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1. Semantic Web Modellare e Condividere per Innovare

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Title: 1. Semantic Web Modellare e Condividere per Innovare


1
1. Semantic WebModellare e Condividere per
Innovare
  • Parte V conclusione

2
Sommario
  • Un modello per studiare linnovazione
  • Il Semantic Web
  • Esempi di applicazione

3
Innovazione
4
Innovazione
creare
idea
problemi
innovare
analizzare
micro fenomeno
macro fenomeno
complessità 6.000.000.000 persone
5
Innovazione
creare
idea
problemi
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
magia
6
Innovazione
creare
idea
problemi
ingegneria
scienza
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
magia
7
Innovare
creare
idea
innovare
micro fenomeno
complessità
8
non è mai solo una questione di tecnologia
creare
idea
soluzione tecnica
soluzione sociale
innovare
micro fenomeno
complessità
9
Un modello per studiare linnovazione
creare
idea
problemi
soluzione tecnica
soluzione sociale
innovare
analizzare
micro fenomeno
macro fenomeno
complessità
10
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
11
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
12
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
13
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
14
(No Transcript)
15
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

16
Tim Berners-Lees Semantic Wave (2003)
17
Tim Berners-Lees Semantic Wave (2008)
18
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,

19
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

20
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
21
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/
22
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/

23
Two ways for computer to understand 1/2
  • Smarter machines
  • Smarter data

24
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
25
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

26
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
27
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
28
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
29
Semantic Web layer cake
Already Possible
UnderInvestigation
Standardized
source http//www.w3.org/2007/03/layerCake.png
30
Data Interchange RDF
31
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.

32
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!
33
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

34
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
35
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

36
Query SPARQL
37
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/...

38
Ontology RDF-S and OWL
39
What does it mean?
Formal, explicit specification of a shared
conceptualization
40
How much explicit shall the specification be?
A little semantics, goes a long way James
Hendler, 2001
41
A simple ontology
42
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
43
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 -
44
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)

45
The ontology we specified
46
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/
47
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)

48
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?

49
Knowing the ontology and RDF semantics
  • A recipient, that knows the ontology and
    understands RDF semantics,
  • Receiving Rodin sculpts TheKiss .

Rodin
TheKiss
50
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

51
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

52
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
53
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)

54
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)

55
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)

56
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.

57
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

58
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

59
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)

60
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

61
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

63
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

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Soluzione manuale
  1. Vado su musicbrainz e guardo quali album hanno
    pubblicato

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

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

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Music Event Explorer
  • Una soluzione poco praticabile
  • ma automatizzabile

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http//meex.cefriel.it/meex
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