Presentation given at the Semantic Technology Conference 2011 (http://semtech2011.semanticweb.com/)

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2. A cross-country flight from New York to Los Angeles on a Boeing 737 plane generates a massive 240 terabytes of data - GigaOmni Media 2

3. In the next few years, sensors networks will produce 10-20 times the amount of generated by social media - GigaOmni Media 3

4. Active Perception over Machine and Citizen Sensing Cory Henson and AmitSheth Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing Wright State University, Dayton, Ohio, USA 4

5. To enable situation awareness on the Web, we must utilize abstractions capable of representing observations and perceptions generated by either people or machines. Web observe perceive “real-world” 5

6. For example, both people and machines are capable of observing qualities, such as redness. observes Observer Quality * Formally described in a sensor/observation ontology 6

7. Sensor and Sensor Network (SSN) Ontology http://www.w3.org/2005/Incubator/ssn/wiki/ 7

8. The ability to perceive is afforded through the use of background knowledge, relating observable qualities to entities in the world. Quality * Formally described in domain ontologies (and knowledge bases) inheres in Entity 8

9. http://linkedsensordata.com 9

11. the ability to minimize explanations based on new information

12. the ability to reason over data on the Web

13. fast (tractable)10

14. minimize explanations tractable degrade gracefully Web reasoning Web Ontology Language (OWL) Parsimonious Covering Theory (PCT) 11

16. The ability to perceive efficiently is afforded through the cyclical exchange of information between observers and perceivers. Observer sends observation sends focus Traditionally called the Perception Cycle (or Active Perception) Perceiver 13

17. Nessier’s Perception Cycle 14

19. Integrated together, we have an general model – capable of abstraction – relating observers, perceivers, and background knowledge. observes Observer Quality sends observation sends focus inheres in perceives Entity Perceiver 16

20. i ntelleg “to perceive” 17

21. Application of Weather Traffic 18 18

22. Traffic Application 19

23. Detection of events, such as blizzards, from weather station observations on LinkedSensorData Weather Application 50% savings in resource requirements needed for detection 20

24. thank you, and please visit us at http://semantic-sensor-web.com Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled Computing Wright State University, Dayton, Ohio, USA 21