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  • Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams

    Matthias T. Frank

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    The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data.

    Umfang: VIII, 216 S.

    Preis: 52.00 €

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    Empfohlene Zitierweise
    Frank, M. 2021. Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000128146
    Frank, M., 2021. Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000128146
    Frank, M. Knowledge-driven Harmonization of Sensor Observations: Exploiting Linked Open Data for Iot Data Streams. KIT Scientific Publishing, 2021. DOI: https://doi.org/10.5445/KSP/1000128146
    Frank, M. (2021). Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000128146
    Frank, Matthias. 2021. Knowledge-driven Harmonization of Sensor Observations: Exploiting Linked Open Data for Iot Data Streams. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000128146




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    Weitere Informationen

    Veröffentlicht am 12. Juli 2021

    Sprache

    Englisch

    Seitenanzahl:

    236

    ISBN
    Paperback 978-3-7315-1076-5

    DOI
    https://doi.org/10.5445/KSP/1000128146