9783731510765.pdf
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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KIT Scientific Publishing
2021
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oapen-20.500.12657-504492021-08-17T02:48:59Z Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams Frank, Matthias T. Internet der Dinge Linked Open Data Datenstromverarbeitung Wissensgraph Sensordatenharmonisierung Internet of Things data stream processing corporate knowledge graph sensor data harmonization bic Book Industry Communication::K Economics, finance, business & management::KC Economics 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. 2021-08-16T09:31:21Z 2021-08-16T09:31:21Z 2021 book ONIX_20210816_9783731510765_10 9783731510765 https://library.oapen.org/handle/20.500.12657/50449 eng application/pdf n/a 9783731510765.pdf KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000128146 10.5445/KSP/1000128146 44e29711-8d53-496b-85cc-3d10c9469be9 9783731510765 KIT Scientific Publishing 236 Karlsruhe open access |
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English |
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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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9783731510765.pdf |
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9783731510765.pdf |
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9783731510765.pdf |
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9783731510765.pdf |
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9783731510765.pdf |
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9783731510765.pdf |
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9783731510765.pdf |
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KIT Scientific Publishing |
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2021 |
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1771297389857996800 |
