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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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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
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Veröffentlicht am 12. Juli 2021
Englisch
236
| Paperback | 978-3-7315-1076-5 |