Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams - Matthias T. Frank
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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 lar ... Full description
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Description
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.
More Information
| Author | Matthias T. Frank |
|---|---|
| Publisher | Karlsruher Institut für Technologie |
| Release year | 2021 |
| Cover type | Softcover |
| EAN | 9783731510765 |