SlideShare a Scribd company logo
RDFa 1.1 Basics
Rich Structured Data Mark-up for Web
Documents
What Browsers see What Humans see
▶ The missing piece is the meaning of the web page’s visual elements
 What’s the missing piece of the web?
What Browsers see What Humans see
▶ RDFa is a bridge between the Web of Documents and the Web of Data
 What’s RDFa?
Add machine-readable
hints to webpage
Add machine-readable
hints to webpage
 RDFa Example
▶ By adding machine-readable hints (property like
“title” and “created”, which are well-defined
vocabularies in the described (URI) resources,
browsers be could able to know the meaning that
can be represented as triples.
▶ By adding machine-readable hints (property like
“title” and “created”, which are well-defined
vocabularies in the described (URI) resources,
browsers be could able to know the meaning that
can be represented as triples.
 Problem#1 : Isn’t it so difficult to add so long property value for
every single element?
▶ RDFa alleviate the problem by setting default
vocab attribute to let the author declare a single
vocabulary for a chunk of HTML.
▶ RDFa alleviate the problem by setting default
vocab attribute to let the author declare a single
vocabulary for a chunk of HTML.
Setting default vocab
 Vocab attribute example
The first vocab attribute
The second vocab attribute
▶ The vocab in the license paragraph overrides the definition inherited from the
body of the document.
▶ The vocab in the license paragraph overrides the definition inherited from the
body of the document.
 Example with FOAF vocabulary
 Example with FOAF vocabulary
 Problem#2 : What if there’s repeated pattern?
▶ RDFa alleviate the problem by using rdfa:copy and the magic type rdfa:Pattern▶ RDFa alleviate the problem by using rdfa:copy and the magic type rdfa:Pattern
 Problem#3 : How to make internal reference?
If the left Alice could be refer to the right Alice
resource which already is described with
RDFa mark-up, the browser could know the
Alice is the person we already described in
the right as well.
If the left Alice could be refer to the right Alice
resource which already is described with
RDFa mark-up, the browser could know the
Alice is the person we already described in
the right as well.
 Problem#3 : How to make internal reference?
▶ The resource attribute appears, in this case, together with property on the same
element: in this situation resource indicates the target of the relation.
▶ The resource attribute appears, in this case, together with property on the same
element: in this situation resource indicates the target of the relation.
 Problem#4 : How to use multiple vocabularies?
- it will be complicated if we use different vocabularies interwined and in different places of the webpage
 Problem#4 : How to use multiple vocabularies?
▶ RDFa offers the possibility of using prefixed terms: a special prefix attribute can
assign prefixes to represent URLs and, using those prefixes, the vocabulary
elements themselves can be abbreviated. The prefix:reference syntax is used: the
URL associated with prefix is simply concatenated to reference to create a full URL.
▶ RDFa offers the possibility of using prefixed terms: a special prefix attribute can
assign prefixes to represent URLs and, using those prefixes, the vocabulary
elements themselves can be abbreviated. The prefix:reference syntax is used: the
URL associated with prefix is simply concatenated to reference to create a full URL.
 RDFa Tool
RDFa Basics

More Related Content

What's hot

Web Search Engine
Web Search EngineWeb Search Engine
Web Search Engine
Chidanand Byahatti
 
Surfing the internet
Surfing the internetSurfing the internet
Surfing the internet
Eveferro
 
search engines
search enginessearch engines
search engines
AshaKrishnan
 
Search engine
Search engineSearch engine
Search engine
samantha varghese
 
Search engines
Search enginesSearch engines
Search engines
Ramesh Ogania
 
Smart Searching
Smart SearchingSmart Searching
Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data Tutorial
Sören Auer
 
Semantic Web(Web 3.0) SPARQL
Semantic Web(Web 3.0) SPARQLSemantic Web(Web 3.0) SPARQL
Semantic Web(Web 3.0) SPARQL
Daniel D.J. UM
 
Leveraging the semantic web meetup, Semantic Search, Schema.org and more
Leveraging the semantic web meetup, Semantic Search, Schema.org and moreLeveraging the semantic web meetup, Semantic Search, Schema.org and more
Leveraging the semantic web meetup, Semantic Search, Schema.org and more
BarbaraStarr2009
 
Internet Search Tools
Internet Search ToolsInternet Search Tools
Internet Search Tools
wmassie
 
Web search engines ( Mr.Mirza )
Web search engines ( Mr.Mirza )Web search engines ( Mr.Mirza )
Web search engines ( Mr.Mirza )
Ali Saif Mirza
 
Search Engine ppt
Search Engine pptSearch Engine ppt
Search engine
Search engineSearch engine
Search engine
silambu111
 
Search engine ppt
Search engine pptSearch engine ppt
Search engine ppt
Polara Mayur
 
Search Engines
Search EnginesSearch Engines
Search Engines
Chidanand Byahatti
 
Search Engine
Search EngineSearch Engine
Search Engine
Ankush Srivastava
 
Search Engine Demystified
Search Engine DemystifiedSearch Engine Demystified
Search Engine Demystified
Sudarsun Santhiappan
 
Internet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and MoreInternet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and More
eclark131
 
Google Search Engine
Google Search EngineGoogle Search Engine
Google Search Engine
guestf460ed0
 
Working of search engine
Working of search engineWorking of search engine
Working of search engine
Nikhil Deswal
 

What's hot (20)

Web Search Engine
Web Search EngineWeb Search Engine
Web Search Engine
 
Surfing the internet
Surfing the internetSurfing the internet
Surfing the internet
 
search engines
search enginessearch engines
search engines
 
Search engine
Search engineSearch engine
Search engine
 
Search engines
Search enginesSearch engines
Search engines
 
Smart Searching
Smart SearchingSmart Searching
Smart Searching
 
Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data Tutorial
 
Semantic Web(Web 3.0) SPARQL
Semantic Web(Web 3.0) SPARQLSemantic Web(Web 3.0) SPARQL
Semantic Web(Web 3.0) SPARQL
 
Leveraging the semantic web meetup, Semantic Search, Schema.org and more
Leveraging the semantic web meetup, Semantic Search, Schema.org and moreLeveraging the semantic web meetup, Semantic Search, Schema.org and more
Leveraging the semantic web meetup, Semantic Search, Schema.org and more
 
Internet Search Tools
Internet Search ToolsInternet Search Tools
Internet Search Tools
 
Web search engines ( Mr.Mirza )
Web search engines ( Mr.Mirza )Web search engines ( Mr.Mirza )
Web search engines ( Mr.Mirza )
 
Search Engine ppt
Search Engine pptSearch Engine ppt
Search Engine ppt
 
Search engine
Search engineSearch engine
Search engine
 
Search engine ppt
Search engine pptSearch engine ppt
Search engine ppt
 
Search Engines
Search EnginesSearch Engines
Search Engines
 
Search Engine
Search EngineSearch Engine
Search Engine
 
Search Engine Demystified
Search Engine DemystifiedSearch Engine Demystified
Search Engine Demystified
 
Internet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and MoreInternet Research: Finding Websites, Blogs, Wikis, and More
Internet Research: Finding Websites, Blogs, Wikis, and More
 
Google Search Engine
Google Search EngineGoogle Search Engine
Google Search Engine
 
Working of search engine
Working of search engineWorking of search engine
Working of search engine
 

Similar to RDFa Basics

Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Diego López-de-Ipiña González-de-Artaza
 
Introduction to Linked Data
Introduction to Linked DataIntroduction to Linked Data
Introduction to Linked Data
Juan Sequeda
 
Understanding RDF: the Resource Description Framework in Context (1999)
Understanding RDF: the Resource Description Framework in Context  (1999)Understanding RDF: the Resource Description Framework in Context  (1999)
Understanding RDF: the Resource Description Framework in Context (1999)
Dan Brickley
 
RDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use itRDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use it
Jose Luis Lopez Pino
 
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
Platypus
 
Why rdfa
Why rdfaWhy rdfa
Why rdfa
JISC Netskills
 
RDF presentation at DrupalCon San Francisco 2010
RDF presentation at DrupalCon San Francisco 2010RDF presentation at DrupalCon San Francisco 2010
RDF presentation at DrupalCon San Francisco 2010
scorlosquet
 
RDFa: an introduction
RDFa: an introductionRDFa: an introduction
RDFa: an introduction
Kai Li
 
Publishing data on the Semantic Web
Publishing data on the Semantic WebPublishing data on the Semantic Web
Publishing data on the Semantic Web
Peter Mika
 
Search Engines After The Semanatic Web
Search Engines After The Semanatic WebSearch Engines After The Semanatic Web
Search Engines After The Semanatic Web
samar_slideshare
 
SemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n BoltsSemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n Bolts
Rinke Hoekstra
 
RDFa Semantic Web
RDFa Semantic WebRDFa Semantic Web
RDFa Semantic Web
Rob Paok
 
Semantic Search using RDF Metadata (SemTech 2005)
Semantic Search using RDF Metadata (SemTech 2005)Semantic Search using RDF Metadata (SemTech 2005)
Semantic Search using RDF Metadata (SemTech 2005)
Bradley Allen
 
Semantic Web and Linked Open Data
Semantic Web and Linked Open DataSemantic Web and Linked Open Data
Semantic Web and Linked Open Data
University of Wisconsin-Madison
 
Danbri Drupalcon Export
Danbri Drupalcon ExportDanbri Drupalcon Export
Danbri Drupalcon Export
Drupalcon Paris
 
RDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use itRDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use it
Jose Luis Lopez Pino
 
Semantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & MetadataSemantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & Metadata
robin fay
 
XML Bible
XML BibleXML Bible
XML Bible
LiquidHub
 
RDF and Drupal - The Semantic web
RDF and Drupal - The Semantic webRDF and Drupal - The Semantic web
RDF and Drupal - The Semantic web
gauravkumar87
 
Analysis on semantic web layer cake entities
Analysis on semantic web layer cake entitiesAnalysis on semantic web layer cake entities
Analysis on semantic web layer cake entities
తేజ దండిభట్ల
 

Similar to RDFa Basics (20)

Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
Hacia la Internet del Futuro: Web Semántica y Open Linked Data, Parte 2
 
Introduction to Linked Data
Introduction to Linked DataIntroduction to Linked Data
Introduction to Linked Data
 
Understanding RDF: the Resource Description Framework in Context (1999)
Understanding RDF: the Resource Description Framework in Context  (1999)Understanding RDF: the Resource Description Framework in Context  (1999)
Understanding RDF: the Resource Description Framework in Context (1999)
 
RDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use itRDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use it
 
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
 
Why rdfa
Why rdfaWhy rdfa
Why rdfa
 
RDF presentation at DrupalCon San Francisco 2010
RDF presentation at DrupalCon San Francisco 2010RDF presentation at DrupalCon San Francisco 2010
RDF presentation at DrupalCon San Francisco 2010
 
RDFa: an introduction
RDFa: an introductionRDFa: an introduction
RDFa: an introduction
 
Publishing data on the Semantic Web
Publishing data on the Semantic WebPublishing data on the Semantic Web
Publishing data on the Semantic Web
 
Search Engines After The Semanatic Web
Search Engines After The Semanatic WebSearch Engines After The Semanatic Web
Search Engines After The Semanatic Web
 
SemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n BoltsSemanticWeb Nuts 'n Bolts
SemanticWeb Nuts 'n Bolts
 
RDFa Semantic Web
RDFa Semantic WebRDFa Semantic Web
RDFa Semantic Web
 
Semantic Search using RDF Metadata (SemTech 2005)
Semantic Search using RDF Metadata (SemTech 2005)Semantic Search using RDF Metadata (SemTech 2005)
Semantic Search using RDF Metadata (SemTech 2005)
 
Semantic Web and Linked Open Data
Semantic Web and Linked Open DataSemantic Web and Linked Open Data
Semantic Web and Linked Open Data
 
Danbri Drupalcon Export
Danbri Drupalcon ExportDanbri Drupalcon Export
Danbri Drupalcon Export
 
RDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use itRDFa: introduction, comparison with microdata and microformats and how to use it
RDFa: introduction, comparison with microdata and microformats and how to use it
 
Semantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & MetadataSemantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & Metadata
 
XML Bible
XML BibleXML Bible
XML Bible
 
RDF and Drupal - The Semantic web
RDF and Drupal - The Semantic webRDF and Drupal - The Semantic web
RDF and Drupal - The Semantic web
 
Analysis on semantic web layer cake entities
Analysis on semantic web layer cake entitiesAnalysis on semantic web layer cake entities
Analysis on semantic web layer cake entities
 

More from GUANGYUAN PIAO

Env2Vec: Accelerating VNF Testing with Deep Learning
Env2Vec: Accelerating VNF Testing with Deep LearningEnv2Vec: Accelerating VNF Testing with Deep Learning
Env2Vec: Accelerating VNF Testing with Deep Learning
GUANGYUAN PIAO
 
Domain-Aware Sentiment Classification with GRUs and CNNs
Domain-Aware Sentiment Classification with GRUs and CNNsDomain-Aware Sentiment Classification with GRUs and CNNs
Domain-Aware Sentiment Classification with GRUs and CNNs
GUANGYUAN PIAO
 
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
GUANGYUAN PIAO
 
Retweet Prediction with Attention-based Deep Neural Network
Retweet Prediction with Attention-based Deep Neural NetworkRetweet Prediction with Attention-based Deep Neural Network
Retweet Prediction with Attention-based Deep Neural Network
GUANGYUAN PIAO
 
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
GUANGYUAN PIAO
 
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
GUANGYUAN PIAO
 
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
GUANGYUAN PIAO
 
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
GUANGYUAN PIAO
 
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
GUANGYUAN PIAO
 
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
GUANGYUAN PIAO
 
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
GUANGYUAN PIAO
 
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
GUANGYUAN PIAO
 
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
GUANGYUAN PIAO
 
JIST2015-data challenge
JIST2015-data challengeJIST2015-data challenge
JIST2015-data challenge
GUANGYUAN PIAO
 
Analyzing User Modeling on Twitter for Personalized News Recommendations
Analyzing User Modeling on Twitter for Personalized News RecommendationsAnalyzing User Modeling on Twitter for Personalized News Recommendations
Analyzing User Modeling on Twitter for Personalized News Recommendations
GUANGYUAN PIAO
 
Owl 2.0 Overview
Owl 2.0 OverviewOwl 2.0 Overview
Owl 2.0 Overview
GUANGYUAN PIAO
 
OWL 2.0 Primer Part01
OWL 2.0 Primer Part01OWL 2.0 Primer Part01
OWL 2.0 Primer Part01
GUANGYUAN PIAO
 
OWL2.0 Primer Part02
OWL2.0 Primer Part02OWL2.0 Primer Part02
OWL2.0 Primer Part02
GUANGYUAN PIAO
 
Hdd industry
Hdd industryHdd industry
Hdd industry
GUANGYUAN PIAO
 

More from GUANGYUAN PIAO (19)

Env2Vec: Accelerating VNF Testing with Deep Learning
Env2Vec: Accelerating VNF Testing with Deep LearningEnv2Vec: Accelerating VNF Testing with Deep Learning
Env2Vec: Accelerating VNF Testing with Deep Learning
 
Domain-Aware Sentiment Classification with GRUs and CNNs
Domain-Aware Sentiment Classification with GRUs and CNNsDomain-Aware Sentiment Classification with GRUs and CNNs
Domain-Aware Sentiment Classification with GRUs and CNNs
 
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
A Study of the Similarities of Entity Embeddings Learned from Different Aspec...
 
Retweet Prediction with Attention-based Deep Neural Network
Retweet Prediction with Attention-based Deep Neural NetworkRetweet Prediction with Attention-based Deep Neural Network
Retweet Prediction with Attention-based Deep Neural Network
 
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
WISE2017 - Factorization Machines Leveraging Lightweight Linked Open Data-ena...
 
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
Hypertext2017-Leveraging Followee List Memberships for Inferring User Interes...
 
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
ECIR2017-Inferring User Interests for Passive Users on Twitter by Leveraging ...
 
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A ...
 
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
SEMANTiCS2016 - Exploring Dynamics and Semantics of User Interests for User ...
 
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
UMAP2016EA - Analyzing MOOC Entries of Professionals on LinkedIn for User Mod...
 
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
UMAP2016 - Analyzing Aggregated Semantics-enabled User Modeling on Google+ an...
 
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
SAC2016-Measuring Semantic Distance for Linked Open Data-enabled Recommender ...
 
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
JIST2015-Computing the Semantic Similarity of Resources in DBpedia for Recomm...
 
JIST2015-data challenge
JIST2015-data challengeJIST2015-data challenge
JIST2015-data challenge
 
Analyzing User Modeling on Twitter for Personalized News Recommendations
Analyzing User Modeling on Twitter for Personalized News RecommendationsAnalyzing User Modeling on Twitter for Personalized News Recommendations
Analyzing User Modeling on Twitter for Personalized News Recommendations
 
Owl 2.0 Overview
Owl 2.0 OverviewOwl 2.0 Overview
Owl 2.0 Overview
 
OWL 2.0 Primer Part01
OWL 2.0 Primer Part01OWL 2.0 Primer Part01
OWL 2.0 Primer Part01
 
OWL2.0 Primer Part02
OWL2.0 Primer Part02OWL2.0 Primer Part02
OWL2.0 Primer Part02
 
Hdd industry
Hdd industryHdd industry
Hdd industry
 

Recently uploaded

University of California, Riverside diploma
University of California, Riverside diplomaUniversity of California, Riverside diploma
University of California, Riverside diploma
eufdev
 
upgrade to zabbix-7 0 como atualiza lts1
upgrade to zabbix-7 0 como atualiza lts1upgrade to zabbix-7 0 como atualiza lts1
upgrade to zabbix-7 0 como atualiza lts1
diogolsew
 
New York Institute of Technology degree Cert diploma offer
New York Institute of Technology degree Cert diploma offerNew York Institute of Technology degree Cert diploma offer
New York Institute of Technology degree Cert diploma offer
ubovu
 
Trump fist pump t shirts Trump fist pump t shirts
Trump fist pump t shirts Trump fist pump t shirtsTrump fist pump t shirts Trump fist pump t shirts
Trump fist pump t shirts Trump fist pump t shirts
exgf28
 
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
QingjieDu1
 
Team Cymru Community Services,Overview of all public services
Team Cymru Community Services,Overview of all public servicesTeam Cymru Community Services,Overview of all public services
Team Cymru Community Services,Overview of all public services
Bangladesh Network Operators Group
 
How God led me to DTS? Through many different signs and connections that I c...
How God led me to DTS? Through many different signs and connections that  I c...How God led me to DTS? Through many different signs and connections that  I c...
How God led me to DTS? Through many different signs and connections that I c...
AshishMohan57
 
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
dilbaagsingh0898
 
Enhancing seamless access using TIGERfed
Enhancing seamless access using TIGERfedEnhancing seamless access using TIGERfed
Enhancing seamless access using TIGERfed
Bangladesh Network Operators Group
 
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
ffg01100
 
IPv6 Deployment Planning and Security Considerations
IPv6 Deployment Planning and Security ConsiderationsIPv6 Deployment Planning and Security Considerations
IPv6 Deployment Planning and Security Considerations
Bangladesh Network Operators Group
 
Network Security version1.0 - Module 3.pptx
Network Security version1.0 - Module 3.pptxNetwork Security version1.0 - Module 3.pptx
Network Security version1.0 - Module 3.pptx
Infotainmentforall
 
Maximizing Network Efficiency with Large Language Models (LLM)
Maximizing Network Efficiency with Large Language Models (LLM)Maximizing Network Efficiency with Large Language Models (LLM)
Maximizing Network Efficiency with Large Language Models (LLM)
Bangladesh Network Operators Group
 
Portugal Dreamin 24 - How to easily use an API with Flows
Portugal Dreamin 24  - How to easily use an API with FlowsPortugal Dreamin 24  - How to easily use an API with Flows
Portugal Dreamin 24 - How to easily use an API with Flows
Thierry TROUIN ☁
 
Software Defined Networking, Concepts and Practical Implementations
Software Defined Networking, Concepts and Practical ImplementationsSoftware Defined Networking, Concepts and Practical Implementations
Software Defined Networking, Concepts and Practical Implementations
Bangladesh Network Operators Group
 
Best Skills to Learn for Freelancing.pdf
Best Skills to Learn for Freelancing.pdfBest Skills to Learn for Freelancing.pdf
Best Skills to Learn for Freelancing.pdf
Million-$-Knowledge {Million Dollar Knowledge}
 
Rent remote desktop server mangohost .net
Rent remote desktop server mangohost .netRent remote desktop server mangohost .net
Rent remote desktop server mangohost .net
pdfsubmission50
 
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
elbertablack
 
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
mahigarg2024#G05
 
Do it again anti Republican shirt Do it again anti Republican shirt
Do it again anti Republican shirt Do it again anti Republican shirtDo it again anti Republican shirt Do it again anti Republican shirt
Do it again anti Republican shirt Do it again anti Republican shirt
exgf28
 

Recently uploaded (20)

University of California, Riverside diploma
University of California, Riverside diplomaUniversity of California, Riverside diploma
University of California, Riverside diploma
 
upgrade to zabbix-7 0 como atualiza lts1
upgrade to zabbix-7 0 como atualiza lts1upgrade to zabbix-7 0 como atualiza lts1
upgrade to zabbix-7 0 como atualiza lts1
 
New York Institute of Technology degree Cert diploma offer
New York Institute of Technology degree Cert diploma offerNew York Institute of Technology degree Cert diploma offer
New York Institute of Technology degree Cert diploma offer
 
Trump fist pump t shirts Trump fist pump t shirts
Trump fist pump t shirts Trump fist pump t shirtsTrump fist pump t shirts Trump fist pump t shirts
Trump fist pump t shirts Trump fist pump t shirts
 
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
SisAi World - Software is AI - Providing AI as Software - Protecting the Inte...
 
Team Cymru Community Services,Overview of all public services
Team Cymru Community Services,Overview of all public servicesTeam Cymru Community Services,Overview of all public services
Team Cymru Community Services,Overview of all public services
 
How God led me to DTS? Through many different signs and connections that I c...
How God led me to DTS? Through many different signs and connections that  I c...How God led me to DTS? Through many different signs and connections that  I c...
How God led me to DTS? Through many different signs and connections that I c...
 
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in CityGirls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
Girls Call Shimla 000XX00000 Provide Best And Top Girl Service And No1 in City
 
Enhancing seamless access using TIGERfed
Enhancing seamless access using TIGERfedEnhancing seamless access using TIGERfed
Enhancing seamless access using TIGERfed
 
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
202254.com香蕉影视,在线观看《我才不要和你做朋友呢》在线观看最新电影,香蕉影视在线观看《我才不要和你做朋友呢》在线观看高清电影
 
IPv6 Deployment Planning and Security Considerations
IPv6 Deployment Planning and Security ConsiderationsIPv6 Deployment Planning and Security Considerations
IPv6 Deployment Planning and Security Considerations
 
Network Security version1.0 - Module 3.pptx
Network Security version1.0 - Module 3.pptxNetwork Security version1.0 - Module 3.pptx
Network Security version1.0 - Module 3.pptx
 
Maximizing Network Efficiency with Large Language Models (LLM)
Maximizing Network Efficiency with Large Language Models (LLM)Maximizing Network Efficiency with Large Language Models (LLM)
Maximizing Network Efficiency with Large Language Models (LLM)
 
Portugal Dreamin 24 - How to easily use an API with Flows
Portugal Dreamin 24  - How to easily use an API with FlowsPortugal Dreamin 24  - How to easily use an API with Flows
Portugal Dreamin 24 - How to easily use an API with Flows
 
Software Defined Networking, Concepts and Practical Implementations
Software Defined Networking, Concepts and Practical ImplementationsSoftware Defined Networking, Concepts and Practical Implementations
Software Defined Networking, Concepts and Practical Implementations
 
Best Skills to Learn for Freelancing.pdf
Best Skills to Learn for Freelancing.pdfBest Skills to Learn for Freelancing.pdf
Best Skills to Learn for Freelancing.pdf
 
Rent remote desktop server mangohost .net
Rent remote desktop server mangohost .netRent remote desktop server mangohost .net
Rent remote desktop server mangohost .net
 
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
Female Service Girls Call Delhi 9873940964 Provide Best And Top Girl Service ...
 
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
Girls Call Mahipalpur 000XX00000 Provide Best And Top Girl Service And No1 in...
 
Do it again anti Republican shirt Do it again anti Republican shirt
Do it again anti Republican shirt Do it again anti Republican shirtDo it again anti Republican shirt Do it again anti Republican shirt
Do it again anti Republican shirt Do it again anti Republican shirt
 

RDFa Basics

  • 1. RDFa 1.1 Basics Rich Structured Data Mark-up for Web Documents
  • 2. What Browsers see What Humans see ▶ The missing piece is the meaning of the web page’s visual elements  What’s the missing piece of the web?
  • 3. What Browsers see What Humans see ▶ RDFa is a bridge between the Web of Documents and the Web of Data  What’s RDFa? Add machine-readable hints to webpage
  • 4. Add machine-readable hints to webpage  RDFa Example ▶ By adding machine-readable hints (property like “title” and “created”, which are well-defined vocabularies in the described (URI) resources, browsers be could able to know the meaning that can be represented as triples. ▶ By adding machine-readable hints (property like “title” and “created”, which are well-defined vocabularies in the described (URI) resources, browsers be could able to know the meaning that can be represented as triples.
  • 5.  Problem#1 : Isn’t it so difficult to add so long property value for every single element? ▶ RDFa alleviate the problem by setting default vocab attribute to let the author declare a single vocabulary for a chunk of HTML. ▶ RDFa alleviate the problem by setting default vocab attribute to let the author declare a single vocabulary for a chunk of HTML. Setting default vocab
  • 6.  Vocab attribute example The first vocab attribute The second vocab attribute ▶ The vocab in the license paragraph overrides the definition inherited from the body of the document. ▶ The vocab in the license paragraph overrides the definition inherited from the body of the document.
  • 7.  Example with FOAF vocabulary
  • 8.  Example with FOAF vocabulary
  • 9.  Problem#2 : What if there’s repeated pattern?
  • 10. ▶ RDFa alleviate the problem by using rdfa:copy and the magic type rdfa:Pattern▶ RDFa alleviate the problem by using rdfa:copy and the magic type rdfa:Pattern
  • 11.  Problem#3 : How to make internal reference? If the left Alice could be refer to the right Alice resource which already is described with RDFa mark-up, the browser could know the Alice is the person we already described in the right as well. If the left Alice could be refer to the right Alice resource which already is described with RDFa mark-up, the browser could know the Alice is the person we already described in the right as well.
  • 12.  Problem#3 : How to make internal reference? ▶ The resource attribute appears, in this case, together with property on the same element: in this situation resource indicates the target of the relation. ▶ The resource attribute appears, in this case, together with property on the same element: in this situation resource indicates the target of the relation.
  • 13.  Problem#4 : How to use multiple vocabularies? - it will be complicated if we use different vocabularies interwined and in different places of the webpage
  • 14.  Problem#4 : How to use multiple vocabularies? ▶ RDFa offers the possibility of using prefixed terms: a special prefix attribute can assign prefixes to represent URLs and, using those prefixes, the vocabulary elements themselves can be abbreviated. The prefix:reference syntax is used: the URL associated with prefix is simply concatenated to reference to create a full URL. ▶ RDFa offers the possibility of using prefixed terms: a special prefix attribute can assign prefixes to represent URLs and, using those prefixes, the vocabulary elements themselves can be abbreviated. The prefix:reference syntax is used: the URL associated with prefix is simply concatenated to reference to create a full URL.