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Using DevOps Principles to Continuously Monitor RDF Data Quality

Published:12 September 2016Publication History

ABSTRACT

One approach to continuously achieve a certain data quality level is to use an integration pipeline that continuously checks and monitors the quality of a data set according to defined metrics. This approach is inspired by Continuous Integration pipelines, that have been introduced in the area of software development and DevOps to perform continuous source code checks. By investigating in possible tools to use and discussing the specific requirements for RDF data sets, an integration pipeline is derived that joins current approaches of the areas of software-development and semantic-web as well as reuses existing tools. As these tools have not been built explicitly for CI usage, we evaluate their usability and propose possible workarounds and improvements. Furthermore, a real-world usage scenario is discussed, outlining the benefit of the usage of such a pipeline.

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  • Published in

    cover image ACM Other conferences
    SEMANTiCS 2016: Proceedings of the 12th International Conference on Semantic Systems
    September 2016
    207 pages
    ISBN:9781450347525
    DOI:10.1145/2993318

    Copyright © 2016 Owner/Author

    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 12 September 2016

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    • Refereed limited

    Acceptance Rates

    SEMANTiCS 2016 Paper Acceptance Rate18of85submissions,21%Overall Acceptance Rate40of182submissions,22%

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