The document discusses explanation in the semantic web and provides examples of linking data about Tim Berners-Lee. It demonstrates how semantic web technologies like RDF can represent relationships between data from different sources to support reasoning and answering queries. Linked data about Tim Berners-Lee's place of birth, occupation, and their relationships is represented in RDF graphs and used to answer the question "Scientists born in United Kingdom?". The example illustrates how the semantic web allows connecting related information distributed across different sources on the web.

1. Explanation for the Semantic Web
Rakebul Hasan

2. Explanation in the Semantic Web
What’s been done (existing work)
What’s ahead (perspective)
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3. What is explanation and why do we need it?
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4. Tim Berners-Lee was born in London
http://www.academiawiki.com/
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5. Tim Berners-Lee was born in London
http://www.academiawiki.com/
London is in England
http://www.geolocationwiki.com/
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6. Tim Berners-Lee was born in London
http://www.academiawiki.com/
London is in England
http://www.geolocationwiki.com/
Computer Scientists are Scientists
http://www.vocabularywiki.com/
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7. Tim Berners-Lee was born in London
http://www.academiawiki.com/
London is in England
http://www.geolocationwiki.com/
Computer Scientists are Scientists
http://www.vocabularywiki.com/
Tim Berners-Lee is a Computer Scientist
http://www.academiawiki.com/
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8. Tim Berners-Lee was born in London
http://www.academiawiki.com/
London is in England
http://www.geolocationwiki.com/
Computer Scientists are Scientists
http://www.vocabularywiki.com/
Tim Berners-Lee is a Computer Scientist
http://www.academiawiki.com/
England is part of United Kingdom
http://www.geolocationwiki.com/
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9. TimBernersLee
Tim Berners-Lee was born in London
http://www.academiawiki.com/
birthPlace
rdf:type London is in England
London
http://www.geolocationwiki.com/
Scientist
Computer Scientists are Scientists
http://www.vocabularywiki.com/ rdfs:subClassOf
ComputerScientist
Tim Berners-Lee is a Computer Scientist
isPartOf http://www.academiawiki.com/
UnitedKingdom
England is part of United Kingdom
http://www.geolocationwiki.com/
isPartOf
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10. TimBernersLee
birthPlace
rdf:type
London
Scientist
rdfs:subClassOf
ComputerScientist
isPartOf
England UnitedKingdom
isPartOf
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11. TimBernersLee Scientist
rdf:type rdfs:subClassOf
birthPlace
ComputerScientist
London UnitedKingdom
isPartOf
isPartOf
England
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12. TimBernersLee Scientist
rdf:type rdfs:subClassOf
birthPlace
ComputerScientist
London UnitedKingdom
isPartOf
isPartOf
England
App
• Reasoning
• RDFS/OWL
• Rules
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13. TimBernersLee Scientist
rdf:type
rdf:type rdfs:subClassOf
birthPlace
ComputerScientist
isPartOf
London UnitedKingdom
isPartOf
isPartOf
England
App
• Reasoning
• RDFS/OWL
• Rules
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14. TimBernersLee Scientist
rdf:type
rdf:type rdfs:subClassOf
birthPlace
ComputerScientist
birthPlace birthPlace
isPartOf
London UnitedKingdom
isPartOf
isPartOf
England
App
• Reasoning
• RDFS/OWL
• Rules
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15. TimBernersLee Scientist
rdf:type
rdf:type rdfs:subClassOf
birthPlace
ComputerScientist
birthPlace birthPlace
isPartOf
London UnitedKingdom
isPartOf
isPartOf
England
Scientists born in United Kingdom? App
• Reasoning
Answer: Tim Berners-Lee • RDFS/OWL
• Rules
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16. Tim Berners-Lee is a Scientist
Tim Berners-Lee was born in United Kingdom
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17. Tim Berners-Lee is a Computer Scientist
http://www.academiawiki.com/
Computer Scientists are Scientists
http://www.vocabularywiki.com/
Tim Berners-Lee is a Scientist
Tim Berners-Lee was born in United Kingdom
Tim Berners-Lee was born in England
England is part of United Kingdom
http://www.geolocationwiki.com/
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18. Tim Berners-Lee is a Computer Scientist
http://www.academiawiki.com/
Computer Scientists are Scientists
http://www.vocabularywiki.com/
Tim Berners-Lee is a Scientist
Tim Berners-Lee was born in London
Tim Berners-Lee was born in United Kingdom http://www.academiawiki.com/
London is in England
Tim Berners-Lee was born in England http://www.geolocationwiki.com/
England is part of United Kingdom
http://www.geolocationwiki.com/
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19. “Oh, yeah?” button to support users in assessing the
reliability of information encountered on the Web
- Tim Berners-Lee
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20. What’s been done
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21. What is explained?
Who are the targets?
How explanations are presented?
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22. What is explained?
• Information manipulation steps
• Information manipulation operations
• Proof tree of derivations
• Provenance information such as How, When, Who,
Where
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23. Target
• Human users
• Natural language explanation
• Graphical explanation
• Software agents
• Machine readable descriptions
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24. How explanations are presented?
How explanations are represented for machines?
How human users interact with explanations?
Trust
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25. Presentation
WIQA [Bizer, 2007]
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26. Presentation
KiWi [Kotowski and Bry, 2010]
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27. Presentation
KiWi [Kotowski and Bry, 2010]
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28. Presentation
Explaining entailments in OWL ontologies [Horridgeet al., 2008]
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29. Presentation
Inference Web [McGuinnesset al. (a), 2003] [McGuinnesset al. (b), 2006] [McGuinnesset al. (c), 2008]
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30. Presentation
EASD/KOIOS [Forcheret al., 2010]
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31. Presentation
EASD/KOIOS [Forcheret al., 2010]
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32. Metadata representation
• Proof trees for answers
• Operations used to compute answers
• Different types of provenance information
• Models for how explanations should be presented to
human users
• Trust related information
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33. Metadata representation
• Proof Markup Language (PML) Ontology
• Proof interlingua
• Justifications: information manipulation steps and
operations
• Provenance information
• Trust information
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34. Metadata representation
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35. Metadata representation
Accountability In RDF (AIR) [Kagalet al., 2011]
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36. Metadata representation
• KOIOS
• KOIOS Process Language (KPL) for describing the
behavior of KOIOS problem solver
• The Mathematical Graph Language (MGL) for
transforming the process model to a graph based view.
• VGL for describing the visualization model
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37. Metadata representation
EXPL: WIQA describes its explanation trees (parts and
subparts of an explanation) using the Explanation
(EXPL) Vocabulary
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38. Interaction
• Navigation
• Follow-up
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39. Interaction
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40. Interaction
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41. Trust
• Inference Web
• PML Trust vocabulary
• Trust explanation
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42. Trust
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43. What’s ahead
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44. Infrastructure
• Accommodating common data publishing principle
• Publishing explanation metadata along with data
using linked data principles
• Addressing heterogeneous and distributed nature of the
Web promoting interoperability
• W3C PROV-DM data model as an interchange data
model
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45. Target
• Level of user expertise should be taken into account
while providing explanation
• User profiling
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46. What is explained?
• Semantic Web applications use distributed
interconnected data in their reasoning process
• Explaining network of data used in the reasoning
process, flow of information
• How explanations exposing problem solving methods
influence security and confidentiality?
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47. Metadata representation
• Blank nodes are not good
• Granularity
• Provenance
• Interoperability
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48. Metadata representation
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49. r4ta:Assertion prov:specializationOf
prov:Entity r4ta:DirectAssertion r4ta:antecedent
r4ta:InferredAssertion
prov:Trace
r4ta:Justification prov:ProvenanceContainer
prov:Plan prov:Account
r4ta:InferenceRule
prov:hadPlan
prov:traceTo
r4ta:inferredByRule
r4ta:justifies
prov:qualifiedTrace prov:Activity
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50. Presentation
• User expertise
• What’s useful and what’s overwhelming?
• Context-aware data consumption
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51. Presentation
Summarization
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52. Presentation
Summarization
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53. Interaction
• What kind of interactions are useful need to be
understood
• How to interact established trust?
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54. Trust
• How explanation influence trust in the Semantic Web?
• How to capture established trust and reason over it?
• Explaining trust itself
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55. Trust
“If someone trusts a large company such as IBM, and IBM
brands other companies as ethical, then the person will
trust those companies, too”
– Tim Berners-Lee, Weaving the Web
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56. geo:about_london
<geo:london><voc:isPartOf><geo:England>.
<geo:london><rdfs:label> “London”@en.
<geo:london><voc:population> “7825200”^^xsd:integer.
<geo:london><voc:lat> “51.50853”^^xsd:decimal.
<geo:london><voc:long> “-0.12574”^^xsd:decimal.
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57. geo:about_london
<geo:london><voc:isPartOf><geo:England>.
<geo:london><rdfs:label> “London”@en.
<geo:london><voc:population> “7825200”^^xsd:integer.
<geo:london><voc:lat> “51.50853”^^xsd:decimal.
<geo:london><voc:long> “-0.12574”^^xsd:decimal.
endorses
trust
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58. geo:about_london
<geo:london><voc:isPartOf><geo:England>.
•Explicit endorsements
<geo:london><rdfs:label> “London”@en. •Incoming links: owl:sameAs
<geo:london><voc:population> “7825200”^^xsd:integer.
<geo:london><voc:lat> “51.50853”^^xsd:decimal.
<geo:london><voc:long> “-0.12574”^^xsd:decimal.
endorses
trust
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59. geo:about_london
<geo:london><voc:isPartOf><geo:England>.
•Explicit endorsements
<geo:london><rdfs:label> “London”@en. •Incoming links: owl:sameAs
<geo:london><voc:population> “7825200”^^xsd:integer.
<geo:london><voc:lat> “51.50853”^^xsd:decimal.
<geo:london><voc:long> “-0.12574”^^xsd:decimal.
•Explanation of trust and
endorsement network
endorses
trust
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60. Please see the research report RR-7974 for the list of references:
http://hal.inria.fr/hal-00702277
Thank you
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