SlideShare a Scribd company logo
1 of 14
Semantic Web (Web 3.0)
Big Data for Business
1/30/2014
Presented by: John dougherty
It’s big
Web 3.0 Definitions
Definition: The predicted third generation of
the World Wide Web, usually conjectured to
include semantic tagging of content

• Who’s in charge?
• W3C has consolidated the resources

• Value add positions, and platforms
• PaaS
• Structured design, implementations

• OORDBMS
• Object Oriented Relational Database Management System
Web 3.0 Definitions (cont.)
• RDF – Resource Description Framework (RDFS: RDF Schema)
• General method for describing information

• Simple Knowledge Organization System
• Its main objective is to enable easy publication and use of such vocabularies as linked data

• SPARQL – Recursive Acronym, SPARQL and RDF Query Language
• Allows for a query to consist of triple patterns (triple-stores holds these), conjunctions (logic), disjunctions (logic), and
optional patterns

• Triple Store – A purpose built database for the storage and retrievel of triples (triple patterns)
• These are ancillary to the idea of Web 3.0 and have been provided by many vendors

• OWL – Web Ontology Language
• OWL is a collection of ontology languages for authoring ontologies or vocabularies

• Vocabularies – Definition of concepts and relationships on the Semantic Web
• No clear division between what is referred to as a vocabulary, or an ontology
• Per the W3C: “The trend is to use the word “ontology” for more complex, and possibly quite formal collection of terms,
whereas “vocabulary” is used when such strict formalism is not necessarily used or only in a very loose sense.”
Web 3.0 Definitions – Vocabulary (or Ontology)
An example of the use of a vocabulary, or ontology:
A bookseller may want to integrate data coming from different publishers.
The data can be imported into a common RDF model, eg, by using converters to the
publishers’ databases. However, one database may use the term “author”, whereas
the other may use the term “creator”.
To make the integration complete, an extra definition should be added to the RDF
data, describing the fact that the relationship described as “author” is the same as
“creator”. This extra piece of information is, in fact, a vocabulary (or an ontology),
albeit an extremely simple one.
Web 3.0 – OORDBMS
Object Oriented Relational Database Management System
• Some debate as to what constitutes an ODBMS
• A basic support for classes of objects and the inheritance properties
and methods by subclasses and their objects
• An easier way (for a programmer/DBA) to understand what you’re
doing to the data.
Web 3.0 – Platforms
Vendors have found a marketplace

Salesforce
PaaS concepts and use cases

The Future Now
Has great descriptions and reviews for existing platforms

ZUEBOX
Linked data and consulting service to implement Web 3.0

FANGGLE
Vertical cloud product utilizing Web 3.0 concepts
Web 3.0 – Tools
Software solutions have been created

FacetApp
PaaS along with OntoApp as a modeling tool/solution

Oracle
Complete tools from modeling to production

IBM
Their best product has to be Watson, just spun off last year as a
business division

Salesforce
Consulting and programmer services augment their PaaS
Web 3.0 – Contentions

It’s a big web, and only getting bigger
We need to do something…but what?
Web 3.0 – Contentions (cont.)

Machine Learning (AI)
Why not both?

The Goal
Human designed approaches

Is consolidation to a single
approach necessary?
Web 3.0 – Challenges
Vastness
• Very large landscape

• Duplication, outlining what constitutes the same data

Vagueness
• Fuzzy logic will prevail

Uncertainty, Inconsistency
• Difficult to define/classify/ingest data

• Logical contradictions in ontologies/vocabularies
• Deductive reasoning falls apart; defeasible and paraconsistent seem to stand
Wrap-Up

Question everything

Thank you for your time.
John Dougherty, CIO - Viriton
Bibliography
Semantic Web
http://en.wikipedia.org/wiki/Semantic_Web#References
http://www.w3.org/standards/semanticweb/
http://commons.wikimedia.org/w/index.php?title=File:Aaron_Swartz_s_A_Programmable_Web_An_Unfinished_Work.pdf&page=9
http://www.brightfire.co.uk/blog/2012/marketing-automation-2/tech-expert-prediction-a-web-3-0-boom-by-2014
http://semanticweb.com/
http://facetapp.com/

Tools/PaaS
http://www.enterprisecioforum.com/en/blogs/jkhawaja/brave-new-world-wide-web-30
http://btogroup.com/
http://www.zslinc.com/enterprise-computing.htm
http://www.topquadrant.com/docs/whitepapers/TopQuadrant_Whitepaper_online.pdf

More Related Content

What's hot

Linked open data project
Linked open data projectLinked open data project
Linked open data project
Faathima Fayaza
 
euclid_linkedup WWW tutorial (Besnik Fetahu)
euclid_linkedup WWW tutorial (Besnik Fetahu)euclid_linkedup WWW tutorial (Besnik Fetahu)
euclid_linkedup WWW tutorial (Besnik Fetahu)
Besnik Fetahu
 
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early AdoptersApril 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
National Information Standards Organization (NISO)
 
Semantic Technologies: Representing Semantic Data
Semantic Technologies: Representing Semantic DataSemantic Technologies: Representing Semantic Data
Semantic Technologies: Representing Semantic Data
Matthew Rowe
 

What's hot (20)

Linking library data
Linking library dataLinking library data
Linking library data
 
Enterprise knowledge graphs
Enterprise knowledge graphsEnterprise knowledge graphs
Enterprise knowledge graphs
 
Linked open data project
Linked open data projectLinked open data project
Linked open data project
 
Keystone Summer School 2015: Mauro Dragoni, Ontologies For Information Retrieval
Keystone Summer School 2015: Mauro Dragoni, Ontologies For Information RetrievalKeystone Summer School 2015: Mauro Dragoni, Ontologies For Information Retrieval
Keystone Summer School 2015: Mauro Dragoni, Ontologies For Information Retrieval
 
Quick Linked Data Introduction
Quick Linked Data IntroductionQuick Linked Data Introduction
Quick Linked Data Introduction
 
Usage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application ScenariosUsage of Linked Data: Introduction and Application Scenarios
Usage of Linked Data: Introduction and Application Scenarios
 
Linked Data
Linked DataLinked Data
Linked Data
 
Introduction to linked data
Introduction to linked dataIntroduction to linked data
Introduction to linked data
 
euclid_linkedup WWW tutorial (Besnik Fetahu)
euclid_linkedup WWW tutorial (Besnik Fetahu)euclid_linkedup WWW tutorial (Besnik Fetahu)
euclid_linkedup WWW tutorial (Besnik Fetahu)
 
Big Linked Data - Creating Training Curricula
Big Linked Data - Creating Training CurriculaBig Linked Data - Creating Training Curricula
Big Linked Data - Creating Training Curricula
 
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early AdoptersApril 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
 
Documents, services, and data on the web
Documents, services, and data on the webDocuments, services, and data on the web
Documents, services, and data on the web
 
An introduction to Linked (Open) Data
An introduction to Linked (Open) DataAn introduction to Linked (Open) Data
An introduction to Linked (Open) Data
 
LDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and DiscussionLDOW2015 Position Talk and Discussion
LDOW2015 Position Talk and Discussion
 
Semantic Technologies: Representing Semantic Data
Semantic Technologies: Representing Semantic DataSemantic Technologies: Representing Semantic Data
Semantic Technologies: Representing Semantic Data
 
Interaction with Linked Data
Interaction with Linked DataInteraction with Linked Data
Interaction with Linked Data
 
Linked (Open) Data
Linked (Open) DataLinked (Open) Data
Linked (Open) Data
 
Linked Data Tutorial
Linked Data TutorialLinked Data Tutorial
Linked Data Tutorial
 
test
testtest
test
 
Linking Open Data
Linking Open DataLinking Open Data
Linking Open Data
 

Viewers also liked (20)

Enc lecture day3
Enc lecture day3Enc lecture day3
Enc lecture day3
 
Jiit 2013 14 project presentation aniket mishra
Jiit 2013 14 project presentation aniket mishraJiit 2013 14 project presentation aniket mishra
Jiit 2013 14 project presentation aniket mishra
 
Subculture hippie
Subculture hippieSubculture hippie
Subculture hippie
 
Evaluation Question 4
Evaluation Question 4Evaluation Question 4
Evaluation Question 4
 
Presentation1
Presentation1Presentation1
Presentation1
 
Pre cd and artist research
Pre cd and artist researchPre cd and artist research
Pre cd and artist research
 
Enc 3241 usability
Enc 3241 usabilityEnc 3241 usability
Enc 3241 usability
 
Diapositiva asesores
Diapositiva asesoresDiapositiva asesores
Diapositiva asesores
 
Usability ppt
Usability pptUsability ppt
Usability ppt
 
Organizaciones tradicionales vs organizaciones actuales
Organizaciones tradicionales vs organizaciones actuales Organizaciones tradicionales vs organizaciones actuales
Organizaciones tradicionales vs organizaciones actuales
 
Enc 3241 color
Enc 3241 colorEnc 3241 color
Enc 3241 color
 
Michigan Therapy Institute
Michigan Therapy InstituteMichigan Therapy Institute
Michigan Therapy Institute
 
Qtllb
QtllbQtllb
Qtllb
 
La empresa
La empresaLa empresa
La empresa
 
Qlitan wid my cousins
Qlitan wid my cousinsQlitan wid my cousins
Qlitan wid my cousins
 
Aca advocacy
Aca advocacyAca advocacy
Aca advocacy
 
Enc 3241 document_design1
Enc 3241 document_design1Enc 3241 document_design1
Enc 3241 document_design1
 
Enc 3241 color
Enc 3241 colorEnc 3241 color
Enc 3241 color
 
페차쿠차_ 조연진
페차쿠차_ 조연진페차쿠차_ 조연진
페차쿠차_ 조연진
 
페차쿠차
페차쿠차페차쿠차
페차쿠차
 

Similar to Semantic Web (Web 3.0)

Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark Greaves
Mediabistro
 

Similar to Semantic Web (Web 3.0) (20)

Semantic Web and Linked Open Data
Semantic Web and Linked Open DataSemantic Web and Linked Open Data
Semantic Web and Linked Open Data
 
Intro to the semantic web (for libraries)
Intro to the semantic web (for libraries) Intro to the semantic web (for libraries)
Intro to the semantic web (for libraries)
 
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
 
Corrib.org - OpenSource and Research
Corrib.org - OpenSource and ResearchCorrib.org - OpenSource and Research
Corrib.org - OpenSource and Research
 
Semantic Web, e-commerce
Semantic Web, e-commerceSemantic Web, e-commerce
Semantic Web, e-commerce
 
Linked data and voyager
Linked data and voyagerLinked data and voyager
Linked data and voyager
 
Intelligent expert systems for location planning
Intelligent expert systems for location planningIntelligent expert systems for location planning
Intelligent expert systems for location planning
 
The Web of data and web data commons
The Web of data and web data commonsThe Web of data and web data commons
The Web of data and web data commons
 
Linked data HHS 2015
Linked data HHS 2015Linked data HHS 2015
Linked data HHS 2015
 
PoolParty SKOS and Linked Data
PoolParty SKOS and Linked DataPoolParty SKOS and Linked Data
PoolParty SKOS and Linked Data
 
Web 3 Mark Greaves
Web 3 Mark GreavesWeb 3 Mark Greaves
Web 3 Mark Greaves
 
First Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the CloudFirst Steps in Semantic Data Modelling and Search & Analytics in the Cloud
First Steps in Semantic Data Modelling and Search & Analytics in the Cloud
 
Why rdfa
Why rdfaWhy rdfa
Why rdfa
 
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
 
DM110 - Week 10 - Semantic Web / Web 3.0
DM110 - Week 10 - Semantic Web / Web 3.0DM110 - Week 10 - Semantic Web / Web 3.0
DM110 - Week 10 - Semantic Web / Web 3.0
 
The Web of Data: The W3C Semantic Web Initiative
The Web of Data: The W3C Semantic Web InitiativeThe Web of Data: The W3C Semantic Web Initiative
The Web of Data: The W3C Semantic Web Initiative
 
Semantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & MetadataSemantic Web, Cataloging, & Metadata
Semantic Web, Cataloging, & Metadata
 
State of the Semantic Web
State of the Semantic WebState of the Semantic Web
State of the Semantic Web
 
unit 1.pptx
unit 1.pptxunit 1.pptx
unit 1.pptx
 

Recently uploaded

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
vu2urc
 

Recently uploaded (20)

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Tech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdfTech Trends Report 2024 Future Today Institute.pdf
Tech Trends Report 2024 Future Today Institute.pdf
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 

Semantic Web (Web 3.0)

  • 1. Semantic Web (Web 3.0) Big Data for Business 1/30/2014 Presented by: John dougherty
  • 3. Web 3.0 Definitions Definition: The predicted third generation of the World Wide Web, usually conjectured to include semantic tagging of content • Who’s in charge? • W3C has consolidated the resources • Value add positions, and platforms • PaaS • Structured design, implementations • OORDBMS • Object Oriented Relational Database Management System
  • 4. Web 3.0 Definitions (cont.) • RDF – Resource Description Framework (RDFS: RDF Schema) • General method for describing information • Simple Knowledge Organization System • Its main objective is to enable easy publication and use of such vocabularies as linked data • SPARQL – Recursive Acronym, SPARQL and RDF Query Language • Allows for a query to consist of triple patterns (triple-stores holds these), conjunctions (logic), disjunctions (logic), and optional patterns • Triple Store – A purpose built database for the storage and retrievel of triples (triple patterns) • These are ancillary to the idea of Web 3.0 and have been provided by many vendors • OWL – Web Ontology Language • OWL is a collection of ontology languages for authoring ontologies or vocabularies • Vocabularies – Definition of concepts and relationships on the Semantic Web • No clear division between what is referred to as a vocabulary, or an ontology • Per the W3C: “The trend is to use the word “ontology” for more complex, and possibly quite formal collection of terms, whereas “vocabulary” is used when such strict formalism is not necessarily used or only in a very loose sense.”
  • 5. Web 3.0 Definitions – Vocabulary (or Ontology) An example of the use of a vocabulary, or ontology: A bookseller may want to integrate data coming from different publishers. The data can be imported into a common RDF model, eg, by using converters to the publishers’ databases. However, one database may use the term “author”, whereas the other may use the term “creator”. To make the integration complete, an extra definition should be added to the RDF data, describing the fact that the relationship described as “author” is the same as “creator”. This extra piece of information is, in fact, a vocabulary (or an ontology), albeit an extremely simple one.
  • 6. Web 3.0 – OORDBMS Object Oriented Relational Database Management System • Some debate as to what constitutes an ODBMS • A basic support for classes of objects and the inheritance properties and methods by subclasses and their objects • An easier way (for a programmer/DBA) to understand what you’re doing to the data.
  • 7. Web 3.0 – Platforms Vendors have found a marketplace Salesforce PaaS concepts and use cases The Future Now Has great descriptions and reviews for existing platforms ZUEBOX Linked data and consulting service to implement Web 3.0 FANGGLE Vertical cloud product utilizing Web 3.0 concepts
  • 8. Web 3.0 – Tools Software solutions have been created FacetApp PaaS along with OntoApp as a modeling tool/solution Oracle Complete tools from modeling to production IBM Their best product has to be Watson, just spun off last year as a business division Salesforce Consulting and programmer services augment their PaaS
  • 9. Web 3.0 – Contentions It’s a big web, and only getting bigger We need to do something…but what?
  • 10. Web 3.0 – Contentions (cont.) Machine Learning (AI) Why not both? The Goal Human designed approaches Is consolidation to a single approach necessary?
  • 11. Web 3.0 – Challenges Vastness • Very large landscape • Duplication, outlining what constitutes the same data Vagueness • Fuzzy logic will prevail Uncertainty, Inconsistency • Difficult to define/classify/ingest data • Logical contradictions in ontologies/vocabularies • Deductive reasoning falls apart; defeasible and paraconsistent seem to stand
  • 12.
  • 13. Wrap-Up Question everything Thank you for your time. John Dougherty, CIO - Viriton