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

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

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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 harmo...

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Bibliographic Details
Main Author: Frank, Matthias T. (auth)
Format: Electronic Book Chapter
Language:English
Published: Karlsruhe KIT Scientific Publishing 2021
Subjects:
Economics
Internet der Dinge
Linked Open Data
Datenstromverarbeitung
Wissensgraph
Sensordatenharmonisierung
Internet of Things
data stream processing
corporate knowledge graph
sensor data harmonization
Online Access:DOAB: download the publication
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Description
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.
Physical Description:1 electronic resource (236 p.)
ISBN:KSP/1000128146
9783731510765
Access:Open Access

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