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

By: Material type: TextTextPublisher: Karlsruhe KIT Scientific Publishing 2021Description: 1 online resource (236 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
Subject(s): Online resources: Summary: 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.
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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.

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