SlideShare uma empresa Scribd logo
1 de 23
Baixar para ler offline
The Semantic Web
a short guide
	
  
Maciej	
  Dabrowski	
  
macdab@gmail.com	
  
THE SEMANTIC WEB
WHAT ISTHE GOAL?	

WHAT ARETHE BUILDING BLOCKS?	

HOW DO WE CREATETHE GRAPH?
WHY LINKED DATA?	

SHORT INTROTO ONTOLOGIES
What’s in a page ? And in a link ?
?	
  
?	
  
?	
  
VISION FOR THE WEB
TIM BERNERS-LEE,THE 1ST WORLD WIDE WEB
CONFERENCE, GENEVA, MAY 1994:	

	

DESCRIBE DOCUMENTS IN MACHINE READIBLE FORM	

CREATE MEANINGFUL LINKS (“RELATIONSHIPVALUES”)	

	

“ONLY WHEN WE HAVETHIS EXTRA LEVEL OF SEMANTICS
WILL WE BE ABLETO USE COMPUTER POWERTO HELP
US EXPLOITTHE INFORMATIONTO A GREATER EXTENT
THAN OUR OWN READING.”
Aims of the Semantic Web
BRIDGINGTHE GAP BETWEEN A WEB OF
DOCUMENTSTO A WEB OF DATA,WITH
TYPED OBJECTS ANDTYPED RELATIONSHIPS	

	

ADDING MACHINE-READABLE METADATA
TO EXISTING CONTENT, SOTHAT
INFORMATION CAN BE PARSED, QUERIED,
REUSED
Aims of the Semantic Web
DEFINING SHARED SEMANTICS FORTHIS
METADATATO ALLOW INTEROPERABILITY
BETWEEN APPLICATIONS AND FOR
ADVANCED PURPOSES, SUCH AS REASONING	

	

ENABLING MACHINE-READABLE KNOWLEDGE
AT WEB SCALE, MAKING INFORMATION MORE
EASYTO FIND AND PROCESS
The Semantic Web, circa 2010
MOST STANDARDISATION WORK IS DONE IN
THE W3C:	

HTTP://WWW.W3.ORG/	

	

INCUBATOR GROUPS,WORKING GROUP,
INTEREST GROUPS:	

WGS FOR SPARQL, RDB2RDF, RIF, ETC.	

HCLS IG, SOCIAL WEB XG, ETC.
Name everything
Identifying resources with URIs
URIS ARE USEDTO IDENTIFY EVERYTHING IN A
UNIQUE AND NON-AMBIGUOUS WAY	

NOT ONLY PAGES (AS ONTHE CURRENT WEB),
BUT ANY RESOURCE (PEOPLE, DOCUMENTS,
BOOKS, INTERESTS, ETC.)	

A URI FOR A PERSON IS DIFFERENT FROM A URI
FOR A DOCUMENT ABOUTTHE PERSON,
BECAUSE A PERSON IS NOT A DOCUMENT!	

e.g. http://deri.ie/user/maciej-dabrowski	

e.g. http://deri.ie/content/modelling-preference-relaxation-e-commerce
Defining assertions with RDF
•  URIS IDENTIFY RESOURCES:	

•  WE USE RDF (RESOURCE DESCRIPTION
FRAMEWORK)TO DEFINE ASSERTIONS
ABOUTTHESE RESOURCES	

•  RDF IS A DATA MODEL;A DIRECTED, LABELED
GRAPH USING URIS	

•  RDF IS BASED ONTRIPLES:	

– <SUBJECT> <PREDICATE> <OBJECT>.!
Simple triples
Maciej
Dabrowski
MDabrowski-lecture3
author
Semantic_Web
Introduction to the
Semantic Web
title
subject
Use Uris
http://example.org/maciej-dabrowski
http://example.org/MDabrowski-lecture3
http://example.org/author
http://example.org/Semantic_Web
Introduction to the
Semantic Web
http://example.org/title
http://example.org/subject
Abbreviating uris
PREFIX ex: http://example.org/#	

ex:maciej = <http://example.org/#maciej>	

	

ex:maciej-dabrowski
ex:MDabrowski-lecture3
ex:author
ex:Semantic_Web
Introduction to the
Semantic Web
ex:title
ex:subject
Reuse existing vocabularies
PREFIX dct: http://purl.org/dc/terms/	

http://deri.ie/user/maciej-dabrowski
http://example.org/MDabrowski-lecture3
dct:creator
http://dbpedia.org/resource/Semantic_Web
Introduction to the
Semantic Web
dct:title
dct:subject
RDF by example
!
!
@prefix dct: <http://purl.org/dc/terms/> . !
<http://example.org/dm110-semweb>!
!dct:title “Introduction to the Semantic Web” ; !
!dct:author <http://www.deri.ie/users/maciej-dabrowski> ; !!
!dct:subject <http://dbpedia.org/resource/Semantic_Web> .!
RDFA
A WAY OF EMBEDDING RDF IN (X)HTML
DOCUMENTS:	

ONE PAGE FOR BOTH HUMANS AND
MACHINES	

DON’T NEEDTO REPEATYOURSELF	

INTRODUCING NEW XHTML ATTRIBUTES	

CURRENT WORK IS ONGOING ON RDFa 1.1:	

FOR PROFILES, ETC.
RDFa example
Triples are everywhere!
10/06/2013	
  
SUBJECT	
  
PREDICATE	
  
OBJECT	
  
PREDICATE	
  
OBJECT	
  
OBJECT	
  
…	
  
Defining semantics with ontologies
•  RDF PROVIDES A WAYTO WRITE ASSERTIONS
ABOUT URIS	

•  WHAT ABOUTTHE SEMANTICS OFTHESE
ASSERTIONS, E.G.TO STATETHAT HTTP://
XMLNS.COM/FOAF/0.1/KNOWS IDENTIFIES AN
ACQUAINTANCE RELATIONSHIP?	

•  ONTOLOGIES PROVIDE COMMON
SEMANTICS FOR RESOURCES ONTHE
SEMANTIC WEB
Ontologies consist mainly of classes and
properties
– :Person a rdfs:Class .!
– :father a rdfs:Property .!
– :father rdfs:domain :Person .!
– :father rdfs:range :Person .!
:Maciej
:Mark
:father
:Person
a
:Person
a
Notable ontologies
SOCIAL NETWORKS AND SOCIAL DATA: 	

FOAF, SIOC	

	

TAXONOMIES AND CONTROLLED
VOCABULARIES: 	

SKOS, MOAT
Linked Data

Mais conteúdo relacionado

Mais procurados

Digital Tools for Academic Research
Digital Tools for Academic ResearchDigital Tools for Academic Research
Digital Tools for Academic Researchorganognosi
 
Semantic Search with Semantic Web
Semantic Search with Semantic WebSemantic Search with Semantic Web
Semantic Search with Semantic WebZahra Sadeghi
 
Building a semantic website
Building a semantic websiteBuilding a semantic website
Building a semantic websiteCJ Jenkins
 
Webinar: Semantic web for developers
Webinar: Semantic web for developersWebinar: Semantic web for developers
Webinar: Semantic web for developersSemantic Web Company
 
It19 20140721 linked data personal perspective
It19 20140721 linked data personal perspectiveIt19 20140721 linked data personal perspective
It19 20140721 linked data personal perspectiveJanifer Gatenby
 
Intro to Semantic Web
Intro to Semantic WebIntro to Semantic Web
Intro to Semantic WebTimea Turdean
 
RDFa Introductory Course Session 3/4 Why RDFa
RDFa Introductory Course Session 3/4 Why RDFaRDFa Introductory Course Session 3/4 Why RDFa
RDFa Introductory Course Session 3/4 Why RDFaPlatypus
 
Jarrar: The Next Generation of the Web 3.0: The Semantic Web
Jarrar: The Next Generation of the Web 3.0: The Semantic WebJarrar: The Next Generation of the Web 3.0: The Semantic Web
Jarrar: The Next Generation of the Web 3.0: The Semantic WebMustafa Jarrar
 
RDFa Introductory Course Session 2/4 How RDFa
RDFa Introductory Course Session 2/4 How RDFaRDFa Introductory Course Session 2/4 How RDFa
RDFa Introductory Course Session 2/4 How RDFaPlatypus
 
An Introduction to Semantic Web Technology
An Introduction to Semantic Web TechnologyAn Introduction to Semantic Web Technology
An Introduction to Semantic Web TechnologyAnkur Biswas
 
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 TutorialRealizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 TutorialEmanuele Della Valle
 
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategy
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategyMaximising Online Resource Effectiveness Workshop Session 5/8 Content strategy
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategyPlatypus
 
Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data TutorialSören Auer
 
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issues
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issuesMaximising Online Resource Effectiveness Workshop Session 3/8 Priority issues
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issuesPlatypus
 
Semantic Mapping and LOD prez
Semantic Mapping and LOD prezSemantic Mapping and LOD prez
Semantic Mapping and LOD prezCarol Chiodo
 
RDA: Are We There Yet? Carterette Webinar S
RDA: Are We There Yet? Carterette Webinar SRDA: Are We There Yet? Carterette Webinar S
RDA: Are We There Yet? Carterette Webinar SEmily Nimsakont
 
San Diego Meetup - Sem Web Overview - 2009.04.27
San Diego Meetup - Sem Web Overview - 2009.04.27San Diego Meetup - Sem Web Overview - 2009.04.27
San Diego Meetup - Sem Web Overview - 2009.04.27Eric Franzon
 

Mais procurados (20)

Digital Tools for Academic Research
Digital Tools for Academic ResearchDigital Tools for Academic Research
Digital Tools for Academic Research
 
Semantic Search with Semantic Web
Semantic Search with Semantic WebSemantic Search with Semantic Web
Semantic Search with Semantic Web
 
Quick Introduction to the Semantic Web, RDFa & Microformats
Quick Introduction to the Semantic Web, RDFa & MicroformatsQuick Introduction to the Semantic Web, RDFa & Microformats
Quick Introduction to the Semantic Web, RDFa & Microformats
 
Building a semantic website
Building a semantic websiteBuilding a semantic website
Building a semantic website
 
Linked data 20171106
Linked data 20171106Linked data 20171106
Linked data 20171106
 
Webinar: Semantic web for developers
Webinar: Semantic web for developersWebinar: Semantic web for developers
Webinar: Semantic web for developers
 
It19 20140721 linked data personal perspective
It19 20140721 linked data personal perspectiveIt19 20140721 linked data personal perspective
It19 20140721 linked data personal perspective
 
Linked Data
Linked DataLinked Data
Linked Data
 
Intro to Semantic Web
Intro to Semantic WebIntro to Semantic Web
Intro to Semantic Web
 
RDFa Introductory Course Session 3/4 Why RDFa
RDFa Introductory Course Session 3/4 Why RDFaRDFa Introductory Course Session 3/4 Why RDFa
RDFa Introductory Course Session 3/4 Why RDFa
 
Jarrar: The Next Generation of the Web 3.0: The Semantic Web
Jarrar: The Next Generation of the Web 3.0: The Semantic WebJarrar: The Next Generation of the Web 3.0: The Semantic Web
Jarrar: The Next Generation of the Web 3.0: The Semantic Web
 
RDFa Introductory Course Session 2/4 How RDFa
RDFa Introductory Course Session 2/4 How RDFaRDFa Introductory Course Session 2/4 How RDFa
RDFa Introductory Course Session 2/4 How RDFa
 
An Introduction to Semantic Web Technology
An Introduction to Semantic Web TechnologyAn Introduction to Semantic Web Technology
An Introduction to Semantic Web Technology
 
Realizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 TutorialRealizing a Semantic Web Application - ICWE 2010 Tutorial
Realizing a Semantic Web Application - ICWE 2010 Tutorial
 
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategy
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategyMaximising Online Resource Effectiveness Workshop Session 5/8 Content strategy
Maximising Online Resource Effectiveness Workshop Session 5/8 Content strategy
 
Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data Tutorial
 
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issues
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issuesMaximising Online Resource Effectiveness Workshop Session 3/8 Priority issues
Maximising Online Resource Effectiveness Workshop Session 3/8 Priority issues
 
Semantic Mapping and LOD prez
Semantic Mapping and LOD prezSemantic Mapping and LOD prez
Semantic Mapping and LOD prez
 
RDA: Are We There Yet? Carterette Webinar S
RDA: Are We There Yet? Carterette Webinar SRDA: Are We There Yet? Carterette Webinar S
RDA: Are We There Yet? Carterette Webinar S
 
San Diego Meetup - Sem Web Overview - 2009.04.27
San Diego Meetup - Sem Web Overview - 2009.04.27San Diego Meetup - Sem Web Overview - 2009.04.27
San Diego Meetup - Sem Web Overview - 2009.04.27
 

Destaque

Chapter 12 power point presentation2
Chapter 12 power point presentation2Chapter 12 power point presentation2
Chapter 12 power point presentation2Angela49938
 
The true meaning of data
The true meaning of dataThe true meaning of data
The true meaning of datamdabrowski
 
Introduction to the Social Semantic Web
Introduction to the Social Semantic WebIntroduction to the Social Semantic Web
Introduction to the Social Semantic Webmdabrowski
 
Contabilizacion final para subir
Contabilizacion final para subirContabilizacion final para subir
Contabilizacion final para subirLesly_12
 
Introduction to the Social Web and its applications
Introduction to the Social Web and its applicationsIntroduction to the Social Web and its applications
Introduction to the Social Web and its applicationsmdabrowski
 
Geo-annotations in Semantic Digital Libraries
Geo-annotations in Semantic Digital Libraries Geo-annotations in Semantic Digital Libraries
Geo-annotations in Semantic Digital Libraries mdabrowski
 
Near real-time recommendations in enterprise social networks
Near real-time recommendations in enterprise social networksNear real-time recommendations in enterprise social networks
Near real-time recommendations in enterprise social networksmdabrowski
 

Destaque (10)

nobela_negra
nobela_negranobela_negra
nobela_negra
 
Chapter 12 power point presentation2
Chapter 12 power point presentation2Chapter 12 power point presentation2
Chapter 12 power point presentation2
 
The true meaning of data
The true meaning of dataThe true meaning of data
The true meaning of data
 
Introduction to the Social Semantic Web
Introduction to the Social Semantic WebIntroduction to the Social Semantic Web
Introduction to the Social Semantic Web
 
Contabilizacion final para subir
Contabilizacion final para subirContabilizacion final para subir
Contabilizacion final para subir
 
Ntp 576
Ntp 576Ntp 576
Ntp 576
 
Introduction to the Social Web and its applications
Introduction to the Social Web and its applicationsIntroduction to the Social Web and its applications
Introduction to the Social Web and its applications
 
China slides
China slidesChina slides
China slides
 
Geo-annotations in Semantic Digital Libraries
Geo-annotations in Semantic Digital Libraries Geo-annotations in Semantic Digital Libraries
Geo-annotations in Semantic Digital Libraries
 
Near real-time recommendations in enterprise social networks
Near real-time recommendations in enterprise social networksNear real-time recommendations in enterprise social networks
Near real-time recommendations in enterprise social networks
 

Semelhante a The Semantic Web: A Short Guide to Identifying Resources, Defining Assertions, and Providing Common Semantics

Semantic Web 2.0: Creating Social Semantic Information Spaces
Semantic Web 2.0: Creating Social Semantic Information SpacesSemantic Web 2.0: Creating Social Semantic Information Spaces
Semantic Web 2.0: Creating Social Semantic Information SpacesJohn Breslin
 
Corrib.org - OpenSource and Research
Corrib.org - OpenSource and ResearchCorrib.org - OpenSource and Research
Corrib.org - OpenSource and Researchadameq
 
Linked Data MLA 2015
Linked Data MLA 2015Linked Data MLA 2015
Linked Data MLA 2015Cason Snow
 
Linked data MLA 2015
Linked data MLA 2015Linked data MLA 2015
Linked data MLA 2015Cason Snow
 
Linked Data and Libraries: What? Why? How?
Linked Data and Libraries: What? Why? How?Linked Data and Libraries: What? Why? How?
Linked Data and Libraries: What? Why? How?Emily Nimsakont
 
Tutorial on Semantic Digital Libraries (ESWC'2007)
Tutorial on Semantic Digital Libraries (ESWC'2007)Tutorial on Semantic Digital Libraries (ESWC'2007)
Tutorial on Semantic Digital Libraries (ESWC'2007)Sebastian Ryszard Kruk
 
Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?Museums Computer Group
 
Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark GreavesMediabistro
 
WebGUI And The Semantic Web
WebGUI And The Semantic WebWebGUI And The Semantic Web
WebGUI And The Semantic WebWilliam McKee
 
Linked Data, Library Users, and the Discovery Tools of the Future
Linked Data, Library Users, and the Discovery Tools of the FutureLinked Data, Library Users, and the Discovery Tools of the Future
Linked Data, Library Users, and the Discovery Tools of the FutureEmily Nimsakont
 
Intelligent expert systems for location planning
Intelligent expert systems for location planningIntelligent expert systems for location planning
Intelligent expert systems for location planningNavid Milanizadeh
 
Semantic Web (Web 3.0)
Semantic Web (Web 3.0)Semantic Web (Web 3.0)
Semantic Web (Web 3.0)John Dougherty
 

Semelhante a The Semantic Web: A Short Guide to Identifying Resources, Defining Assertions, and Providing Common Semantics (20)

Lec1.pptx
Lec1.pptxLec1.pptx
Lec1.pptx
 
Semantic Web 2.0: Creating Social Semantic Information Spaces
Semantic Web 2.0: Creating Social Semantic Information SpacesSemantic Web 2.0: Creating Social Semantic Information Spaces
Semantic Web 2.0: Creating Social Semantic Information Spaces
 
Linked Data
Linked DataLinked Data
Linked Data
 
Linked data and voyager
Linked data and voyagerLinked data and voyager
Linked data and voyager
 
A theory of Metadata enriching & filtering
A theory of  Metadata enriching & filteringA theory of  Metadata enriching & filtering
A theory of Metadata enriching & filtering
 
Corrib.org - OpenSource and Research
Corrib.org - OpenSource and ResearchCorrib.org - OpenSource and Research
Corrib.org - OpenSource and Research
 
Linked Data MLA 2015
Linked Data MLA 2015Linked Data MLA 2015
Linked Data MLA 2015
 
Linked data MLA 2015
Linked data MLA 2015Linked data MLA 2015
Linked data MLA 2015
 
Digital Libraries of the Future
Digital Libraries of the Future
Digital Libraries of the Future
Digital Libraries of the Future
 
Semantic Web, e-commerce
Semantic Web, e-commerceSemantic Web, e-commerce
Semantic Web, e-commerce
 
Danbri Drupalcon Export
Danbri Drupalcon ExportDanbri Drupalcon Export
Danbri Drupalcon Export
 
Semantic Web and Linked Open Data
Semantic Web and Linked Open DataSemantic Web and Linked Open Data
Semantic Web and Linked Open Data
 
Linked Data and Libraries: What? Why? How?
Linked Data and Libraries: What? Why? How?Linked Data and Libraries: What? Why? How?
Linked Data and Libraries: What? Why? How?
 
Tutorial on Semantic Digital Libraries (ESWC'2007)
Tutorial on Semantic Digital Libraries (ESWC'2007)Tutorial on Semantic Digital Libraries (ESWC'2007)
Tutorial on Semantic Digital Libraries (ESWC'2007)
 
Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?Lee Iverson - How does the web connect content?
Lee Iverson - How does the web connect content?
 
Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark Greaves
 
WebGUI And The Semantic Web
WebGUI And The Semantic WebWebGUI And The Semantic Web
WebGUI And The Semantic Web
 
Linked Data, Library Users, and the Discovery Tools of the Future
Linked Data, Library Users, and the Discovery Tools of the FutureLinked Data, Library Users, and the Discovery Tools of the Future
Linked Data, Library Users, and the Discovery Tools of the Future
 
Intelligent expert systems for location planning
Intelligent expert systems for location planningIntelligent expert systems for location planning
Intelligent expert systems for location planning
 
Semantic Web (Web 3.0)
Semantic Web (Web 3.0)Semantic Web (Web 3.0)
Semantic Web (Web 3.0)
 

Mais de mdabrowski

Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...
Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...
Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...mdabrowski
 
2017 05 Hadoop User Group Meetup Dublin
2017 05 Hadoop User Group Meetup Dublin2017 05 Hadoop User Group Meetup Dublin
2017 05 Hadoop User Group Meetup Dublinmdabrowski
 
Applications of the Social Semantic Web
Applications of the Social Semantic WebApplications of the Social Semantic Web
Applications of the Social Semantic Webmdabrowski
 
MarcOnt Initiative - Protege meeting
MarcOnt Initiative - Protege meetingMarcOnt Initiative - Protege meeting
MarcOnt Initiative - Protege meetingmdabrowski
 
Philosophy and Atrificial Inteligence
Philosophy and Atrificial Inteligence Philosophy and Atrificial Inteligence
Philosophy and Atrificial Inteligence mdabrowski
 
MarcOnt Initiative
MarcOnt InitiativeMarcOnt Initiative
MarcOnt Initiativemdabrowski
 

Mais de mdabrowski (6)

Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...
Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...
Spark Summit Europe 2017 - Applying multiple ML pipelines to heterogenous dat...
 
2017 05 Hadoop User Group Meetup Dublin
2017 05 Hadoop User Group Meetup Dublin2017 05 Hadoop User Group Meetup Dublin
2017 05 Hadoop User Group Meetup Dublin
 
Applications of the Social Semantic Web
Applications of the Social Semantic WebApplications of the Social Semantic Web
Applications of the Social Semantic Web
 
MarcOnt Initiative - Protege meeting
MarcOnt Initiative - Protege meetingMarcOnt Initiative - Protege meeting
MarcOnt Initiative - Protege meeting
 
Philosophy and Atrificial Inteligence
Philosophy and Atrificial Inteligence Philosophy and Atrificial Inteligence
Philosophy and Atrificial Inteligence
 
MarcOnt Initiative
MarcOnt InitiativeMarcOnt Initiative
MarcOnt Initiative
 

Último

Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Disha Kariya
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxVishalSingh1417
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfJayanti Pande
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...fonyou31
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 

Último (20)

Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..Sports & Fitness Value Added Course FY..
Sports & Fitness Value Added Course FY..
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 

The Semantic Web: A Short Guide to Identifying Resources, Defining Assertions, and Providing Common Semantics

  • 1. The Semantic Web a short guide   Maciej  Dabrowski   macdab@gmail.com  
  • 2. THE SEMANTIC WEB WHAT ISTHE GOAL? WHAT ARETHE BUILDING BLOCKS? HOW DO WE CREATETHE GRAPH? WHY LINKED DATA? SHORT INTROTO ONTOLOGIES
  • 3. What’s in a page ? And in a link ? ?   ?   ?  
  • 4. VISION FOR THE WEB TIM BERNERS-LEE,THE 1ST WORLD WIDE WEB CONFERENCE, GENEVA, MAY 1994: DESCRIBE DOCUMENTS IN MACHINE READIBLE FORM CREATE MEANINGFUL LINKS (“RELATIONSHIPVALUES”) “ONLY WHEN WE HAVETHIS EXTRA LEVEL OF SEMANTICS WILL WE BE ABLETO USE COMPUTER POWERTO HELP US EXPLOITTHE INFORMATIONTO A GREATER EXTENT THAN OUR OWN READING.”
  • 5. Aims of the Semantic Web BRIDGINGTHE GAP BETWEEN A WEB OF DOCUMENTSTO A WEB OF DATA,WITH TYPED OBJECTS ANDTYPED RELATIONSHIPS ADDING MACHINE-READABLE METADATA TO EXISTING CONTENT, SOTHAT INFORMATION CAN BE PARSED, QUERIED, REUSED
  • 6. Aims of the Semantic Web DEFINING SHARED SEMANTICS FORTHIS METADATATO ALLOW INTEROPERABILITY BETWEEN APPLICATIONS AND FOR ADVANCED PURPOSES, SUCH AS REASONING ENABLING MACHINE-READABLE KNOWLEDGE AT WEB SCALE, MAKING INFORMATION MORE EASYTO FIND AND PROCESS
  • 7. The Semantic Web, circa 2010 MOST STANDARDISATION WORK IS DONE IN THE W3C: HTTP://WWW.W3.ORG/ INCUBATOR GROUPS,WORKING GROUP, INTEREST GROUPS: WGS FOR SPARQL, RDB2RDF, RIF, ETC. HCLS IG, SOCIAL WEB XG, ETC.
  • 9. Identifying resources with URIs URIS ARE USEDTO IDENTIFY EVERYTHING IN A UNIQUE AND NON-AMBIGUOUS WAY NOT ONLY PAGES (AS ONTHE CURRENT WEB), BUT ANY RESOURCE (PEOPLE, DOCUMENTS, BOOKS, INTERESTS, ETC.) A URI FOR A PERSON IS DIFFERENT FROM A URI FOR A DOCUMENT ABOUTTHE PERSON, BECAUSE A PERSON IS NOT A DOCUMENT! e.g. http://deri.ie/user/maciej-dabrowski e.g. http://deri.ie/content/modelling-preference-relaxation-e-commerce
  • 10. Defining assertions with RDF •  URIS IDENTIFY RESOURCES: •  WE USE RDF (RESOURCE DESCRIPTION FRAMEWORK)TO DEFINE ASSERTIONS ABOUTTHESE RESOURCES •  RDF IS A DATA MODEL;A DIRECTED, LABELED GRAPH USING URIS •  RDF IS BASED ONTRIPLES: – <SUBJECT> <PREDICATE> <OBJECT>.!
  • 13. Abbreviating uris PREFIX ex: http://example.org/# ex:maciej = <http://example.org/#maciej> ex:maciej-dabrowski ex:MDabrowski-lecture3 ex:author ex:Semantic_Web Introduction to the Semantic Web ex:title ex:subject
  • 14. Reuse existing vocabularies PREFIX dct: http://purl.org/dc/terms/ http://deri.ie/user/maciej-dabrowski http://example.org/MDabrowski-lecture3 dct:creator http://dbpedia.org/resource/Semantic_Web Introduction to the Semantic Web dct:title dct:subject
  • 15. RDF by example ! ! @prefix dct: <http://purl.org/dc/terms/> . ! <http://example.org/dm110-semweb>! !dct:title “Introduction to the Semantic Web” ; ! !dct:author <http://www.deri.ie/users/maciej-dabrowski> ; !! !dct:subject <http://dbpedia.org/resource/Semantic_Web> .!
  • 16. RDFA A WAY OF EMBEDDING RDF IN (X)HTML DOCUMENTS: ONE PAGE FOR BOTH HUMANS AND MACHINES DON’T NEEDTO REPEATYOURSELF INTRODUCING NEW XHTML ATTRIBUTES CURRENT WORK IS ONGOING ON RDFa 1.1: FOR PROFILES, ETC.
  • 18. Triples are everywhere! 10/06/2013   SUBJECT   PREDICATE   OBJECT   PREDICATE   OBJECT   OBJECT   …  
  • 19.
  • 20. Defining semantics with ontologies •  RDF PROVIDES A WAYTO WRITE ASSERTIONS ABOUT URIS •  WHAT ABOUTTHE SEMANTICS OFTHESE ASSERTIONS, E.G.TO STATETHAT HTTP:// XMLNS.COM/FOAF/0.1/KNOWS IDENTIFIES AN ACQUAINTANCE RELATIONSHIP? •  ONTOLOGIES PROVIDE COMMON SEMANTICS FOR RESOURCES ONTHE SEMANTIC WEB
  • 21. Ontologies consist mainly of classes and properties – :Person a rdfs:Class .! – :father a rdfs:Property .! – :father rdfs:domain :Person .! – :father rdfs:range :Person .! :Maciej :Mark :father :Person a :Person a
  • 22. Notable ontologies SOCIAL NETWORKS AND SOCIAL DATA: FOAF, SIOC TAXONOMIES AND CONTROLLED VOCABULARIES: SKOS, MOAT