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

1. Social Semantic (Sensor) Web
David Crowley
david.crowley@deri.org
david.crowley@nuigalway.ie

2. About me!
• Mechanical & Electronic Engineering (Cert)
• Mathematics & Information Technology (BA)
• Interactive Media (MSc)
• Google Android Project
• Implementing Sensor controlled applications

3. Currently
• PhD Candidate/Researcher
• NUI Galway
– Electrical & Electronic Engineering
• Bio-Electronics (Sensors)
– DERI – Digital Enterprise Research Institute
• USS – Social Software Unit

4. Social Web

6. The Social Web
is exploding!
image from tinyurl.com/nuketest

7. Sites go up...
image from tinyurl.com/rocket15

8. ...and sites come down
image from tinyurl.com/elhell

14. Semantic Web

15. The Web = The Internet + links + documents
or
The Web = The Internet + http + html
Image from - http://www.bbc.co.uk/blogs/radiolabs/s5/linked-data/s5.html

16. 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

17. 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!

18. The Web as we know
it…is not the Web that
Tim Berners Lee wanted

19. Social Machines
“Computers can help if we use
them to create abstract social
machines on the Web : processes
in which the people do the creative
work and the machine does the
administration…”
Berners-Lee, Weaving the Web, 1999

20. 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."

21. Technologies - RDF
• RDF – Resource Description Language
– Triples
– Subject, Predicate, Object,
• “Stefan works at DERI”
– Stefan – Subject
– Works at – Predicate
– DERI - Object

22. URI
• But Stefan can be described by a URI
http://www.deri.ie/fileadmin/scripts/foaf.php?
id=12
• And DERI can be described by it’s homepage
http://www.deri.ie
• So we can rewrite it in English as
http://www.deri.ie/fileadmin/scripts/foaf.php?
id=12 works at http://www.deri.org/

23. 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

24. 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

25. 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

27. Linked Data
• Linked Data is about using the Web to
connect related data that wasn't 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)

28. Is publishing data enough?
http://lab.linkeddata.deri.ie/2010/star-scheme-by-example/

29. The LOD cloud
2007
2008

30. The LOD cloud
2008
2009

31. “Linking Open Data cloud diagram, by Richard Cyganiak and
Anja Jentzsch. http://lod-cloud.net/”

32. Predicting the Future

33. Social Semantic Web

42. Social Semantic (Sensor) Web

43. “In the next century, planet earth will don an
electronic skin. It will use the Internet as a scaffold to
support and transmit its sensations.”
– Neil Gross, Bloomberg Business Week, 1999

44. And this skin contains
Sensors

45. Sensors, Sensors everywhere
• Embedded in our homes
• Cars
• Work places
• Weather stations
• Laptops
• Tablets
• Smartphones
• People!

46. Sensor Networks
• Generally
– Hard to build,
– Hard to maintain
– Distance issues
– Network issues
– Data issues

47. But we have lots of these…

48. And these..

49. 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

50. 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!

51. 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

52. 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-
healthgeographics.com/content/10/1/67/abstrac
t

53. References
• Hand drawn slide used with permission of John Breslin
- http://www.slideshare.net/Cloud/the-social-
semantic-web-1328494
• Other slides from John Breslin’s slideshare also used
(LOD cloud images)
• BBC Presentation on Linked Data -
http://www.bbc.co.uk/blogs/radiolabs/s5/linked-
data/s5.html
• BBC Blog Post about using Sem Web Technologies for
World Cup 2010 -
http://www.bbc.co.uk/blogs/bbcinternet/2010/07/bbc
_world_cup_2010_dynamic_sem.html