Difference between revisions of "SSW"
From Knoesis wiki
| Line 1: | Line 1: | ||
| − | + | ==Semantic Sensor Web== | |
| − | + | ||
Millions of sensors around the globe currently collect avalanches of data about our environment. The rapid development and deployment of sensor technology involves many different types of sensors, both remote and in situ, with such diverse capabilities as range, modality, and maneuverability. It is possible today to utilize networks with multiple sensors to detect and identify objects of interest up close or from a great distance. The lack of integration and communication between these networks, however, often leaves this avalanche of data stovepiped and intensifies the existing problem of too much data and not enough knowledge.1 With a view to alleviating this glut, we propose that sensor data be annotated with semantic metadata to provide contextual information essential for situational awareness. In particular, we present an approach to annotating sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the W3C and Open Geospatial Consortium (OGC) and extends them with semantic Web technologies to provide enhanced descriptions and access to sensor data. | Millions of sensors around the globe currently collect avalanches of data about our environment. The rapid development and deployment of sensor technology involves many different types of sensors, both remote and in situ, with such diverse capabilities as range, modality, and maneuverability. It is possible today to utilize networks with multiple sensors to detect and identify objects of interest up close or from a great distance. The lack of integration and communication between these networks, however, often leaves this avalanche of data stovepiped and intensifies the existing problem of too much data and not enough knowledge.1 With a view to alleviating this glut, we propose that sensor data be annotated with semantic metadata to provide contextual information essential for situational awareness. In particular, we present an approach to annotating sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the W3C and Open Geospatial Consortium (OGC) and extends them with semantic Web technologies to provide enhanced descriptions and access to sensor data. | ||
| − | == | + | ==Publications== |
| − | + | ||
* Krishnaprasad Thirunarayan, Dharan K. Althuru, Cory A. Henson, and Amit P. Sheth, "[http://knoesis.wright.edu/library/resource.php?id=00474 A Local Qualitative Approach to Referral and Functional Trust]," In: Proceedings of the The 4th Indian International Conference on Artificial Intelligence (IICAI-09), December 2009. | * Krishnaprasad Thirunarayan, Dharan K. Althuru, Cory A. Henson, and Amit P. Sheth, "[http://knoesis.wright.edu/library/resource.php?id=00474 A Local Qualitative Approach to Referral and Functional Trust]," In: Proceedings of the The 4th Indian International Conference on Artificial Intelligence (IICAI-09), December 2009. | ||
* Cory Henson, Holger Neuhaus, Amit Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya, "[http://knoesis.wright.edu/library/resource.php?id=00475 An Ontological Representation of Time Series Observations on the Semantic Sensor Web]," in Proceedings of 1st International Workshop on the Semantic Sensor Web 2009, collocated with the 6th European Semantic Web Conference (ESWC 2009), Herkalion, Greece, June 1, 2009 | * Cory Henson, Holger Neuhaus, Amit Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya, "[http://knoesis.wright.edu/library/resource.php?id=00475 An Ontological Representation of Time Series Observations on the Semantic Sensor Web]," in Proceedings of 1st International Workshop on the Semantic Sensor Web 2009, collocated with the 6th European Semantic Web Conference (ESWC 2009), Herkalion, Greece, June 1, 2009 | ||
Revision as of 16:10, 2 November 2009
Contents
Semantic Sensor Web
Millions of sensors around the globe currently collect avalanches of data about our environment. The rapid development and deployment of sensor technology involves many different types of sensors, both remote and in situ, with such diverse capabilities as range, modality, and maneuverability. It is possible today to utilize networks with multiple sensors to detect and identify objects of interest up close or from a great distance. The lack of integration and communication between these networks, however, often leaves this avalanche of data stovepiped and intensifies the existing problem of too much data and not enough knowledge.1 With a view to alleviating this glut, we propose that sensor data be annotated with semantic metadata to provide contextual information essential for situational awareness. In particular, we present an approach to annotating sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the W3C and Open Geospatial Consortium (OGC) and extends them with semantic Web technologies to provide enhanced descriptions and access to sensor data.
Publications
- Krishnaprasad Thirunarayan, Dharan K. Althuru, Cory A. Henson, and Amit P. Sheth, "A Local Qualitative Approach to Referral and Functional Trust," In: Proceedings of the The 4th Indian International Conference on Artificial Intelligence (IICAI-09), December 2009.
- Cory Henson, Holger Neuhaus, Amit Sheth, Krishnaprasad Thirunarayan, Rajkumar Buyya, "An Ontological Representation of Time Series Observations on the Semantic Sensor Web," in Proceedings of 1st International Workshop on the Semantic Sensor Web 2009, collocated with the 6th European Semantic Web Conference (ESWC 2009), Herkalion, Greece, June 1, 2009
- Cory Henson, Josh Pschorr,Amit Sheth, Krishnaprasad Thirunarayan, "SemSOS: Semantic Sensor Observation Service," in Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore, MD, May 18-22, 2009.
- Krishnaprasad Thirunarayan, Cory Henson,Amit Sheth, "Situation Awareness via Abductive Reasoning for Semantic Sensor Data: A Preliminary Report," in Proceedings of 2009 International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore, MD, May 18-22, 2009.
- Giovani Rimon Abuaitah, Bin Wang, "Trusted query in spatial and temporal correlated wireless sensor networks," cts, pp.98-105, 2009 International Symposium on Collaborative Technologies and Systems, 2009
- Amit Sheth, Cory Henson and Satya S. Sahoo, "Semantic Sensor Web," IEEE Internet Computing.
- Cory Henson, Amit Sheth, Prateek Jain, Josh Pschorr, Terry Rapoch, "Video on the Semantic Sensor Web," W3C Video on the Web Workshop, December 12-13, 2007, San Jose, CA, and Brussels, Belgium.
Ontologies and Datasets
Prototypes, Demos and Tools
- Semantic Sensor Observation Service (MesoWest)
- Semantic Sensor Observation Service (Buckeye Traffic)
- Video on the Semantic Sensor Web
Contact Information: Cory Henson
