Ontology of a temperature sensor

Ontology of a temperature sensor

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  Data Representation Using Ontologies 1
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  Contents • Introduction • Dataspecific issues in IoT • Approaches used • Ontology • Demo 2
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  Introduction • IoT makesour life comfortable – Desktop (static) to Ubiquitous (mobile) computing • IoT devices are mostly sensors – Motion, Pressure, Temperature, Light sensors – Cameras, Microphones, GPS enabled devices • Nature of data – Streaming data: audio/video recording – Event Based: Temperature reading, RFID tag read, light curtain interrupt 3
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  Issues? • Sensors areresource constrained devices – Battery, processor and storage • Date generation is continuous – Leads to BIG DATA PROBLEM • Generated data meaningful to limited users only – Only sensor itself and its deployer knows • Human understandable and Machine understandable data – Celsius vs. kelvin 4
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  Will consider only •Sensors are resource constrained devices – Battery, processor and storage • Date generation is continuous – Leads to BIG DATA PROBLEM • Generated data meaningful to limited users only – Only sensor itself and its deployer knows • Human understandable and Machine understandable data 5
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  Approaches used • Meaninglessdata  add annotations (Metadata) • Unstructured data suitable for human consumption but not machine understandable use standardized syntax (XML, RDF) • Interoperability of data Use ontologies 6
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  Will use • Meaninglessdata  add annotations (Metadata) • Unstructured data suitable for human consumption but not machine understandable use standardized syntax (XML, RDF) • Interoperability of data Use ontologies 7
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  Ontology • A datamodel that represents knowledge as a set of concepts within a domain and the relationship between these concepts • It is be used to support reasoning about concepts. 8
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  Ontology 9
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  Basic Blocks ofOntology • Classes • Instances • Relations – A knows B • TRIPLES 10
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  Example: A simpleontology of CS Department in US 11
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  Why we useOntologies • To share common understanding of the structure of information among people or machines • To enable reuse of domain knowledge • Ontologies allow us to infer extra knowledge from basic facts encoded 12
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  Represent this inOntology 13
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  Possible Ontology Classes Individuals Subclasses Relationship 14
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  Relationship 15
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  Expanded view ofsome individuals of Place(class) Mumbai 16
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  Internal details associatedwith each individual 17
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  Tools used andDemo • Tools used: Protégé, Jena Framework • Demo: – Create an individual of ontology – Display created individual in Protégé – Perform queries on Ontology 18
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  References • From sensordata to triples: Information flow in semantic sensor networks • Slides from www.slideshare.net 19
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  Annexure 1 • Eachresource(thing) is represented on web • Organizations can refer to each others business definitions • Models can be modularized and reused • Third parties can understand the information 20