Druck auf Anfrage Neuware - Printed after ordering - 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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Bibliographic Details

Title: Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
Publisher: Karlsruher Institut F�r Technologie
Publication Date: 2021
Language: English
ISBN 10: 3731510766
ISBN 13: 9783731510765
Binding: Taschenbuch
Condition: Neu
Dimensions: 240 millimeters width by 170 millimeters height by 15 millimeters depth
Weight: 457 grams

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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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