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Enabling Semantics within Industry 4.0

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Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10444))

Abstract

Manufacturing faces increasing requirements from customers which causes the need of exploiting emerging technologies and trends for preserving competitive advantages. The apriori announced fourth industrial revolution (also known as Industry 4.0) is represented mainly by an employment of Internet technologies into industry. The essential requirement is the proper understanding of given CPS (one of the key component of Industry 4.0) data models together with a utilization of knowledge coming from various systems across a factory as well as an external data sources. The suitable solution for data integration problem is an employment of Semantic Web Technologies and the model description in ontologies. However, one of the obstacles to the wider use of the Semantic Web technologies including the use in the industrial automation domain is mainly insufficient performance of available triplestores. Thus, on so called Semantic Big Data Historian use case we are proposing the usage of state of the art distributed data storage. We discuss the approach to data storing and describe our proposed hybrid data model which is suitable for representing time series (sensor measurements) with added semantics. Our results demonstrate a possible way to allow higher performance distributed analysis of data from industrial domain.

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Notes

  1. 1.

    A triplestore is a database for the storage and retrieval of triples through semantic queries.

  2. 2.

    http://www.openrdf.org.

  3. 3.

    http://4store.org.

  4. 4.

    https://code.google.com/p/cumulusrdf/.

  5. 5.

    http://hadoop.apache.org.

  6. 6.

    https://jena.apache.org.

  7. 7.

    http://spark.apache.org.

  8. 8.

    http://cassandra.apache.org.

  9. 9.

    ERP—Enterprise resource planning system.

  10. 10.

    YARN—Yet Another Resource Negotiator.

  11. 11.

    https://hive.apache.org.

  12. 12.

    https://hbase.apache.org.

  13. 13.

    http://mahout.apache.org.

  14. 14.

    https://www.knime.org.

  15. 15.

    https://aws.amazon.com/dynamodb/.

  16. 16.

    https://cloud.google.com/bigtable/.

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Acknowledgment

This research has been supported by Rockwell Automation Laboratory for Distributed Intelligent Control (RA-DIC) and by institutional resources for research by the Czech Technical University in Prague, Czech Republic.

Author information

Authors and Affiliations

  1. Czech Institute of Robotics, Informatics, and Cybernetics, Czech Technical University in Prague, Zikova 4, 166 36, Prague, Czech Republic

    Václav Jirkovský

  2. Rockwell Automation R&D Center, Argentinska 1610/4, 170 00, Prague, Czech Republic

    Marek Obitko

Authors
  1. Václav Jirkovský
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  2. Marek Obitko
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Corresponding author

Correspondence to Václav Jirkovský .

Editor information

Editors and Affiliations

  1. Czech Technical University, Prague, Czech Republic

    Vladimír Mařík

  2. German Research Center for AI, Saarbrücken, Germany

    Wolfgang Wahlster

  3. Austrian Institute of Technology, Vienna, Austria

    Thomas Strasser

  4. Czech Technical University, Prague, Czech Republic

    Petr Kadera

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Jirkovský, V., Obitko, M. (2017). Enabling Semantics within Industry 4.0. In: Mařík, V., Wahlster, W., Strasser, T., Kadera, P. (eds) Industrial Applications of Holonic and Multi-Agent Systems. HoloMAS 2017. Lecture Notes in Computer Science(), vol 10444. Springer, Cham. https://doi.org/10.1007/978-3-319-64635-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-64635-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64634-3

  • Online ISBN: 978-3-319-64635-0

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