Semantic web (Foundation – Architecture – Languages – Tools)

EMU–School of Computing and Technology

Karwan JacksiPhD StudentEastern Mediterranean University & University of ZakhoSchool of Computing and Technology & Department of Computer Science

Link to the slideswww.KarwanJacksi.net/seminars

Guest LectureText Mining -Fall – 201514.12.2015

Semantic WebFoundation – Architecture – Languages – Tools


05/03/2023Karwan Jacksi 2

Agenda

• Development of the Web• Limitations of the current Web• Introduction to Semantic Web• Semantic Web Architecture and Languages• Semantic Web Tools• Who actually does the Semantic Web?• Summery• References



Development of the Web

a) Internet

b) Web 1.0

c) Web 2.0

d) Web 3.0?



a)-Internet

• “The Internet is a global system of interconnected computer networks that use the standard Internet Protocol Suite (TCP/IP) to serve billions of users worldwide.

• It is a network of networks that consists of millions of private and public, academic, business, and government networks of local to global scope that are linked by a broad array of electronic and optical networking technologies.”



1-Internet Cont’d



Memex Conceived

1945

WWWCreated

1989

MosaicCreated

1993

A Mathematical

Theory of Communication

1948

Packet Switching Invented

1964

SiliconChip1958

First Vast ComputerNetwork

Envisioned1962

ARPANET1969

TCP/IPCreated

1972

InternetNamed

and Goes

TCP/IP1984

HypertextInvented

1965

Age ofeCommerce

Begins1995

A brief summary of Internet evolution

1945 1995



b) Web 1.0

• “The World Wide Web ("WWW" or simply the "Web") is a system of interlinked, hypertext documents that runs over the Internet.

• With a Web browser, a user views Web pages that may contain text, images, and other multimedia and navigates between them using hyperlinks”.



c) Web 2.0

• “The term "Web 2.0" (2004) is commonly associated with web applications that facilitate interactive information sharing, interoperability, user-centered design, and collaboration on the World Wide Web”



3- Web 2.0 Cont’d

• A Web 2.0 site may allow users to interact and collaborate with each other in a social media dialogue as creators of user-generated content in a virtual community, in contrast to Web sites where people are limited to the passive viewing of content. – Examples of Web 2.0 include social networking sites, blogs, wikis,

video sharing sites…etc.



3- Web 2.0 Cont’d

• With Web 1.0 technology a significant amount of software skills and investment in software was necessary to publish information. – Web 2.0 technology changed this dramatically.



Limitations of the Web 2.0

• The current Web has its limitations when it comes to:1. finding relevant information

2. extracting relevant information

3. combining and reusing information



1-Finding relevant information



1-Finding relevant information Cont’d

• Finding information on the current Web is based on keyword search• Keyword search has a limited recall and precision due to:

– Synonyms: • e.g. Searching information about “Cars” will ignore Web pages that

contain the word “Automobiles” even though the information on these pages could be relevant

• Check Google for Car and Automobile

– Homonyms:• e.g. Searching information about “Jaguar” will bring up pages containing

information about both “Jaguar” (the car brand) and “Jaguar” (the animal) even though the user is interested only in one of them

https://www.google.com.tr/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=car

https://www.google.com.tr/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=Automobile



1-Finding relevant information Cont’d

– Spelling variants:• e.g. “organize” in American English vs. “organise” in British English

– Spelling mistakes

– Multiple languages• i.e. information about same topics in published on the Web on different

languages (English, German, Italian,…)

• Current search engines provide no means to specify the relation between a resource and a term– e.g. sell / buy



2-Extracting relevant information

• One-fit-all automatic solution for extracting information from Web pages is not possible due to different formats, different syntaxes

• Even from a single Web page is difficult to extract the relevant information

Which book is about the Web?

What is the priceof the book?



2-Extracting relevant information Cont’d

• Extracting information from current web sites can be done using wrappers

WEBHTML pages

Layout

Structured Data,Databases,

XMLStructure

Wrapper

extractannotatestructure



2-Extracting relevant information Cont’d

• The actual extraction of information from web sites is specified using standards such as XSL Transformation (XSLT)

• Extracted information can be stored as structured data in XML format or databases.

• However, using wrappers do not really scale because the actual extraction of information depends again on the web site format and layout



3-Combining and reusing information

• Tasks often require to combine data on the Web1. Searching for the same information in different digital libraries

2. Information may come from different web sites and needs to be combined




Example – Let’s organize a trip from Famagusta to Budapest using the Web!

– You try to:




– You try to find a proper flight with:… a big, reputable airline, or …




– You try to find a proper flight with:… the airline of the target country, or …




– You try to find a proper flight with:… … or a low cost one




– Then, you have to find a hotel, so you look for…




– Then, you have to find a hotel, so you look for… a really cheap accommodation, or




– Then, you have to find a hotel, so you look for… or a really luxurious one, or …




– Then, you have to find a hotel, so you look for… an intermediate one …




– Oops!! That is no good, the page is in Hungarian that almost nobody understands, but…




– Of course, you could decide to trust a specialized site… like this




– Of course, you could decide to trust a specialized site… or this




– You may want to know something about Budapest; look for some photographs… Flickr or Google images or a (social) travel site




• So, what happened here? You had to consult a large number of sites, all different in style,

purpose, possibly language… You had to mentally integrate all those information to achieve your

goals We all know that, sometimes, this is a long and tedious process!



How to improve current Web?

• Increasing automatic linking among data• Increasing recall and precision in search• Increasing automation in data integration• Increasing automation in the service life cycle

• Solution? Adding semantics to data and services!



What is the Semantic Web?

• “The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.”

T. Berners-Lee, J. Hendler, O. Lassila, “The Semantic Web”, Scientific American, May 2001



• Semantics = meaning (from Greek)• Set of practices and standards• Synonymous or related to:

– Web of data

– Linked data (cloud)

– Giant Global Graph (GGG)

– Web 3.0

– Open Data

– Big Data

• Tim Berners-Lee has described the semantic web as a component of "Web 3.0".

What is the Semantic Web? Cont’d

https://en.wikipedia.org/wiki/Tim_Berners-Lee



What is the Semantic Web? Cont’d

• So it is:– The next generation of the WWW

– Information has machine-processable and machine-understandable semantics

– Ease sharing and mixing data

– Not a separate Web but an augmentation of the current one

– The backbone of Semantic Web are ontologies



Ontology definition

• Ontologies are the modeling foundations to Semantic Web– They provide the well-defined meaning for information

formal, explicit specification of a shared conceptualization

commonly accepted understanding

conceptual model of a domain

(ontological theory)

unambiguous terminology definitions

machine-readability with computational

semantics



Ontology example

• Concept – conceptual entity of the domain

• Property – attribute describing a concept

• Relation – relationship between concepts or properties

• Axiom – coherency description between Concepts /

Properties / Relations via logical expressions

Person

Student Professor

Lecture

isA – hierarchy (taxonomy)

name email

matr.-nr. researchfield

topiclecturenr.

attends holds

holds(Professor, Lecture) =>Lecture.topic = Professor.researchField



Semantic Web of Data

1. Web Data Annotation

2. Data Linking on the Web (Web of Data)

3. Data Integration over the Web



1-Web Data Annotation– connecting (syntactic) Web objects, like text chunks, images,

… to their semantic notion • e.g., this image is about Famagusta, Nazife Dimililer is a

professor



2-Data Linking on the Web

– global networking of knowledge through URI, RDF, and SPARQL • e.g., connecting my calendar with my rss feeds, my pictures, ...

LinkedCT



2-Data Linking on the Web (Web of Data) Cont’d

• Linked Open Data statistics:– data sets: 123

– total number of triples: 19.562.409.691

– total number of links between data sets: 142.605.717

• Statistics available at: (These pages were last modified on 23 September 2010!)

– http://esw.w3.org/topic/TaskForces/CommunityProjects/LinkingOpenData/DataSets/Statistics

– http://esw.w3.org/topic/TaskForces/CommunityProjects/LinkingOpenData/DataSets/LinkStatistics

• Newest Statistics available at: http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData

http://esw.w3.org/topic/TaskForces/CommunityProjects/LinkingOpenData/DataSets/Statistics

http://esw.w3.org/topic/TaskForces/CommunityProjects/LinkingOpenData/DataSets/LinkStatistics

http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData



2-Data Linking on the Web (Web of Data) Cont’d

• The DBpedia Data Set (2015-04) statistics:– provides localized versions in 128 languages

– Altogether the DBpedia 2015-04 release consists of 6.9 billion pieces of information (RDF triples)

• out of which 737 million were extracted from the English edition of Wikipedia, 3.76 billion were extracted from other language editions and 2.4 billion from DBpedia Commons and Wikidata.



3-Data Integration over the Web

• Data integration involves combining data residing in different sources and providing user with a unified view of these data

• Data integration over the Web can be implemented as follows:1. Export the data sets to be integrated as RDF graphs

2. Merge identical resources (i.e. resources having the same URI) from different data sets

3. Start making queries on the integrated data, queries that were not possible on the individual data sets.

Example (next slide)



3-Data Integration over the Web Cont’d

1.Export first data set as RDF graphWe have a book with titled “The Glass Palace” by author Amitav Ghosh and in English.

Export it to RDF graphs




1.Export second data set as RDF graphInformation about the same book but in French this time is modeled in RDF graph below




2.Merge identical resources (i.e. resources having the same URI) from different data sets

Same URI = Same resource




2.Merge identical resources (i.e. resources having the same URI) from different data sets




3.Start making queries on the integrated data– A user of the second dataset may ask queries like: “give me the title of

the original book”

– This information is not in the second dataset!

– This information can be however retrieved from the integrated dataset, in which the second dataset was connected with the first dataset



Semantic Web Architecture and Languages

• Requirements– Extensibility

• Each layer should extend the previous one(s)

– Support for data interchange• Using data from one source in other applications

– Support for ontology description with different complexity• Including rules

– Support for data query

– Support for data provenance and trust evaluation



Semantic Web Stack ( or building blocks)



UNICODE, URI and XML

• UNICODE is the standard international character set– E.g. used to encode the data in the repository

• ASCII –7 bit, 128 characters (a-z, A-Z, 0-9, punctuation

• Extension code pages –128 chars (ß, Ä, ñ, ø, Š, etc.)– Different systems, many different code pages

– ISO Latin 1, CP1252 –Western languages(197 = Å)

– ISO Latin 2, CP1250 –East Europe(197 = Ĺ)

• Code page is an interpretation, not a property of text– Thus if we do not interpret correctly the code page, the result visualized will

not be the expected one



UNICODE, URI and XML Cont’d

• Uniform Resource Identifiers (URIs) identify things and concepts– E.g. used to identify resources on the Web and in the repository

• URI Syntax scheme: [//authority] [/path] [?query] [#fragid]

– (Almost) everyting is a URI

• Example URIs:– “Normal” URIs

• http://www.example.com/id/bob

• http://www.example.com/people/bob.html

• urn:isbn:1898432023

• http://xmlns.com/foaf/0.1/firstName

– Hash URIs• http://www.example.com/about#alice



UNICODE, URI and XML Cont’d

• eXtensible Markup Language (XML) is a markup language used for data exchange– Language for creating languages

– “Meta-language”

– XHTML is a language: HTML expressed in XML• E.g. format that can be wrapped into RDF and imported into the

repository

– Examples:• <temperature unit="F">64</temperature>

• <swearword language='fr'>con</swearword>



RDF, RDFS and OWL

• Resource Description Framework (RDF) is the HTML of the Semantic Web– Simple way to describe resources on the Web

– Based on triples <subject, predicate, object> (and quads <context>)

• Various serializations, including one based on XML (RDF/XML, Turtle,N3…etc)

• Facts and relations organized in triples• Triples mimic natural language sentences• Graphical representation is a directed graph• Example

– My name is Karwan Jacksi.

– My age is 31.

– I work for BadinanSoft Company.



RDF, RDFS and OWL Cont’d

• Example

ex:kjacksi

Karwan Jacksi

31

foaf:ageldif:company

foaf:fullName

ex:BadinanSoft



RDF, RDFS and OWL

• Another Example:– <ex:john, ex:father-of, ex:bill>

– <#john, rdf:type, #Student>

• What is a “#Student”?• RFD is not defining a vocabulary about the statements, but only to

express statements• We know that “#Student” identifies a category (a concept or a

class), but this is only implicitly defined in RDF




• We need a language for defining RDF types:– Define classes:

• “#Student is a class”

– Relationships between classes:• “#Student is a sub-class of #Person”

– Properties of classes:• “#Person has a property hasName”

• So, RDF Schema (RDFS) is such a language

Person

Student Professor

Lecture

isA – hierarchy (taxonomy)

name email

matr.-nr. researchfield

topiclecturenr.

attends holds




• Web Ontology Language (OWL) is a more complex ontology language than RDFS– Layered language based on Description Logic

– Overcomes some RDF(S) limitations

• Common ontologies– Friend of a Friend (foaf)

– Dublin Core

– SIOC

– SKOS

– …




• In-depth RDFS/OWL example

ex:Karwan rdf:type foaf:Person .foaf:Person rdf:type rdfs:Class .

ex:Karwan foaf:age “31"^^xsd:int .ex:Karwan foaf:name "Karwan " .ex:Karwan foaf:lastName “Jacksi" .ex:Karwan owl:sameAs cs:Karooo .

cs:Karooo foaf:currentProject cs:SemSearchEngine.



SPARQL and Rule Languages

• SPARQL – SPARQL Protocol and RDF Query Language– A protocol for querying RDF data over the Web

– A language used to query the repository (RDF triples) from user interface• E.g. What are all the country capitals in Africa?

• Rule languages (esp. Rule Interchange Format RIF) – Extend ontology languages with proprietary axioms

– Based on different types of logics• Description Logic

• Logic Programming

– E.g. used to enable reasoning over data to infer new knowledge

PREFIX abc: <http://example.com/exampleOntology#> SELECT ?capital ?country WHERE {

?x abc:cityname ?capital ; abc:isCapitalOf ?y . ?y abc:countryname ?country ; abc:isInContinent abc:Africa . }

holds(Professor, Lecture) =>Lecture.topic = Professor.researchField



Logics, Proof and Trust

• Unifying logic– Bring together the various ontology and rule languages– Common inferences, meaning of data

• Proof– Explanation of inference results, data provenance

• Trust– Trust that the system performs correctly– Trust that the system can explain what it is doing– Network of trust for data sources and services– Technology and user interface



Tools for semantic web

• The Semantic web tools can be grouped according to their purpose 1. the ontology Editors are used for data modeling

• The visualization and editing of Ontologies are added to be the extensions of Ontology Editors.

2. the Reasoner for the notion of generalized Inference mechanism.

3. the Plugin and APIs that can set up the Semantic web development environment.



Ontology Editor

• The Ontology Editors are used for creating a data model for the underlying Semantic web Application – It favours manipulating the available ontologies for access.

• The ontologies are constructed using standard Ontology languages. • The Ontology Languages are formal languages that depends with

reasoning rules for framing these ontologies • The Ontology Languages are classified either by syntax or structure.

– The Syntax oriented Ontology Languages like OWL, RDF and OIL are more prevalent ontology languages.

– The Ontology Editors can be classified based on the type of ontology languages used.



Ontology Editor Cont’d

• Protege (today) http://protege.stanford.edu

• Neon Toolkit: www.neon-toolkit.org• myOntology: www.myontology.org• Semantic Media Wiki

– HALO extension http://www.mediawiki.org/wiki/Extension:Halo_Extension

– Ontology editor extension http://smw-active.sti-innsbruck.at

• DOGMA Modeler http://starlab.vub.ac.be/website/node/47• OntoStudio http://www.ontoprise.de/ • TopBraid Composer http://www.topbraidcomposer.com/

http://protege.stanford.edu/

http://protege.stanford.edu/

http://www.neon-toolkit.org/

http://www.neon-toolkit.org/

http://www.myontology.org/

http://www.mediawiki.org/wiki/Extension:Halo_Extension

http://smw-active.sti-innsbruck.at/

http://starlab.vub.ac.be/website/node/47

http://www.ontoprise.de/

http://www.topbraidcomposer.com/



Reasoner

• The Inference mechanism on Reasoners are the rich capability provided to infer logical consequences from axioms.

• These Logical consequences are nothing but the relationship between statements that are true, where axioms are the statements which are accepted to be true without controversy.



Reasoner Cont’d

• AllegroGraph http://agraph.franz.com/ • Fact http://www.cs.man.ac.uk/%7Ehorrocks/FaCT/ • Pellet http://clarkparsia.com/pellet • Racer http://www.racer-systems.com/ • IRIS http://www.sti-innsbruck.at/ • OWLIM http://http//ontotext.com/owlim/ • KAON http://kaon2.semanticweb.org/

http://agraph.franz.com/

http://www.cs.man.ac.uk/~horrocks/FaCT/

http://clarkparsia.com/pellet

http://www.racer-systems.com/

http://www.sti-innsbruck.at/

http://http/ontotext.com/owlim/

http://kaon2.semanticweb.org/



Plugin and API

• The Application Programming Interface (API) is a set of protocols, and tools for building software applications. – It favors easier development of a program by providing necessary

building blocks and assembling these building blocks is the remaining part to work.

• The APIs are more useful for users than programmers. – Since, they provide a common API with similar interface for all

programs.

• This leads to an easier learning task for even naïve users.



Plugin and API Cont’d

• The plug-ins are a set of software components used for adding specific abilities to a larger software application. – For Example, Pellet Reasoner Plugins are added in Eclipse IDE for

inferring the relationships.



Plugin and API Cont’d

• Jena API – The Jena API is a well known Semantic web platform among Java

framework for building Semantic Web applications.

– It includes wide range of java libraries that help developers to develop code easier.

– The first approach of developing Jena was underwent by researchers in HP Labs by 2000.

– Jena is an open-source project, and has been used in a wide variety of semantic web applications.

– In 2010, Jena was adopted by the Apache Software Foundation



Is it happening?

Linked data and open data

• Dbpedia• Freebase• Geonames• Social data• Media• Government data• Publications• Many many other

• datahub.io• lod.openlinksw.com• data.gov• data.gov.uk• datadotgc.ca• openlibrary.org• bnb.data.bl.uk



Who does the Semantic Web?

IBM

• IBM DB2• Open Services Lifecycle

Collaboration• Linked Data Platform

Oracle

• Oracle 11g– Triplestore

– Reasoner




Google

• Webmaster tools• Knowledge graph• Freebase• RDFa/Microdata (also Yahoo)

Facebook

• Open Graph Protocol




Government/public data

• Thousands of datasets• Some offered in RDF• Linked by Linking Open

Government Data project• (200 datasets)

• Open Government Partnership (50+ countries)

Academic work

• Gene research• Language processing• Semantic MediaWiki




• The State of the LOD Cloud 2011– Graph view:

http://lod-cloud.net/versions/2011-09-19/lod-cloud_colored.html

• The State of the LOD Cloud 2014 – Graph view

http://linkeddatacatalog.dws.informatik.uni-mannheim.de/state/LODCloudDiagram.html

http://lod-cloud.net/state

http://lod-cloud.net/versions/2011-09-19/lod-cloud_colored.html

http://linkeddatacatalog.dws.informatik.uni-mannheim.de/state/





Summery

• Semantic Web is not a replacement of the current Web, it’s an evolution of it

• Semantic Web is about:– annotation of data on the Web

– data linking on the Web

– data Integration over the Web

• Semantic Web aims at automating tasks currently carried out by humans

• Semantic Web is becoming real!



Good Videos

• Evolution Web 1.0, Web 2.0 to Web 3.0• https://www.youtube.com/watch?v=bsNcjya56v8

• Web today -Web 2.0• https://www.youtube.com/watch?v=6gmP4nk0EOE

• The Future Internet: Service Web 3.0• https://www.youtube.com/watch?v=off08As3siM

• Web 3.0 - The Internet of Things!• https://www.youtube.com/watch?v=F_nbUizGeEY

• Web 3.0• http://www.sti-innsbruck.at/results/movies/web-30

https://www.youtube.com/watch?v=bsNcjya56v8

https://www.youtube.com/watch?v=6gmP4nk0EOE

https://www.youtube.com/watch?v=off08As3siM

https://www.youtube.com/watch?v=F_nbUizGeEY

http://www.sti-innsbruck.at/results/movies/web-30



References

• A Survey of Exploratory Search Systems Based On LOD Resources– Karwan Jacksi, Nazife Dimililer and Subhi R. M. Zeebaree / Proceedings of the 5th ICOCI 2015

• A Survey on Tools Essential for Semantic Web Research – International Journal of Computer Applications (0975 – 8887) Volume 62– No.9, January 2013

• A Review on Semantic-Based Web Mining and its Applications– Sivakumar J et al. / International Journal of Engineering and Technology (IJET)

• Wikipedia– https://en.wikipedia.org/wiki/Internet

– https://en.wikipedia.org/wiki/Memex

– https://en.wikipedia.org/wiki/Integrated_circuit

– https://en.wikipedia.org/wiki/Mosaic_(web_browser)

– https://en.wikipedia.org/wiki/World_Wide_Web

– https://en.wikipedia.org/wiki/Web_2.0

– http://en.wikipedia.org/wiki/Semantic_Web

– https://en.wikipedia.org/wiki/Amazon_Mechanical_Turk

– http://en.wikipedia.org/wiki/Resource_Description_Framework

– http://en.wikipedia.org/wiki/Linked_Data

https://en.wikipedia.org/wiki/Internet

https://en.wikipedia.org/wiki/Memex

https://en.wikipedia.org/wiki/Integrated_circuit

https://en.wikipedia.org/wiki/Mosaic_(web_browser)

https://en.wikipedia.org/wiki/World_Wide_Web

https://en.wikipedia.org/wiki/Web_2.0

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

https://en.wikipedia.org/wiki/Amazon_Mechanical_Turk

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

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



References

• Other Links– http://www.w3.org/TR/xslt

– http://www.ontoprise.de

– http://linkeddata.org

– http://www.w3.org/People/Ivan/CorePresentations/SWTutorial/Slides.pdf

– http://sti-innsbruck.at/sites/default/files/courses/01_SW-Introduction.pdf

– http://facweb.cs.depaul.edu/mobasher/classes/it130/internet-www/index.html

– http://dbpedia.org/services-resources/datasets/data-set-38/data-set-statistics

– chrome-extension://gbkeegbaiigmenfmjfclcdgdpimamgkj/views/app.html

– http://www.slideshare.net/tpluskiewicz/introduction-to-the-semantic-web-16024553

http://www.w3.org/TR/xslt





http://linkeddata.org/

http://linkeddata.org/

http://www.w3.org/People/Ivan/CorePresentations/SWTutorial/Slides.pdf

http://www.w3.org/People/Ivan/CorePresentations/SWTutorial/Slides.pdf

http://facweb.cs.depaul.edu/mobasher/classes/it130/internet-www/index.html





http://dbpedia.org/services-resources/datasets/data-set-38/data-set-statistics

http://dbpedia.org/services-resources/datasets/data-set-38/data-set-statistics

chrome-extension://gbkeegbaiigmenfmjfclcdgdpimamgkj/views/app.html



http://www.slideshare.net/tpluskiewicz/introduction-to-the-semantic-web-16024553

http://www.slideshare.net/tpluskiewicz/introduction-to-the-semantic-web-16024553



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