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

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

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

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

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

* Formally described in domain ontologies (and knowledge bases) 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

http://linkedsensordata.com

With the help of sophisticated inference, both people and machines are also capable of perceiving entities, such as apples. perceives Perceiver Entity the ability to degrade gracefully with incomplete information the ability to minimize explanations based on new information the ability to reason over data on the Web fast (tractable)

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

Conversion of PCT to OWL 2 (EL) Parsimonious Covering Theory (Abductive Logic) * OWL-DL Cory Henson, Krishnaprasad Thirunarayan, Amit Sheth, Pascal Hitzler. Representation of Parsimonious Covering Theory in OWL-DL. In: Proceedings of the 8th International Workshop on OWL: Experiences and Directions (OWLED 2011), San Francisco, CA, United States, June 5-6, 2011.

Traditionally called the Perception Cycle (or Active Perception) 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

Nessier’s Perception Cycle

Cognitive Theory of Perception (timeline) 1970’s - Perception is an active, cyclical process of exploration and interpretation - Nessier’s Perception Cycle 1980’s - The perception cycle is driven by background knowledge in order to generate and test hypotheses. - Richard Gregory (optical illusions) 1990’s - In order to effectively test hypotheses, some observations are more informative than others. - Norwich’s Entropy Theory of Perception

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 Perceiver Entity

i ntelleg “to perceive”

Application of Traffic Weather

Traffic Application

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

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