Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams

• Autore: Frank Matthias T
• Pubblicazione: Karlsruhe, : KIT Scientific Publishing, 2021
• Descrizione fisica: 1 online resource (236 p.)
• Soggetto topico: Economics
• Soggetto non controllato: corporate knowledge graph; data stream processing; Datenstromverarbeitung; Internet der Dinge; Internet of Things; Linked Open Data; sensor data harmonization; Sensordatenharmonisierung; Wissensgraph
• Sommario/riassunto: 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.
• Altri titoli varianti: Knowledge-Driven Harmonization of Sensor Observations
• Titolo autorizzato: Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
• ISBN: 1000128146
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910493731503321
• Lo trovi qui: Univ. Federico II