Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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A cross-country flight from New York to Los Angeles on a Boeing 737 plane generates a massive 240 terabytes of data
- GigaOmni Media
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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In the next few years, sensors networks will produce10-20 times the amount of generated by social media - GigaOmni Media
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Active Perception over Machine and Citizen Sensing
Cory Henson and Amit Sheth
Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled ComputingWright State University, Dayton, Ohio, USA
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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For example, both people and machines are capable of observing qualities, such as redness.
* Formally described in a sensor/observation ontology
observesObserver Quality
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Sensor and Sensor Network (SSN) Ontology
http://www.w3.org/2005/Incubator/ssn/wiki/
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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The ability to perceive is afforded through the use of background knowledge, relating observable qualities to entities in the world.
* Formally described in domain ontologies
(and knowledge bases)
inheres in
Quality
Entity
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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http://linkedsensordata.com
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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With the help of sophisticated inference, both people and machines are also capable of perceiving entities, such as apples.
• 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)
perceivesEntityPerceiver
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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minimizeexplanations
degrade gracefully
tractable
Parsimonious Covering Theory (PCT)
Web OntologyLanguage (OWL)
Web reasoning
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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OWL-DL
Conversion of PCT to OWL 2 (EL)
ParsimoniousCovering Theory(Abductive Logic)
* 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.
*
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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The ability to perceive efficiently is afforded through the cyclical exchange of information between observers and perceivers.
Traditionally called the Perception Cycle
(or Active Perception)
sendsfocus
sends observation
Observer
Perceiver
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Nessier’s Perception Cycle
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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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
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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observes
inheres in
Integrated together, we have an general model – capable of abstraction – relating observers, perceivers, and background knowledge.
perceives
sendsfocus
sends observation
Observer Quality
EntityPerceiver
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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ntellegi “to perceive”
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Application of
Traffic Weather
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Traffic Application
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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50% savings in resource requirements needed for detection
Weather ApplicationDetection of events, such as blizzards, from weather station observations on LinkedSensorData
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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thank you, and please visit us at
http://semantic-sensor-web.com
Kno.e.sis – Ohio Center of Excellence in Knowledge-enabled ComputingWright State University, Dayton, Ohio, USA
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