Publishing Linked Sensor Data
Barnaghi, P, Presser, M and Moessner, K Publishing Linked Sensor Data In: ISWC 2010, 2010-11-07 - 2010-11-11, Shanghai, China.
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This paper describes a linked-data platform to publish sen- sor data and link them to existing resource on the semantic Web. The linked sensor data platform, called Sense2Web supports exible and in- teroperable descriptions and provide association of dierent sensor data ontologies to resources described on the semantic Web and the Web of data. The current advancements in (wireless) sensor networks and being able to manufacture low cost and energy ecient hardware for sensors has lead to much interest in integrating physical world data into theWeb. Wireless sensor networks employ various types of hardware and software components to observe and measure physical phenomena and make the obtained data available through dierent networking services. Applica- tions and users are typically interested in querying various events and requesting measurement and observation data from the physical world. Using a linked data approach enables data consumers to access sensor data and query the data and relations to obtain information and/or inte- grate data from various sources. Global access to sensor data can provide a wide range of applications in dierent domains such as geographical information systems, healthcare, smart homes, and business applications and scenarios. In this paper we focus on publishing linked-data to anno- tate sensors and link them to other existing resources on the Web.
|Item Type:||Conference or Workshop Item (Paper)|
|Additional Information:||Copyright © 2010 for the individual papers by the papers' authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.|
|Divisions:||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research|
|Depositing User:||Symplectic Elements|
|Date Deposited:||09 May 2012 13:27|
|Last Modified:||23 Sep 2013 19:23|
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