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Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
Matthias T. Frank
2021
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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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Keywords
- corporate knowledge graph
- data stream processing
- Datenstromverarbeitung
- Economics
- Economics, finance, business & management
- Internet der Dinge
- Internet of Things
- Linked Open Data
- sensor data harmonization
- Sensordatenharmonisierung
- thema EDItEUR::K Economics, Finance, Business and Management::KC Economics
- Wissensgraph
Links
DOI: 10.5445/KSP/1000128146Editions