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Social and Behavioral Sciences Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Social and Behavioral Sciences
The Ssn Ontology Of The W3c Semantic Sensor Network Incubator Group, Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Andrew Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit P. Sheth, Kerry Taylor
The Ssn Ontology Of The W3c Semantic Sensor Network Incubator Group, Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Andrew Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit P. Sheth, Kerry Taylor
Kno.e.sis Publications
The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Linked Sensor Data, Harshal Kamlesh Patni, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
A number of government, corporate, and academic organizations are collecting enormous amounts of data provided by environmental sensors. However, this data is too often locked within organizations and underutilized by the greater community. In this paper, we present a framework to make this sensor data openly accessible by publishing it on the Linked Open Data (LOD) Cloud. This is accomplished by converting raw sensor observations to RDF and linking with other datasets on LOD. With such a framework, organizations can make large amounts of sensor data openly accessible, thus allowing greater opportunity for utilization and analysis.
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Sensor Discovery On Linked Data, Josh Pschorr, Cory Andrew Henson, Harshal Kamlesh Patni, Amit P. Sheth
Kno.e.sis Publications
There has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web is a non-trivial challenge. In this paper, we present an approach to discovering sensors through a standard service interface over Linked Data. This is accomplished with a semantic sensor network middleware that includes a sensor registry on Linked Data and a sensor discovery service that extends the OGC Sensor Web Enablement. With this approach, we are able to access and discover sensors that are positioned near named-locations …
Provenance Aware Linked Sensor Data, Harshal Kamlesh Patni, Satya S. Sahoo, Cory Andrew Henson, Amit P. Sheth
Provenance Aware Linked Sensor Data, Harshal Kamlesh Patni, Satya S. Sahoo, Cory Andrew Henson, Amit P. Sheth
Kno.e.sis Publications
Provenance, from the French word “provenir”, describes the lineage or history of a data entity. Provenance is critical information in the sensors domain to identify a sensor and analyze the observation data over time and geographical space. In this paper, we present a framework to model and query the provenance information associated with the sensor data exposed as part of the Web of Data using the Linked Open Data conventions. This is accomplished by developing an ontology-driven provenance management infrastructure that includes a representation model and query infrastructure. This provenance infrastructure, called Sensor Provenance Management System (PMS), is …
An Ontological Representation Of Time Series Observations On The Semantic Sensor Web, Cory Andrew Henson, Holger Neuhaus, Amit P. Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya
An Ontological Representation Of Time Series Observations On The Semantic Sensor Web, Cory Andrew Henson, Holger Neuhaus, Amit P. Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya
Kno.e.sis Publications
Time series observations are a common method of collecting sensor data. The Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) provides a standard representation for time series observations within the Observations and Measurements language, and therefore is in heavy use on the Sensor Web. By providing a common model, Observations and Measurements (O&M) facilitates syntax-level integration, but lacks the ability to facilitate semantic-level integration. This inability can cause problems with interoperability between disparate sensor networks that may have subtle variations in their sensing methods. An ontological representation of time series observations could provide a more expressive model and resolve problems …