Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
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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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Karlsruhe
KIT Scientific Publishing
2021
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009871129206719 |
| Sumario: | 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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| Descripción Física: | 1 electronic resource (236 p.) |
