Skip to Main content Skip to Navigation
Conference papers

The Semantic Sensor Network Ontology, Revamped

Abstract : The Semantic Sensor Network Ontology, popularly knownasSSN, was developed by an Incubator Group of the World Wide WebConsortium (W3C) over 2009 to 2011. Subsequently, the W3C and theOpen Geospatial Consortium (OGC) joined forces to update the SSNas informed by experience, to harmonize it with OGC’s O&M, and topublish a new version to be endorsed as both a W3C Recommendationand an OGC standard in late 2017. The major contribution of the newSSN is a modular structure designed to be more convenient for ontologyengineers and data custodians. It also slightly extends the coverage ofthe previous SSN with new terms for sampling and actuation. SSN re-tains the ability to comprehensively represent:sensorsin terms of whatthey can sense, and what and how they do sense;observationsin termsof what they measure and what values they find;systems(or networks)of sensors in terms of sensor components and how they are deployed;andreal-world objects(calledfeatures of interest, OGC-style) in terms oftheir physical properties, what can sense them, and what observations ofthem have been made. A few little-used SSN terms have been deprecated,and several others have been renamed. For a comprehensive descriptionof new SSN the reader is referred to the specification [10]. A full descrip-tion of the scope, design rationale and additions, with examples of itsapplication are presented in [11].
Document type :
Conference papers
Complete list of metadatas

https://hal-emse.ccsd.cnrs.fr/emse-02430047
Contributor : Florent Breuil <>
Submitted on : Tuesday, January 7, 2020 - 9:48:19 AM
Last modification on : Wednesday, June 24, 2020 - 4:19:16 PM

Identifiers

  • HAL Id : emse-02430047, version 1

Citation

Kerry Taylor, Armin Haller, Maxime Lefrançois, Simon Cox, Krzysztof Janowicz, et al.. The Semantic Sensor Network Ontology, Revamped. 18th International Semantic Web Conference, Oct 2019, Auckland, New Zealand. ⟨emse-02430047⟩

Share

Metrics

Record views

44