Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams
Material type: ArticleLanguage: English Publication details: Karlsruhe KIT Scientific Publishing 2021Description: 1 electronic resource (236 p.)ISBN:- KSP/1000128146
- 9783731510765
Item type | Current library | Collection | Shelving location | Call number | Status | Notes | Date due | Barcode |
---|---|---|---|---|---|---|---|---|
Electronic edition | Bucheon University Library | Computers | OAPEN | 004 K62 | Not for loan | Смотреть (pdf) | 1010554 |
Open Access star Unrestricted online access
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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