1. Semantic Web Modellare e Condividere per Innovare

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1. Semantic WebModellare e Condividere per
Innovare

• Parte V conclusione

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Sommario

• Un modello per studiare linnovazione
• Il Semantic Web
• Esempi di applicazione

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Innovazione
4
Innovazione
creare
idea
problemi
innovare
analizzare
micro fenomeno
macro fenomeno
complessità 6.000.000.000 persone
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Innovazione
creare
idea
problemi
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
magia
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Innovazione
creare
idea
problemi
ingegneria
scienza
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
magia
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Innovare
creare
idea
innovare
micro fenomeno
complessità
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non è mai solo una questione di tecnologia
creare
idea
soluzione tecnica
soluzione sociale
innovare
micro fenomeno
complessità
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Un modello per studiare linnovazione
creare
idea
problemi
soluzione tecnica
soluzione sociale
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
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Analizziamo il Web delle origini
Non riesco ad accedere allinformazione
Ipertesti Internet
creare
idea
problemi
Come trovole pagine?
URI HTTP HTML
Come posso scrivere?
soluzione tecnica
soluzione sociale
innovare
analizzare
Condividere info Link a cose interessanti
micro fenomeno
macro fenomeno
WWW
Esplosione del fenomeno Web
complessità
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Analizziamo google
Come trovole pagine?
Indici SVM
creare
idea
problemi
Google spoofing
PageRank
soluzione tecnica
soluzione sociale
innovare
analizzare
Condividere info Link a cose interessanti
micro fenomeno
macro fenomeno
Google
Il fenomeno Google
complessità
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Analizziamo il Web 2.0
Come posso scrivere?
wiki-wiki e diari Web
creare
idea
problemi
wiki blog
Come gestire tutta questa info?
soluzione tecnica
soluzione sociale
innovare
analizzare
Condividere info Link a cose interessanti
micro fenomeno
macro fenomeno
I fenomeni Wikipedia, blogosphere,
Web 2.0
complessità
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Analizziamo il Semantic Web
KR Web
Come gestire i dati sul Web?
creare
idea
problemi
?
Modellare RDF OWL SPARQL RIF
soluzione tecnica
soluzione sociale
innovare
analizzare
Condividere info Link a cose interessanti
micro fenomeno
macro fenomeno
?
Semantic Web
complessità
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Semantic Web

• Un modo di specificare dati e relazioni tra i
  dati
• Permette di condividere e riusare dati tra
  applicazioni, imprese e gruppi di interesse
• Una collezione di tecnologie
• RDF
• RDF-S
• OWL
• GRDDL
• SPARQL
• La prossima onda del Web da surfare

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Tim Berners-Lees Semantic Wave (2003)
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Tim Berners-Lees Semantic Wave (2008)
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The corporate landscape is moving

• Major companies offer (or will offer) Semantic
  Web tools or systems using Semantic Web
• Adobe, Oracle, IBM, HP, Software AG, GE, Northrop
  Gruman, Altova, Microsoft, Dow Jones,
• Others are using it (or consider using it) as
  part of their own operations
• Novartis, Boeing, Pfizer, Telefónica,
• Some of the names of active participants in W3C
  SW related groups
• ILOG, HP, Agfa, SRI International, Fair Isaac
  Corp., Oracle, Boeing, IBM, Chevron, Siemens,
  Nokia, Pfizer, Sun, Eli Lilly,

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The 2007 Gartner predictions

• During the next 10 years, Web-based technologies
  will improve the ability to embed semantic
  structures it will occur in multiple
  evolutionary steps
• By 2017, we expect the vision of the Semantic Web
  to coalesce and the majority of Web pages
  are decorated with some form of semantic
  hypertext.
• By 2012, 80 of public Web sites will use some
  level of semantic hypertext to create SW
  documents 15 of public Web sites will use
  more extensive Semantic Web-based ontologies to
  create semantic databases
• Source Finding and Exploiting Value in
  Semantic Web Technologies on the Web, Gartner
  Research Report, May 2007

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The Web Today
Too much information to browse, need for
searching and mashing up automatically
Large number of integrations - ad hoc -
pair-wise
Millions of Applications
?
Each site is understandable for us
Computers dont understand much
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What does understand mean?

• What we say to Web agents
• " For more information visit lta
  hrefhttp//www.ex.orggt my company lt/agt Web
  site. . .
• What they hear
• " blah blah blah blah blah lta hrefhttp//www.ex.
  orggt blah blah blah lt/agt blah blah. . .
• Jet this is enought to train them to achive tasks
  for us

source http//www.thefarside.com/
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What does Google understand?

• Understanding that
• page1 links page2 ? page2 is interesting
• Google is able to rank results!
• The heart of our software is PageRank, a system
  for ranking web pages (that) relies on the
  uniquely democratic nature of the web by using
  its vast link structure as an indicator of an
  individual page's value.
• http//www.google.com/technology/

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Two ways for computer to understand 1/2

• Smarter machines
• Smarter data

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Two ways for computer to understand 2/2

• Smarter machines
• Such as
• Natural Langue processing (NLP)
• Audio Processing
• Image Processing (IP)
• Video Processing
• many many more
• They all work fine alone, the problem is combinig
  them
• E.g., NLP meets IP
• NLP What does your eye see?
• IP I see a sea
• NLP You see a c?
• IP Yes, what else could it be?
• Not the Semantic Web approach
• Smarter Data
• Make data easier for machines to publish, share,
  find and understand
• E.g. wornet2.1sea/noun/1 vs. wordnet2.1c/noun/10
  
• The Semantic Web approach

Some NLP Related Entertainment http//www.cl.cam.a
c.uk/Research/ NL/amusement.html
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The Semantic Web 1/4

• The Semantic Web is not a separate Web, but an
  extension of the current one, in which
  information is given well-defined meaning, better
  enabling computers and people to work in
  cooperation.
• The Semantic Web, Scientific American Magazine,
  Maggio 2001 http//www.sciam.com/article.cfm?artic
  leID00048144-10D2-1C70-84A9809EC588EF21
• Key concepts
• an extension of the current Web
• in which information is given well-defined
  meaning
• better enabling computers and people to work in
  cooperation.
• Both for computers and people

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The Semantic Web 2/4

• The Semantic Web is not a separate Web, but an
  extension of the current one

Web 1.0
The Web Today
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The Semantic Web 3/4

• The Semantic Web , in which information is
  given well-defined meaning

Semantic Web
Web 1.0
?
Human understandable but only machine-readable
Human and machine understandable
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The Semantic Web 4/4
better enabling computers and people to work
in cooperation.
Fewer Integration - standard - multi-lateral
Even More Applications
Semantic Web
Semantic Mash-ups Search
Easier to understand for people
More understandable for computers
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Semantic Web layer cake
Already Possible
UnderInvestigation
Standardized
source http//www.w3.org/2007/03/layerCake.png
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Data Interchange RDF
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RDF Resource Description Framework

• RDF is a general method for conceptual
  description or modeling of information that is
  implemented in web resources
• Basically speaking, the RDF data model is based
  upon the idea of making statements about Web
  resources, in the form of subject-predicate-object
  expressions.These expressions are known as
  triples in RDF terminology.
• The subject denotes the resource, and the
  predicate denotes traits or aspects of the
  resource and expresses a relationship between the
  subject and the object.

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RDF Resource Description Framework

• For example, one way to represent the notion "The
  sky has the color blue" in RDF is as the triple
• a subject denoting "the sky"
• wordnetsynset-sky-noun-1
• a predicate denoting "has the color"
• wordnetwordsense-color-verb-6
• an object denoting "blue
• wordnetsynset-blue-noun-1
• In FOL we could write
• predicate(subject, object)
• wnwordsense-color-verb-6(wnsynset-sky-noun-1,
  wnsynset-blue-noun-1)

Click read!
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Serialization of RDF

• Serialization (N3 notation)
• subject predicate object .
• _at_prefix wn lthttp//www.w3.org/2006/03/wn/wn20/sch
  ema/gt.
• wnsynset-sky-noun-1 wnwordsense-color-verb-6
  wnsynset-blue-noun-1 .
• Serialization (N3 notation)
• ltrdfDescription about"subject"gt
• ltpredicate rdfresource"object/gt
• lt/rdfDescriptiongt
• lt rdfRDF
• xmlnsrdf"http//www.w3.org/1999/02/22-rdf-syn
  tax-ns"
• xmlnswn"http//www.w3.org/2006/03/wn/wn20/sch
  ema/" gt
• ltrdfDescription about"wnsynset-sky-noun-1"gt
• ltwnwordsense-color-verb-6
• rdfresource"wnsynset-blue-noun-1"/gt
• lt/rdfDescriptiongt
• lt/rdfRDFgt

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Example BBCs Artist as Linked Data

• lt?xml version"1.0" encoding"utf-8"?gt
• ltrdfRDF
• xmlnsrdf "http//www.w3.org/1999/02/22-rdf-synt
  ax-ns"
• xmlnsrdfs "http//www.w3.org/2000/01/rdf-schema
  "
• xmlnsowl "http//www.w3.org/2002/07/owl"
• xmlnsdc "http//purl.org/dc/elements/1.1/"
• xmlnsfoaf "http//xmlns.com/foaf/0.1/"
• xmlnsrel "http//www.perceive.net/schemas/relat
  ionship/"
• xmlnsmo "http//purl.org/ontology/mo/"
• xmlnsrev "http//purl.org/stuff/rev" gt
• ltrdfDescription rdfabout"/music/artists/a3cb23f
  c-acd3-4ce0-8f36-1e5aa6a18432.rdf"gt
• ltrdfslabelgtDescription of the artist
  U2lt/rdfslabelgt
• ltfoafprimaryTopic rdfresource"/music/artists/
  a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432artist"/gt
• lt/rdfDescriptiongt
• ltmoMusicGroup rdfabout"/music/artists/a3cb23fc-
  acd3-4ce0-8f36-1e5aa6a18432artist"gt
• ltfoafnamegtU2lt/foafnamegt
• ltowlsameAs rdfresource"http//dbpedia.org/res
  ource/U2" /gt
• ltfoafpage rdfresource"/music/artists/a3cb23fc
  -acd3-4ce0-8f36-1e5aa6a18432.html" /gt
• ltmomusicbrainz rdfresource"http//musicbrainz
  .org/artist/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.h
  tml" /gt

HTML http//www.bbc.co.uk/music/artists/a3cb23fc-
acd3-4ce0-8f36-1e5aa6a18432 RDF
http//www.bbc.co.uk/music/artists/a3cb23fc-acd3-4
ce0-8f36-1e5aa6a18432.rdf
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If you want to see the triples

• RDF is not always serialized in N3 notation, so
  if you want to see the triples you can use W3C
  RDF Validation Service
• http//www.w3.org/RDF/Validator/
• To see the triples in the RDF version of the page
  about U2 on BCC
• http//www.w3.org/RDF/Validator/ARPServlet?URIhtt
  p3A2F2Fwww.bbc.co.uk2Fmusic2Fartists2Fa3cb23
  fc-acd3-4ce0-8f36-1e5aa6a18432.rdfPARSEParseUR
  I3ATRIPLES_AND_GRAPHPRINT_TRIPLESFORMATPNG_E
  MBED

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Query SPARQL
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What is SPARQL?

• SPARQL
• is the query language of the Semantic Web
• stays for SPARQL Protocol and RDF Query Language
• A Query Language ...Find names and websites of
  contributors to PlanetRDF PREFIX foaf
  lthttp//xmlns.com/foaf/0.1/gt SELECT ?name
  ?website FROM lthttp//planetrdf.com/bloggers.rdfgt
  WHERE ?person foafweblog ?website
  ?person foafname ?name . ?website a
  foafDocument
• ... and a Protocol.http//.../qps?
  query-langhttp//www.w3.org/TR/rdf-sparql-query/
  graph-idhttp//planetrdf.com/bloggers.rdf
  queryPREFIX foaf lthttp//xmlns.com/foaf/0.1/...
  

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Ontology RDF-S and OWL
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What does it mean?
Formal, explicit specification of a shared
conceptualization
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How much explicit shall the specification be?
A little semantics, goes a long way James
Hendler, 2001
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A simple ontology
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Specifying classes, sub-classes and instances

• Creating a class
• RDFS Artist rdftype rdfsClass .
• FOL ?x Artist(x)
• Creating a subclass
• RDFS Painter rdfssubClassOf Artist .
• RDFS Sculptor rdfssubClassOf Artist .
• FOL ?x Painter(x) ? Sculptor(x) ? Artist(x)
• Creating an instance
• RDFS Rodin rdftype Sculptor .
• FOL Sculptor(Rodin)

Artist
Painter
Sculptor
Rodin
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Specifying properties and sub-properties

• Creating a property
• RDFS creates rdftype rdfProperty .
• FOL ?x ?y Creates(x,y)
• Using a property
• RDFS Rodin creates TheKiss .
• FOL Creates(Rodin, TheKiss)
• Creating subproperties
• RDFS paints rdfssubPropertyOf creates .
• FOL ?x ?y Paints(x,y) ? Creates(x,y)
• RDFS sculpts rdfssubPropertyOf creates .
• FOL ?x ?y Sculpts(x,y) ? Creates(x,y)

creates
paints
- 42 -
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Specifying domain/range constrains

• Checking which classes and properties can be use
  together
• RDFS
• creates rdfsdomain Artist .
• creates rdfsrange Piece .
• paints rdfsdomain Painter .
• paints rdfsrange Paint .
• sculpts rdfsdomain Sculptor .
• sculpts rdfsrange Sculpt .
• FOL
• ?x ?y Creates(x,y) ? Artist(x) ? Piece(y)
• ?x ?y Paints(x,y) ? Painter(x) ? Paint(y)
• ?x ?y Sculpts(x,y) ? Sculptor(x) ? Sculpt(y)

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The ontology we specified
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RDF semantics (a part of it)

• hypothesis conclusion
• x rdfssubClassOf y . a rdftype y .a
  rdftype x .
• x rdfssubClassOf y . x rdfssubClassOf z .y
  rdfssubClassOf z .
• x a y . x b y . a
  rdfssubPropertyOf b .
• a rdfssubPropertyOf b . a rdfssubPropertyOf c
  .b rdfssubPropertyOf c .
• x a y . x rdftype z .a
  rdfsdomain z .
• x a u . u rdftype z .a
  rdfsrange z .

Read out more in RDF Semantics http//www.w3.org/T
R/rdf-mt/
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First Order Calculus and RDF semantics

• RDFS inference rules are valid deduction
• hypothesis Conclusion
• p rdfssubClassOf q . a rdftype q .
• a rdftype p .
• In FOL
• ?x P(x) ? Q(x),
• P(A)
• ? Q(A)
• We can demonstate that it is a valid deduction
  using First Order Calculus
• 1. ?x P(x) ? Q(x) hypothesis
• 2. P(A) hypothesis
• 3. P(A) ? Q(A) E?(1)
• 4. Q(A) E?(3,2)

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Without Inference

• A recipient, that only understands XML syntax,
• receiving
• ltRDFgt
• ltDescription about"Rodin"gt
• ltsculpts resource"TheKiss"/gt
• lt/Descriptiongt
• lt/RDFgt
• can answer the following queries
• What does Rodin sculpt?
• RDF/Description_at_about'Rodin'/sculpts/_at_resource
• Who does sculpt TheKiss?
• RDF/Descriptionsculpts/_at_resource'TheKiss'/_at_abou
  t
• Try out your self at http//www.mizar.dk/XPath/
• but it cannot answer
• Who is Rodin?
• What is TheKiss?
• Is there any Sculptor/Scupts?
• Is there any Artist/Piece?

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Knowing the ontology and RDF semantics

• A recipient, that knows the ontology and
  understands RDF semantics,
• Receiving Rodin sculpts TheKiss .

Rodin
TheKiss
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a reasoner can answer 1/2

• the previous queries
• What does Rodin sculpt?
• PREFIX rdfs lthttp//www.w3.org/2000/01/rdf-schema
  gt
• PREFIX ex lthttp//www.ex.org/schemagt
• SELECT ?x
• WHERE exRodin exsculpts ?x
• ?x exTheKiss
• Who does sculpt TheKiss?
• WHERE exRodin exsculpts ?x
• ?x exRodin
• and it can also answer
• Who is Rodin?
• WHERE exRodin a ?x
• ?x exArtist, exSculptor, rdfsResource
• What is TheKiss?
• WHERE exTheKiss a ?x
• ?x exSclupt, exPiece, rdfsResource

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a reasoner can answer 2/2

• Is there any Sculptor?
• WHERE ?x a exSculptor
• ?x exRodin
• Is the any Artist?
• WHERE ?x a exArtist
• ?x exRodin
• Is there any Sculpt?
• WHERE ?x a exSculpt
• ?x exTheKiss
• Is there any Piece?
• WHERE ?x a exPiece
• ?x exTheKiss
• Is there any Paint?
• WHERE ?x a exPaint
• 0 results
• Is there any Painter?
• WHERE ?x a exPainter
• 0 results

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SPARQL vs Reasoner

• SPARQL alone cannot answer queries that require
  reasoning
• but a reasoner can be exposed as a SPARQL
  service.

RDF
SPARQLservice
Reasoner
RDF
SPARQLservice
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More expressive power 1/3

• RDFS is a light ontological language that allows
  for defining simple vocabularies.
• One may want also express
• Cardinality constrains (max, min, exactly) for
  properties usage
• Es. a Polygon has 3 or more edges
• ?x Polygon(x) ? 3y Edge(y) ? Forms(y,x)
• Property types
• transitive
• e.g. hasAncestor is a transitive property if A
  hasAncestor B and B hasAncestor C, then A
  hasAncestor C.
• ?x ?y ?z HasAncestor(x,y) ? HasAncestor(y,z) ?
  HasAncestor(x,z)
• inverse
• e.g. sclupts has isSculptedBy as inverse
  propertyif A sclupts B then B isSculptedBy A
• ?x ?y Sculpts(x,y) ? IsSculptedBy(y,x)

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More expressive power 2/3

• simmetric
• e.g. isCloseTo is a simmetric property if A
  isCloseTo B then B isCloseTo A
• ?x ?y IsCloseTo(x,y) ? IsCloseTo(y,x)
• Restrictions of usage for a specific property
• All values of property must be of a certain kind
• e.g. a D.O.C. Wine can be only produced by a
  Certified Wienery
• ?x ?y DOCWine(x) ? Produces(x,y) ?
  CertifiedWienery(y)
• Some values of property must be of a certain kind
• e.g. a Famous Painter must have painted some
  Famous Painting
• ?x FamousPainter(x) ? ?y FamousPaint(y) ?
  IsPaintedBy(y,x)
• A class is defined combining other classes
  (union, intersection, negation, ...)
• A white wine is a Wine and its color is white
• ?x Wine(x) ? White(x)

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More expressive power 3/3

• Two instances refers to the same real object
• The Boss and Bruce Springsteen are two names
  for the same person
• TheBoss BruceSpringsteen
• Two classes refers to the same set
• Painters in english and Pittori in italian
• ?x Painter(x) ? Pittore(x)
• Two properties refers to the same binary
  relationship
• Paints in english and Dipinge in italian
• ?x ?y Paints(x,y) ? Dipinge(x,y)

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Expressivity vs. Tractability

• The more an ontological language is expressive
  the less is tractable
• the Web Ontology Language (OWL) comes with
  several profiles that offers different trade-offs
  between expressivity and tractability.

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OWL 2 profiles

• OWL 1 defines only one fragment (OWL Lite)
• And it isnt very tractable!
• OWL 2 defines several different fragments with
• Useful computational properties
• E.g., reasoning complexity in range LOGSPACE to
  PTIME
• Useful implementation possibilities
• E.g., Smaller fragments implementable using RDBs
• OWL 2 profiles
• OWL 2 EL, OWL 2 QL, OWL 2 RL

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OWL 2 EL

• Useful for applications employing ontologies that
  contain very
• large number of properties and/or classes
• Captures expressive power used by many
  large-scaleontologies E.g. SNOMED CT, NCI
  thesaurus
• Features
• Included existential restrictions, intersection,
  subClass,equivalentClass, disjointness, range and
  domain, object property inclusion possibly
  involving property chains, and data property
  inclusion, transitive properties, keys
• Missing include value restrictions, Cardinality
  restrictions (min, max and exact), disjunction
  and negation
• Maximal language for which reasoning (including
  query answering) known to be worst-case polynomial

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OWL 2 QL

• Useful for applications that use very large
  volumes of data, and where query answering is the
  most important task
• Captures expressive power of simple ontologies
  like thesauri, classifications, and (most of)
  expressive power of ER/UML schemas
• E.g., CIM10, Thesaurus of Nephrology, ...
• Features
• Included limited form of existential
  restrictions, subClass, equivalentClass,
  disjointness, range domain, symmetric
  properties,
• Missing existential quantification to a class,
  self restriction, nominals, universal
  quantification to a class, disjunction etc.
• Can be implemented on top of standard relational
  DBMS
• Maximal language for which reasoning (including
  query answering) is known to be worst case
  logspace (same as DB)

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OWL 2 RL

• Useful for applications that require scalable
  reasoning without sacrifying too much expressive
  power, and where query answering is the most
  important task
• Support most OWL features but
• with restrictions placed on the syntax of OWL 2
• standard semantics only apply when they are used
  in a restricted way
• Can be implemented on top of rule extended DBMS
• E.g., Oracles OWL Prime implemented using
  forward chaining rules in Oracle 11g
• Related to DLP and pD
• Allows for scalable (polynomial) reasoning using
  rule-based technologies

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Application
62
Light weight semantic mark-up
ltdiv id"event-info-where" class"info-wh-info
vcard"gt lth2gtlta rel"bookmark" class"fn org
location" href"/venues/V0-001-00
0693919-2"gt Circus Krone
Munichlt/agtlt/h2gt ltdiv class"adr"gt
ltspan class"street-address"gt1lt/spangtltbrgt
ltspan class"locality"gtMunichlt/spangt,
ltspan class"region"gtBayernlt/spangt ltbrgt
ltspan class"country-name"gtGermanylt/spangt

• A firefox plug-in such as Operator can extract
  those semantic mark-up from the page and offers
  actions such as add the event to your calendar
• https//addons.mozilla.org/en-US/firefox/addon/410
  6

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Linking Open Data Project

• Goal extend the Web with data commons by
  publishing open data sets using Semantic Web techs

• Project Chartres
• RDFizers and ConverterToRdf
• Publishing Tools
• Semantic Web Browsers and Client Libraries
• Semantic Web Search Engines
• Applications

Visit http//esw.w3.org/topic/SweoIG/TaskForces/C
ommunityProjects/LinkingOpenData !
64
Navigating the Semantic Web

• Use a Semantic Web search engine to enter into it
• E.g., sindice http//sindice.com/
• Search for something (e.g., Varese)
• Click and browse
• NOTE Its meant for machine consumption!

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The new era of Semantic Apps

• One of the highlights of October's Web 2.0 Summit
  in San Francisco was the emergence of 'Semantic
  Apps' as a force.
• The purpose of this post is to highlight 10
  Semantic Apps. It reflects the nascent status
  of this sector, even though people like Hillis
  and Spivack have been working on their apps for
  years now.

• Read out more at http//www.readwriteweb.com/archi
  ves/10_semantic_apps_to_watch.php

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Esempi di applicazioni

• Allen Brain Atlas Gene Expression Results
• http//sw.neurocommons.org/hcls_gene_image.html
• SWEOs use case collection
• http//www.w3.org/2001/sw/sweo/public/UseCases/
• Linking Open Data Project
• http//esw.w3.org/topic/SweoIG/TaskForces/Communit
  yProjects/LinkingOpenData
• Music Event Explorer
• http//meex.cefriel.it/meex/

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Music Event Explorer

• Esigenza dove posso andare a sentire musica folk
  nei prossimi giorni?
• Soluzione manuale
• Vado su musicmoz e scopro i cantanti che fanno
  musica folk
• Vado su musicbrainz e guardo quali album hanno
  pubblicato
• Per ciascuno di quelli che mi piace cerco su EVDB
  se ci ha organizzato eventi nei prossimi giorni
• Mi appunto i posti e poi li cerco in GoogleMaps

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Soluzione manuale

• Vado su musicmoz e scopro i cantanti che fanno
  musica folk

69
Soluzione manuale

1. Vado su musicbrainz e guardo quali album hanno
   pubblicato

70
Soluzione manuale

1. Per ciascuno di quelli che mi piace cerco su EVDB
   se ci ha organizzato eventi nei prossimi giorni

71
Soluzione manuale

1. Mi appunto i posti e poi li cerco in GoogleMaps

72
Music Event Explorer

• Una soluzione poco praticabile
• ma automatizzabile

73
http//meex.cefriel.it/meex