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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Bibliographic Details
Main Author: Frank, Matthias T.
Format: eBook
Language:English
Published: Karlsruhe KIT Scientific Publishing 2021
Subjects:
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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.
Item Description:Creative Commons (cc), by-sa/4.0, http://creativecommons.org/licenses/by-sa/4.0
Physical Description:1 electronic resource (236 p.)
ISBN:1000128146
9783731510765