Curso de verano upm'2010 web2.0, web semántica y la web de datos

iSOCO

Linked Data: ¿una oportunidad o un riesgo?
Web2.0, Web Semántica y la Web de los Datos

Curso de Verano UPM. Julio, 2010
Carlos Ruiz Moreno

2 Carlos Ruiz Moreno

Introducción

“Nuestra misión es transformar la investigación sobre
las nuevas tecnologías en innovación y valor para
nuestros clientes y la sociedad”

ALGUNOS DATOS SEDES

 iSOCO nace en 1999 como una spin-
off del CSIC en el campus de la UAB
Pamplona
 Facturación 2008: ~6 MM € T. +34 948 102 408
 Equipo humano: 85 personas (86% Parque Tomás Caballero, 2, 6º-4ª
31006 Pamplona
licenciados superiores)
 Accionariado:
- BCN Emprèn
- BtoB Factory
- Invernova
Barcelona
- Accionistas particulares T. +34 93 5677200
Madrid C/ Alcalde Barnils 64-68
 Departamentos: T. +34 91 3349797 08190 St. Cugat del Vallès
- innovationLAB (I+D) C/Pedro de Valdivia, 10
28006 Madrid Valencia
- Intelligent Content Management T. +34 96 3467143
- Sourcing Transformation C/ Prof. Beltrán Báguena 4,
46009 Valencia


Evolution of the Web
Today, Now!

Semántica

Web
Web 2.0 Servicios


Agenda

Evolution of The Web
Semantic Web
Linked Data

6

The beginning: Web 1.0

WWW
HTTP
URI

Tim Berners-Lee, 1989-90


Web 2.0. Motivation

Más de 30 mil
millones de
páginas

Más de 1000 millones
de usuarios
 Requisitos
- Cooperación
- Dinamicidad
- Cambio descentralizado
- Interoperable
- Multimedia

WWW
Static URI, HTML, HTTP


Web 2.0. Motivation

Taken from:
http://web2.socialcomputingjournal.com/all_we_got_was_web_10_when_tim_bernerslee_actually_gave_us_w.htm

Web 2.0

 Tim O‟Reilly: “Web 2.0 is the business revolution in the
computer industry caused by the move to the internet as
platform, and an attempt to understand the rules for
success on that new platform. Chief among those rules is
this: Build applications that harness network effects to get
better the more people use them. ”.
Source: http://radar.oreilly.com/archives/2006/12/web_20_compact.html

 Web 2.0 comprises terms like web services, social
networks, wikis, folksonomies, mash-ups, and
syndication.


Web 2.0. Folksonomies

 Folksonomy: classification from collaboratively creating and
managing tags to annotate and categorize content
 Collaborative tagging, social classification, social tagging


Web 2.0. Web Services. Flickr


Web 2.0. Web Services. Del.icio.us


Web 2.0. Social Networks. Facebook


Web 2.0. Wikis


Web 2.0. Mask-ups
http://www.wikicrimes.org


Web 2.0. Social Networks. Folksonomies


Web 2.0. Syndication


Web 1.0 vs. Web 2.0. Comparison

 DoubleClick  Google AdSense
 Ofoto  Flickr
 mp3.com  Napster
 Britannica Online  Wikipedia
 personal websites  blogging
 domain name speculation  search engine optimization
 page views  cost per clicks
 screen scraping  web services
 publishing  participation
 content management systems  wikis
 directories (taxonomy)  tagging ("folksonomy")


Semantic Web. Motivation



 The current Web is based
on HTML, which specifies
how to layout a web page
for human readers
 Software has to “guess” all
the semantics
 A lot of reading and
navigation before we find
the right answer for many
types of queries

<td class="arial16bold">Bodas de sangre</td>
<td width="16" align="right" valign="top"><img
src="images/icono_libros_libros.gif" width="16" height="15"></td>
<td nowrap class="arial11" valign="bottom">Precio editor: 5,70 <img
src='/images/icons/euro.gif' width='9' height='10'> | 948 pts </td>



Expression
Author
Title

Book

Cultural Ontology

<Product>
<Book>
<Author>Federico García Lorca</Author> Product
<Title>Bodas de sangre</Title>
</ Book> Price
Invoice
<Price> Currency
<Currency>Euro</currency>
Value
<Value>5,42</value>
</Price> eCommerce
</Product> Ontology


Semantic Web. Definition

The Semantic Web is an extension of the current web in which
information is given well-defined meaning, better enabling
computers and people to work in cooperation.
[Tim Berners-Lee, James Hendler, Ora Lassila, Scientific American, May 2001].

Tim Berners-Lee has a vision of a semantic web which
 has machine-understandable semantics of information, and
 trillions of small specialized reasoning services that provide
support in automated task achievement based on the
accessible information.


Web 3.0
Pillars

Collaboration Knowledge

Ubiquity


Web 1.0, Web 2.0 and Web 3.0


The Web of Data

 How do we look up about things?

 Nowadays:
- Web of Documents (HTML and hyperlinks)
- Intended for humans
- Stored in silos.
 Web of Data: Each particular data can be
- published
- re-used
- and shared


The Web of Data. Linked Data

 One promising approach is through Linked Data paradigm
 Pillars:
- Semantic Web: Standards for
• Ontologies and vocabularies [meaning]

• For machine-readable representation [interoperability]

• Query and inference engines [reasoning]

- WWW design principles:
• Simplicity

• Open and tested protocols

• Modular design, and

• Decentralization.

- Principles of Linked Data


Agenda

Semantic Web
Linked Data

32

Semantic Web
Introduction

<tr><td class="arial16bold">
Poeta en Nueva York
</td></tr>
<tr><td class="arial12normal">
<a href='http://www.fnac.es/dsp/?servlet=actor.HomeActorServlet&
Code1=224517047&Code2='class='arial12normal'>
Federico García Lorca
</a>
</td></tr><tr><td><img src="images/pixelin.gif" width="274" height="8"></td></tr>

<co:Product><co:Book>
<co:Title>Poeta en Nueva York</co:Title>
<co:Publisher>Cátedra</co:Publisher>
<co:Price>
<co:amount currency=”Eu”>5,42</co:amount>
<co:amount currency=”Pts”>902</co:amount>
<co:discount>5</co:discount>
</co:Price></co:Book></co:Product>


Semantic Web. Key Components

 Ontologies
 Semantic Web languages:
- RDF
- OWL
 Query languages
- SPARQL
 Semantics into web pages:
- RDFa
- Microformats
 Other important aspects:
- Storage – triple stores.
- Reasoning
- Visualisation
- Multilingualism


Semantic Web
Ontology. What is it?
Some definitions

 An ontology may take various forms, but necessarily it will
include a vocabulary of terms, and some specification of their
meaning (Uschold, Jaspers & Uschold)
 A body of knowledge describing some common sense domain
(CYC project)
 An ontology is a formal, explicit specification of a shared
conceptualization (Gruber)


Semantic Web
Ontology. What is it?

“An ontology is a formal, explicit specification of a shared conceptualization”

Machine-readable
Consensual
Knowledge

Concepts, properties
relations, functions, Abstract model of some
constraints, axioms, phenomenon in the world
are explicitly defined


Semantic Web
Ontology. What is inside it?

Common components of ontologies are:
 Classes/Concepts (and class-hierarchy)
 Individuals/Instances
 Slots/ Attributes
 Relations: ways in which classes and individuals can be related
to one another
 Restrictions on slots (type, cardinality): formally stated
descriptions of what must be true in order for some assertion to
be accepted as input
 Axioms: assertions (including rules) in a logical form that
together comprise the overall theory that the ontology describes
in its domain of application.

Semantic Web
Ontology. Examples

 Upper ontologies / Foundational ontologies
- Dublin Core: a simple ontology for documents and publishing
- DOLCE: a Descriptive Ont. for Linguistic and Cognitive Engineering
- WordNet: a lexical reference system
- Cyc: a large Foundation Ontology for formal representation of the
universe of discourse.
 General purpose ontologies
- FOAF: an ontology for describing people, their activities and relations
- SIOC: an ontology for describing online communities
 Domain ontologies


Semantic Web
Semantic Web Stack

URI: Uniform Resource Identification
XML: Surface syntax, no semantics
XML Schema: Describes structure of XML
documents
RDF: Data model for describing “relations”
between “things”
RDF Schema: RDF Vocabulary Definition
Language
OWL: A more expressive
Vocabulary Definition Language


Semantic Web
Ontology Languages. RDF Introduction

 Resource Description Framework –RDF-
 A general method for conceptual description or modeling of
information that is implemented in web resources
 RDF Triple: Subject - Predicate-Object statement
• “The sky has the colour blue”
- Subject [object]: “the sky”
- Predicate [relationship]: “has the colour”
- Object [value]: “blue”
 It represents a labeled, directed multi graph
 Serializations formats:
 RDF/XML Carlos_Ruiz a foaf:Person.
Carlos_Ruiz foaf:name “Carlos”
 N3, Turtle, N-Triples

Semantic Web
Ontology Languages. RDF. Example I

 A Wikipedia article about Tony Benn
Subject Predicate Object
<http://en.wikipedia.org/wiki/Tony_Benn> <http://purl.org/dc/elements/1.1/title> "Tony Benn" -

. "Wikipedia" .
<http://en.wikipedia.org/wiki/Tony_Benn> <http://purl.org/dc/elements/1.1/publisher>

N-Triples


Semantic Web
Ontology Languages. RDF. Example I

 A Wikipedia article about Tony Benn

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-
ns#" xmlns:dc="http://purl.org/dc/elements/1.1/">
<rdf:Description rdf:about="http://en.wikipedia.org/Tony_Benn">
<dc:title>Tony Benn</dc:title>
<dc:publisher>Wikipedia</dc:publisher>
</rdf:Description>
</rdf:RDF>

RDF/XML


Semantic Web
Ontology Languages. RDF. Example II

 RDF Description of a person named Eric Miller

URI – Uniform Resource Identifier

RDF Graph


Semantic Web
Ontology Languages. RDF. Example II

 RDF Description of a person named Eric Miller
Subject Predicate Object
http://www.w3.org/People/EM/contac http://www.w3.org/2000/10/swap/pim/contact
"Eric Miller"
t#me #fullName

"Dr."
t#me #personalTitle

http://www.w3.org/
http://www.w3.org/People/EM/contac http://www.w3.org/1999/02/22-rdf-syntax- 2000/10/swap/pim
t#me ns#type /contact#Person

em@w3.org
t#me #mailbox

N-Triples


Semantic Web
Ontology Languages. OWL

 OWL – Web Ontology Language
- a family of knowledge representation languages for authoring ontologies
endorsed by the WWW
- characterized by:
• formal semantics (DL and semantic extension of RDF) and
• RDF/XML-based serializations for the Semantic Web
- OWL 2.0, Oct. 2009.
 OWL comes with:
 Larger vocabulary and
 Stronger syntax that RDF


Semantic Web
SPARQL – SPARQL Protocol and RDF Query Language

 RDF query language
 Allows for a query to consist of:
- Triple patterns subject-predicate-object
- Conjunctions
- Disjunction
- Optional patterns

http://en.wikipedia.org/wiki/SPARQL

Semantic Web
SPARQL – SPARQL Protocol and RDF Query Language

What are all the country capitals in Africa?

http://en.wikipedia.org/wiki/SPARQL


Semantic Web
RDFa

 RDFa - Resource Description Framework in attributes:
- A set of attribute level extensions to XHTML for embedding
rich metadata within Web documents
• embedding RDF triples within XHTML documents
• enabling the extraction of RDF model triples by compliant
user agents.


Semantic Web
RDFa + XHTML. Example

http://en.wikipedia.org/wiki/RDFa


Semantic Web
RDF/XML. Example

http://en.wikipedia.org/wiki/RDFa


Semantic Web
Microformats

 Why:
- Traditional markup tags used to display information on the web
do not describe what the information means.
- Avoid complicated methods: screen scraping, NLP
 What:
- A web-based approach to semantic mark-up
- Re-use existing (X)HTML tags to convey metadata
 Examples (see microformats.org):
- Contact information – hCard
- Calendar events – hCalendar
- Revisiones - hReview


Semantic Web
Microformats. Example hCard


Semantic Web
Microformats. Example II


Semantic Web
Semantic Web Services. Extending the Semantic Web

• 500 million users more than 3 billion pages

Static
WWW
URI, HTML, HTTP


Semantic Web

• Serious Problems in
- information finding,
- information extracting,
- information representing,
- information interpreting and
- information maintaining.

Static
WWW Semantic Web
URI, HTML, HTTP RDF, RDF(S), OWL


Semantic Web

• Bringing the computer back
as a device for computation

Dynamic Web Services
UDDI, WSDL, SOAP

Static
WWW Semantic Web


Semantic Web

• Bringing the web to its full potential

Web Services Intelligent Web
Dynamic
UDDI, WSDL, SOAP Services

Static
WWW Semantic Web


Semantic Web
Semantic Search Engines

Keyword-based search engines

 Need a lot of reading and navigation
- Low relevancy
- Depends on vocabulary

 Problem: current search technologies
do not understand what you are
looking for
- The only look for keywords

 Problem: popular-based analytics
- The „Deep‟ web is not
considered
- No retrieval of „implicit
knowledge‟


Semantic Web

 Benefits:
Semantic search engines - Based on the meaning
- Integrates multiple sources

 Technologies:
- Semantic Web [Ontologies]
- Natural Language
- Reasoning

 Examples:
- Hakia
- Kngine


Semantic Web


Semantic Web
Semantic Search Engines. Hakia


Semantic Web
Examples. Revyu.com


Semantic Web
adoption. Rich Snippets
http://googlewebmastercentral.blogspot.com/2009/0
5/introducing-rich-snippets.html

Simple Markup

Microformats markup

RDFa markup


Semantic Web
RDFa adoption. Others
Best Buy – RDFa + GoogRelations eCommerce ontology

Yahoo! - RDFa + SearchMonkey


Agenda

Semantic Web
Linked Data

67

Linked Data
Motivation

Why?
 Expose data on the Web, not just documents
 Interlink these data with those of other data sources
 Not silos of information anymore!

Other applications and humans:
 Easily access your data using Web tech.
 Follow the links in order to obtain further contextual
information
 Links to your data and search engine indices can increase
the visibility of your data


Linked Data
Principles

 The Four rules (Berners-Lee, 2007):
1. Use URIs as names for things
2. Use HTTP URIs so that people can look up those names
3. When someone looks up a URI, provide useful information, using
the standards (RDF*, SPARQL)
4. Include links to other URIs. so that they can discover more things.


Linked Data
Open Linking Data

Community effort to
 publish existing open license datasets as Linked Data on
the Web
 interlink things between different data sources
 develop clients that consume Linked Data from the Web


Linked Data
Open Linking Data. Data sets

May, 2007
Over 500 million RDF triples
Around 120,000 RDF links between data sources


Linked Data

Currently:
13.1 billion RDF triples
Interlinked by around 142 million RDF links


Linked Data


Linked Data
Data flow. Publication & Tools

voID
R2O y ODEMapster RDQuery
data.dcs Silk
D2R Server Triplr
Triplify Linked Data API
Openlink Virtuoso Pubby
Vapour


Linked Data
Data flow. Consume & Tools

opm: Open Provenance Model
provenir: Provenir ontology
prv: Provenance Vocabulary
pml:Proof Markup Language
dc: Dublin Core
cs: Changeset Vocabulary

RelBrowser
Tabulator
Zitgist DataViewer
Disco
marbles
RelFinder
LENA
Sheaflight
VisNav


Linked Data
Applications. Dbpedia

http://dbpedia.org/sparql


Linked Data
Applications. Sig.ma
http://sig.ma.com


Linked Data
Applications. NYT I
http://data.nytimes.com/


Linked Data
Applications. NYT II
http://data.nytimes.com/60694995023816375851.html


Linked Data
Applications. NYT III


Linked Data
Open Government. Motivation

 Government and state administration should be opened at
all levels to effective public scrutiny and oversight
 Objectives:
- Transparency
- Participation
- Collaboration
- Inclusion
 Cost reduction Some Links:
 B. Obama – Transparency and Open
- Interoperability
Government
- Reusability  T. Berners-Lee - Raw data now!
 Leadership  J. Manuel Alonso - ¿Qué es Open Data?
 Open Government Data
- Market & Value
 8 Principles of Open Government Data

Linked Data
Open Government. EEUU and UK


Linked Data
Open Government. Applications. Data.uk.gov

Research Funding Explorer – data.co.gov


Linked Data
Open Government. Applications. Data.gov

Clean Status and Trends Network (CASTNET)


Linked Data
Open Government. Applications. Australia
http://www.suburbantrends.com.au/


Linked Data
Open Government. What about Spain?


Linked Data


Linked Data
Open Government. AELID

www.aelid.es
- Fundada por miembros de iSOCO y UPM-OEG (Marzo, 2010)
- Objetivos:
• Actuar como punto de encuentro de la comunidad española.
• Organización y participación en eventos de diseminación, campañas
de concienciación
• Retos para estimular el desarrollo de la tecnología y aplicaciones
Linked Data
• Promoción de la investigación científica de alta calidad e innovación
tecnológica, de acuerdo con los estándares de excelencia y mejores
prácticas.
• Establecimiento de relaciones con entidades públicas y privadas
europeas.

Gracias
Preguntas - Discusión

iSOCO

Web2.0, Web Semántica y la Web de los Datos

Carlos Ruiz Moreno

Curso de verano upm'2010 web2.0, web semántica y la web de datos

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