Social Semantic (Sensor) Web


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Lecture given to students @ Tralee Institute of Technology 13 Feb 2012

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Social Semantic (Sensor) Web

  1. 1. Social Semantic (Sensor) Web David Crowley
  2. 2. About me!• Mechanical & Electronic Engineering (Cert)• Mathematics & Information Technology (BA)• Interactive Media (MSc) • Google Android Project • Implementing Sensor controlled applications
  3. 3. Currently• PhD Candidate/Researcher• NUI Galway – Electrical & Electronic Engineering • Bio-Electronics (Sensors) – DERI – Digital Enterprise Research Institute • USS – Social Software Unit
  4. 4. Social Web
  5. 5. The Social Web is exploding!image from
  6. 6. Sites go up... image from
  7. 7. ...and sites come down image from
  8. 8. Semantic Web
  9. 9. The Web = The Internet + links + documents or The Web = The Internet + http + html Image from -
  10. 10. Current Web• HTTP protocol is used for accessing and exchanging web data• HTML language is used for creating web pages• Machines can read the language• But they don’t “understand” the content
  11. 11. People and the Web• But people aren’t interested in documents!• People are interested in things (objects)• People can extract knowledge from web pages• Machines can’t!• So we need a way to help machines help us!
  12. 12. The Web as we know it…is not the Web thatTim Berners Lee wanted
  13. 13. Social Machines“Computers can help if we usethem to create abstract socialmachines on the Web : processesin which the people do the creativework and the machine does theadministration…” Berners-Lee, Weaving the Web, 1999
  14. 14. Semantic Web• The idea of the Semantic Web aims at converting the current web of unstructured documents into a web of data• Tim Berners Lee defines the Semantic Web as "a web of data that can be processed directly and indirectly by machines."
  15. 15. Technologies - RDF• RDF – Resource Description Language – Triples – Subject, Predicate, Object,• “Stefan works at DERI” – Stefan – Subject – Works at – Predicate – DERI - Object
  16. 16. URI• But Stefan can be described by a URI• And DERI can be described by it’s homepage• So we can rewrite it in English as works at
  17. 17. SPARQL• SPARQL - SPARQL Protocol and RDF Query Language• Think of it as SQL for RDF• But because RDF data is more “expressive” – SPARQL allows for more complicated queries• Give me all artists signed to Elektra Records that are from the genre Rock
  18. 18. Ontologies• Ontology define the terms used to describe and represent an area of interest – Concepts (classes) – Relationships (subclasses) – Properties (attributes)• FOAF– Friend of a Friend• SIOC – Semantically Interlinked Online Communities• DC – Dublin Core• SSN – Semantic Sensor Network
  19. 19. Ontologies• Ontologies are used to describe certain areas of interest• For example FOAF – describes relationships between people• SIOC – Describes groups and creates interoperability between blogs/forums/social networks• SSN ontology describes sensor stations/sensor nodes and their sensing capabilities
  20. 20. Linked Data• Linked Data is about using the Web to connect related data that wasnt previously linked• Without Linked Data there is no Web of Data• For example - DBPedia – is a Linked Data version of Wikipedia which recreates the data on Wikipedia and linked it to other data sources (Geonames)
  21. 21. Is publishing data enough?
  22. 22. The LOD cloud 2007 2008
  23. 23. The LOD cloud 2008 2009
  24. 24. “Linking Open Data cloud diagram, by Richard Cyganiak andAnja Jentzsch.”
  25. 25. Predicting the Future
  26. 26. Social Semantic Web
  27. 27. Social Semantic (Sensor) Web
  28. 28. “In the next century, planet earth will don anelectronic skin. It will use the Internet as a scaffold tosupport and transmit its sensations.”– Neil Gross, Bloomberg Business Week, 1999
  29. 29. And this skin containsSensors
  30. 30. Sensors, Sensors everywhere• Embedded in our homes• Cars• Work places• Weather stations• Laptops• Tablets• Smartphones• People!
  31. 31. Sensor Networks• Generally – Hard to build, – Hard to maintain – Distance issues – Network issues – Data issues
  32. 32. But we have lots of these…
  33. 33. And these..
  34. 34. Citizen Sensing• Networks of Humans with Sensors• Humans process data (a positive and a negative)• Sensor nodes generally do not process data• But using mobile devices’ sensors we can add an additional layer to human in the loop sensing
  35. 35. Semantic Sensing• Describing Sensors with Semantic Technologies• SSN Ontology and adding reasoning on top of that• For example – if light temperature is reading low light levels and the humidity sensor is reading high humidity then rain is likely!
  36. 36. Annotating Sensor data to Social web posts!• Define a standard way for attaching mobile sensor data to social web content• Twitter Annotations• Extend SIOC ontology and align with SSN Ontology
  37. 37. Why?• Natural Disaster Management• Traffic Reporting Applications• All kinds of crowdsourcing applications• Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples - http://www.ij- t
  38. 38. References• Hand drawn slide used with permission of John Breslin - semantic-web-1328494• Other slides from John Breslin’s slideshare also used (LOD cloud images)• BBC Presentation on Linked Data - data/s5.html• BBC Blog Post about using Sem Web Technologies for World Cup 2010 - _world_cup_2010_dynamic_sem.html