly, reproducibility in a decentralized scenario may be difficult to achieve because of data replication. This paper introduces and addresses these challenges which arise for optimizing the process of achieving reproducibility of results.
Original languageUndefined
Title of host publicationProceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages75-78
Number of pages4
ISBN (Print)978-1-4503-0385-9
DOIs
Publication statusPublished - 30 Oct 2010

Publication series

Name
PublisherACM

Keywords

  • METIS-275813
  • IR-75365
  • Optimization
  • CR-E
  • E-science applications
  • Sensor data
  • EWI-19184
  • Reproducibility

Cite this

Huq, M. R., Wombacher, A., & Apers, P. M. G. (2010). Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications. In Proceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010 (pp. 75-78). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/1871902.1871916
Huq, M.R. ; Wombacher, Andreas ; Apers, Peter M.G. / Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications. Proceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010. New York : Association for Computing Machinery (ACM), 2010. pp. 75-78
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abstract = "One of the major requirements for e-science applications handling sensor data, is reproducibility of results. Several optimization and scalability problems exist where the reproducibility of results remains guaranteed. Firstly, various data streams need to be coordinated to optimize the accuracy and processing of the results. Secondly, because of the high volume of streaming data and a series of processing steps to be performed on that data, demand for disk space may grow unacceptably high. Lastly, reproducibility in a decentralized scenario may be difficult to achieve because of data replication. This paper introduces and addresses these challenges which arise for optimizing the process of achieving reproducibility of results.",
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Huq, MR, Wombacher, A & Apers, PMG 2010, Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications. in Proceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010. Association for Computing Machinery (ACM), New York, pp. 75-78. https://doi.org/10.1145/1871902.1871916

Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications. / Huq, M.R.; Wombacher, Andreas; Apers, Peter M.G.

Proceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010. New York : Association for Computing Machinery (ACM), 2010. p. 75-78.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - One of the major requirements for e-science applications handling sensor data, is reproducibility of results. Several optimization and scalability problems exist where the reproducibility of results remains guaranteed. Firstly, various data streams need to be coordinated to optimize the accuracy and processing of the results. Secondly, because of the high volume of streaming data and a series of processing steps to be performed on that data, demand for disk space may grow unacceptably high. Lastly, reproducibility in a decentralized scenario may be difficult to achieve because of data replication. This paper introduces and addresses these challenges which arise for optimizing the process of achieving reproducibility of results.

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Huq MR, Wombacher A, Apers PMG. Identifying the Challenges for Optimizing the Process to Achieve Reproducible Results in E-science Applications. In Proceedings of the 3rd Workshop on Ph.D. Students in Information and Knowledge Management, PIKM 2010. New York: Association for Computing Machinery (ACM). 2010. p. 75-78 https://doi.org/10.1145/1871902.1871916