1. Semantic Web Modellare e Condividere per Innovare

Ingegneria della conoscenza 2007-08Emanuele Della ValleScienze e Tecniche Della Comunicazione

1. Semantic WebModellare e Condividere per Innovare

Parte V: conclusione

I-1

2Sommario

Un modello per studiare l’innovazione

Il Semantic Web

Esempi di applicazione

I-1Innovazione

3

I-1Innovazione

4

idea

microfenomeno

macrofenomeno

problemi

inn

ovare

an

aliz

zare

creare

complessità = 6.000.000.000 persone

I-1Innovazione

5

idea

microfenomeno

macrofenomeno

problemi

inn

ovare

an

aliz

zare

creare

complessità = magia

I-1Innovazione

6

idea

microfenomeno

macrofenomeno

problemi

inn

ovare

an

aliz

zare

creare

complessità = magia

scie

nza

ingegneria

I-1Innovare …

7

idea

microfenomeno

inn

ovare

creare

complessità

I-1… non è mai solo una questione di tecnologia

8

idea

microfenomeno

inn

ovare

soluzione tecnic

a

soluzione sociale

creare

complessità

I-1Un modello per studiare l’innovazione

9

idea

microfenomeno

macrofenomeno

problemi

an

aliz

zare

creare

complessità

soluzione tecnic

a

soluzione sociale

inn

ovare

I-1Analizziamo il Web delle origini

10

idea

microfenomeno

macrofenomeno

problemi

an

aliz

zare

creare

complessità

soluzione tecnic

a

soluzione sociale

inn

ovare

Non riesco ad accedere all’informazione Ipertesti + Internet

WWW

Condividere infoLink a cose interessanti

URI HTTP HTML

Esplosione del fenomeno Web

Come trovole pagine?

Come posso scrivere?

I-1Analizziamo google

11

idea

microfenomeno

macrofenomeno

problemi

an

aliz

zare

creare

complessità

soluzione tecnic

a

soluzione sociale

inn

ovare

Come trovole pagine?

Indici + SVM

Google

PageRank

Il fenomeno Google

Google spoofing


I-1Analizziamo il Web 2.0

12

idea

microfenomeno

macrofenomeno

problemi

an

aliz

zare

creare

complessità

soluzione tecnic

a

soluzione sociale

inn

ovare

Come posso scrivere?

wiki-wiki e diari Web

Web 2.0

wiki blog

I fenomeni Wikipedia, blogosphere, …

Come gestire tutta questa info?


I-1Analizziamo il Semantic Web

13

idea

microfenomeno

macrofenomeno

problemi

an

aliz

zare

creare

complessità

soluzione tecnic

a

soluzione sociale

inn

ovare

Come gestire i dati sul Web?

KR + Web

Semantic Web

ModellareRDF OWL

SPARQL RIF

?

?


I-1

14

I-1Semantic 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 …

15

I-1Tim Berners-Lee’s Semantic Wave (2003)

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I-1Tim Berners-Lee’s Semantic Wave (2008)

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I-1The “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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I-1The 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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I-1The Web Today

Large number of integrations - ad hoc - pair-wise

Too much information to browse, need for searching and mashing up automatically

Each site is “understandable” for us Computers don’t “understand” much

?

Search & Mash-up Engine

010 0 1 1 0

01101

10100 10 0010 01 101 101 01 110 1 10 110 0 1 1 01 0 1 0 0 1 1 0 1 1 1 10 01 101 0 1

Millions of Applications

20

I-1What does “understand” mean?

What we say to Web agents

" For more information visit <a href=“http://www.ex.org”> my company </a> Web site. . .”

What they “hear”

" blah blah blah blah blah <a href=“http://www.ex.org”> blah blah blah </a> blah blah. . .”

Jet this is enought to train them to achive tasks for us

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[ source http://www.thefarside.com/ ]

I-1What 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/

22

I-1Two ways for computer to “understand” 1/2

Smarter machines

Smarter data

23

I-1Two 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. wornet2.1:sea/noun/1 vs. wordnet2.1:c/noun/10 The Semantic Web approach

24

Some NLP Related Entertainment http://www.cl.cam.ac.uk/Research/

NL/amusement.html

I-1The 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?articleID=00048144-10D2-1C70-84A9809EC588EF21

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

25


“The Semantic Web is not a separate Web, but an extension of the current one […] ”

26

Web 1.0 The Web Today


“The Semantic Web […] , in which information is given well-defined meaning […]”

27

Human understandable but “only” machine-

readable

Human and machine “understandable”

?

Web 1.0 Semantic Web


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Semantic Web

Fewer Integration - standard - multi-lateral

[…] better enabling computers and people to

work in cooperation.Even More Applications

Easier to understand for people

More “understandable” for computers

Semantic Mash-ups &Search

I-1Semantic Web “layer cake”

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Standardized

UnderInvestigation

Already Possible

[ source http://www.w3.org/2007/03/layerCake.png ]

I-1Data Interchange: RDF

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I-1RDF: 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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I-1RDF: 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"

wordnet:synset-sky-noun-1 a predicate denoting "has the color"

wordnet:wordsense-color-verb-6 an object denoting "blue“

wordnet:synset-blue-noun-1

In FOL we could write predicate(subject, object) wn:wordsense-color-verb-6(wn:synset-sky-noun-1, wn:synset-blue-noun-1)

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Click & read!

I-1Serialization of RDF

Serialization (N3 notation) subject predicate object .@prefix wn: <http://www.w3.org/2006/03/wn/wn20/schema/>.

wn:synset-sky-noun-1 wn:wordsense-color-verb-6 wn:synset-blue-noun-1 .

Serialization (N3 notation) <rdf:Description about="subject">

<predicate rdf:resource="object“/> </rdf:Description>

< rdf:RDF

xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"

xmlns:wn="http://www.w3.org/2006/03/wn/wn20/schema/" >

<rdf:Description about="wn:synset-sky-noun-1">

<wn:wordsense-color-verb-6

rdf:resource="wn:synset-blue-noun-1"/>

</rdf:Description>

</rdf:RDF>

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I-1Example: BBC’s Artist as Linked Data

<?xml version="1.0" encoding="utf-8"?> <rdf:RDF xmlns:rdf = "http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs = "http://www.w3.org/2000/01/rdf-schema#" xmlns:owl = "http://www.w3.org/2002/07/owl#" xmlns:dc = "http://purl.org/dc/elements/1.1/" xmlns:foaf = "http://xmlns.com/foaf/0.1/" xmlns:rel = "http://www.perceive.net/schemas/relationship/" xmlns:mo = "http://purl.org/ontology/mo/" xmlns:rev = "http://purl.org/stuff/rev#" > <rdf:Description rdf:about="/music/artists/a3cb23fc-acd3-4ce0-

8f36-1e5aa6a18432.rdf"> <rdfs:label>Description of the artist U2</rdfs:label> <foaf:primaryTopic rdf:resource="/music/artists/a3cb23fc-acd3-

4ce0-8f36-1e5aa6a18432#artist"/> </rdf:Description> <mo:MusicGroup rdf:about="/music/artists/a3cb23fc-acd3-4ce0-

8f36-1e5aa6a18432#artist"> <foaf:name>U2</foaf:name> <owl:sameAs rdf:resource="http://dbpedia.org/resource/U2" /> <foaf:page rdf:resource="/music/artists/a3cb23fc-acd3-4ce0-

8f36-1e5aa6a18432.html" /> <mo:musicbrainz

rdf:resource="http://musicbrainz.org/artist/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.html" />

<mo:homepage rdf:resource="http://www.u2.com/" /> <mo:fanpage rdf:resource="http://www.atu2.com/" /> <mo:wikipedia

rdf:resource="http://en.wikipedia.org/wiki/U2" /> <mo:imdb

rdf:resource="http://www.imdb.com/name/nm1277752/" /> <mo:myspace rdf:resource="http://www.myspace.com/u2" /> <mo:member rdf:resource="/music/artists/7f347782-eb14-

40c3-98e2-17b6e1bfe56c#artist" /> <mo:member rdf:resource="/music/artists/1f52af22-0207-

40ac-9a15-e5052bb670c2#artist" />

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HTML: http://www.bbc.co.uk/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432 RDF : http://www.bbc.co.uk/music/artists/a3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.rdf

I-1If 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?

URI=http%3A%2F%2Fwww.bbc.co.uk%2Fmusic%2Fartists%2Fa3cb23fc-acd3-4ce0-8f36-1e5aa6a18432.rdf+&PARSE=Parse+URI%3A+&TRIPLES_AND_GRAPH=PRINT_TRIPLES&FORMAT=PNG_EMBED

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I-1Query: SPARQL

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I-1What 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: <http://xmlns.com/foaf/0.1/> SELECT ?name ?website FROM <http://planetrdf.com/bloggers.rdf> WHERE { ?person foaf:weblog ?website ; ?person foaf:name ?name . ?website a foaf:Document }

... and a Protocol.http://.../qps? query-lang=http://www.w3.org/TR/rdf-sparql-query/ &graph-id=http://planetrdf.com/bloggers.rdf &query=PREFIX foaf: <http://xmlns.com/foaf/0.1/...

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I-1Ontology: RDF-S and OWL

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I-1What does it mean?

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Formal, explicit specification of a shared conceptualization

Machinereadable

Several peopleagrees that suchconceptual model

is adequate to describe such aspects of the

reality

A conceptual model of someaspects of the

realityIt makesdomain

assumptionexplicit

I-1How much explicit shall the specification be?

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“A little semantics, goes a long way”[James Hendler, 2001]

“A little semantics, goes a long way”[James Hendler, 2001]

I-1A simple ontology

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Artist Piece

Painter Paint

paints

Sculptor Sculpt

sculpts

creates

I-1Specifying classes, sub-classes and instances

Creating a class RDFS: Artist rdf:type rdfs:Class . FOL: x Artist(x)

Creating a subclass RDFS: Painter rdfs:subClassOf Artist . RDFS: Sculptor rdfs:subClassOf Artist . FOL: x [Painter(x) Sculptor(x) Artist(x)]

Creating an instance RDFS: Rodin rdf:type Sculptor . FOL: Sculptor(Rodin)

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ArtistPainter

SculptorRodin

I-1

Creating a property RDFS: creates rdf:type rdf:Property . FOL: x y Creates(x,y)

Using a property RDFS: Rodin creates TheKiss . FOL: Creates(Rodin, TheKiss)

Creating subproperties RDFS: paints rdfs:subPropertyOf creates . FOL: x y [Paints(x,y) Creates(x,y)] RDFS: sculpts rdfs:subPropertyOf creates . FOL: x y [Sculpts(x,y) Creates(x,y)]

Specifying properties and sub-properties 43

creates

paints

I-1Specifying domain/range constrains

Checking which classes and properties can be use together

RDFS:creates rdfs:domain Artist .

creates rdfs:range Piece .

paints rdfs:domain Painter .

paints rdfs:range Paint .

sculpts rdfs:domain Sculptor .

sculpts rdfs:range 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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I-1The ontology we specified

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Artist Piece

Painter Paint

paints

Sculptor Sculpt

sculpts

creates

I-1RDF semantics (a part of it)

hypothesis conclusion

x rdfs:subClassOf y . a rdf:type y .

a rdf:type x .

x rdfs:subClassOf y . x rdfs:subClassOf z .

y rdfs:subClassOf z .

x a y . x b y .

a rdfs:subPropertyOf b .

a rdfs:subPropertyOf b . a rdfs:subPropertyOf c .

b rdfs:subPropertyOf c .

x a y . x rdf:type z .

a rdfs:domain z .

x a u . u rdf:type z .

a rdfs:range z .

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Read out more in RDF Semantics http://www.w3.org/TR/rdf-mt/

I-1 First Order Calculus and RDF semantics

RDFS inference rules are valid deductionhypothesis Conclusionp rdfs:subClassOf q . a rdf:type q .a rdf:type p .

In FOLx [ P(x) Q(x)],P(A) Q(A)

We can demonstate that it is a valid deduction using First Order Calculus1. 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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I-1Without Inference

A recipient, that only understands XML syntax, receiving

<RDF> <Description about="Rodin"> <sculpts resource="TheKiss"/> </Description></RDF>

can answer the following queries What does Rodin sculpt?RDF/Description[@about='Rodin']/sculpts/@resource Who does sculpt TheKiss?RDF/Description[sculpts/@resource='TheKiss']/@about 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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I-1Knowing the ontology and RDF semantics …

A recipient, that knows the ontology and “understands” RDF semantics,

Receiving Rodin sculpts TheKiss .

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Artist Piece

Painter Paint

paints

Sculptor Sculpt

sculpts

creates

Rodin TheKiss

I-1… a reasoner can answer 1/2

the previous queries What does Rodin sculpt?

PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>PREFIX ex: <http://www.ex.org/schema#>SELECT ?xWHERE { ex:Rodin ex:sculpts ?x }?x = ex:TheKiss

Who does sculpt TheKiss?WHERE { ex:Rodin ex:sculpts ?x }?x = ex:Rodin

and it can also answer Who is Rodin?

WHERE { ex:Rodin a ?x }?x = ex:Artist, ex:Sculptor, rdfs:Resource

What is TheKiss?WHERE { ex:TheKiss a ?x }?x = ex:Sclupt, ex:Piece, rdfs:Resource

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I-1… a reasoner can answer 2/2

Is there any Sculptor?WHERE { ?x a ex:Sculptor}?x = ex:Rodin

Is the any Artist?WHERE { ?x a ex:Artist }?x = ex:Rodin

Is there any Sculpt?WHERE { ?x a ex:Sculpt }?x = ex:TheKiss

Is there any Piece?WHERE { ?x a ex:Piece }?x = ex:TheKiss

Is there any Paint?WHERE { ?x a ex:Paint }0 results

Is there any Painter?WHERE { ?x a ex:Painter }0 results

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I-1SPARQL vs Reasoner

SPARQL alone cannot answer queries that require reasoning

but a reasoner can be exposed as a SPARQL service.

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RDFSPARQLservice

ReasonerRDFSPARQLservice

I-1More 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

property:if A sclupts B then B isSculptedBy A

x y [Sculpts(x,y) IsSculptedBy(y,x) ]

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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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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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I-1Expressivity 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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I-1OWL 2 profiles

OWL 1 defines only one fragment (OWL Lite) And it isn’t 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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I-1OWL 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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I-1OWL 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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I-1OWL 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., Oracle’s 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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I-1Application

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I-1Light weight semantic mark-up

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/4106

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<div id="event-info-where" class="info-wh-info vcard"> <h2><a rel="bookmark" class="fn org location" href="/venues/V0-001-000693919-2"> Circus Krone Munich</a></h2> <div class="adr"> <span class="street-address">1</span><br> <span class="locality">Munich</span>, <span class="region">Bayern</span> <br> <span class="country-name">Germany</span>

I-1Linking Open Data Project

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

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Visit http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData !

Project Chartres

• RDFizers and ConverterToRdf

• Publishing Tools

• Semantic Web Browsers and Client Libraries

• Semantic Web Search Engines

• Applications

• […]

I-1Navigating 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: It’s meant for machine consumption!

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I-1The 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/archives/10_semantic_apps_to_watch.php

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I-1Esempi di applicazioni

Allen Brain Atlas Gene Expression Results http://sw.neurocommons.org/hcls_gene_image.html

SWEO’s use case collection http://www.w3.org/2001/sw/sweo/public/UseCases/

Linking Open Data Project http://esw.w3.org/topic/SweoIG/TaskForces/

CommunityProjects/LinkingOpenData

Music Event Explorer http://meex.cefriel.it/meex/

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I-1Music Event Explorer

Esigenza: dove posso andare a sentire musica folk nei prossimi giorni?

Soluzione manuale:1. Vado su musicmoz e scopro i cantanti che fanno

musica folk2. Vado su musicbrainz e guardo quali album hanno

pubblicato 3. Per ciascuno di quelli che mi piace cerco su EVDB

se ci ha organizzato eventi nei prossimi giorni4. Mi appunto i posti e poi li cerco in GoogleMaps

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I-1Soluzione manuale

1. Vado su musicmoz e scopro i cantanti che fanno musica folk

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2. Vado su musicbrainz e guardo quali album hanno pubblicato

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

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

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I-1Music Event Explorer

Una soluzione poco praticabile …

… ma automatizzabile

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I-1http://meex.cefriel.it/meex

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1. Semantic Web Modellare e Condividere per Innovare

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