Semantic Web Technologies - 01 - From Internet to the Web of Data

Semantic Web Technologies

Lecture Blog: http://semweb2013.blogspot.com/This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0)

LectureDr. Harald Sack

Hasso-Plattner-Institut für IT Systems EngineeringUniversity of Potsdam

Winter Semester 2012/13

Donnerstag, 18. Oktober 12

Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam

1. Introduction 2. Semantic Web - Basic Architecture

Languages of the Semantic Web - Part 1

3. Knowledge Representation and LogicsLanguages of the Semantic Web - Part 2

4. Applications in the ,Web of Data‘

2

Semantic Web Technologies Content



3 1. Introduction • From Internet to Web 2.0

...from a historical point of view

• Quo Vadis WWW? ...the limits of the WWW

• Semantic Web...towards an ,intelligent‘ WWW

• Semantic Web Applications...the semantic WWW begins




4



5

ARPANET29. October 1969


J.C.R. Licklider, Robert Taylor: "The Computer as a Communication Device". Science and Technology 76, pp. 21-31, April 1968.

"[...] we are entering a technological age in which we will be able to interact with the richness of living information - not merely in the passive way that we have been accustomed to using books and libraries, but as active participants in an ongoing process, bringing something to it through our interaction with it, and not simply receiving something from it by our connection to it."

J.C.R. LickliderARPA IPTO Director

(1962-1964)

Robert TaylorARPA IPTO Director

(1966-1969)

Larry RobertsARPA IPTO Chief Scientist

(1966-1973)


http://www.kurzweilai.net/the-computer-as-a-communication-device

http://www.kurzweilai.net/the-computer-as-a-communication-device


6 Es war einmal....das Internet

Larry RobertsARPA IPTO Chief Scientist

(1966-1973)

Semantic Web Technologies From Internet to Web 2.0



7 • How did the user get the information?

1. open terminal2. connect to remote computer3. retrieve file system data from

remote computer4. download file from remote to

local computer5. read file on local computer

Problem:• Information access requires expert knowledge• Information access is expensive...• Information Retrieval is very expensive...

First Generation: The Internet Computer Centered Processing



8

The World Wide Web was born at the European Nuclear Research CenterCERN in 1990...

Tim Berners-Lee

Robert Cailliau



9 • How did the user get the information?

Advantages:• No expert knowledge required• Simple information access• Information retrieval via search engines

Second Generation: The Web Document Centered Processing

1. open browser2. load document3. click on next hyperlink4. ...

Dokument

Dokument

Dokument

Dokument

Dokument

Hyperlink

Hyperlink Hyperlink

Hyperlink

HyperlinkHy

perlink



10

• But the original idea behind theWWW is much older.....

Denis Diderot(1713-1784)

Jean-Baptiste le Rond

d'Alembert (1717-1783)



11

Agostino Ramelli (1588), Le diverse et artificiose machine;

composte in lingua Italiana et Francese



11

Agostino Ramelli (1588), Le diverse et artificiose machine;

composte in lingua Italiana et Francese

Usabilit

y...?



12

Vannevar Bush(1890-1974)

vgl. Vannevar Bush, As we may think ,The Atlantic Monthly, 1945, July

Vannevar Bush proposed the firstHypertext-System „MEMEX“ in 1945



13

Why was the Web such a big success ?

Lynx 1993




14

NCSA Mosaic 1994




15

IPadSafari 2010



16

http://www.isc.org/(Stand: 10/2012)

There seem to be no Limits of Growth...



17

Information Consumption

Information Production

Interactive Participation

908,585,739

From Web 1.0 to Web 2.0 Web Content and Applications are Changing



18

Web Content and Roles are Changing... Web 2.0 is thebusiness revolution inthe computer industrycaused by the move tothe Internet as

platform, and anattempt to understandthe rules for successon that new platform " -- Tim O'Reilly, 2003



19


1. Introduction • From Internet to Web 2.0







20

How can we find somethingin the Web?



current solution:

21



The Web is big. Really big. You just won't believe how vastly, hugely, mind-bogglingly big it is.(...according to Douglas Adams)

22



The Web is really big...•ca. 25 x 109 indexed documents in search engines

(TNL Blog: Google has 24 billion items index, considers MSN search nearest competitor, September 2005)

•Web Crawler: > 1012 (1 trillion) documents(The Official Google Blog: We knew the Web was Big....., Juli 25, 2008)

•Google Search Index Caffeine comprises ca.100 Million Gigabytes i.e. 1017 Byte (SMX Video: Google’s Matt Cutts On Caffeine Launch, June 9, 2010,http://searchengineland.com/smx-video-googles-matt-cutts-on-caffeine-launch-43933)

•DeepWeb (Darkweb) estimated to be about 550 times bigger than Surface Web (Bergman, 2001)

23


http://www.tnl.net/blog/2005/09/27/google-has-24-billion-items-index-considers-msn-search-nearest-competitor/




http://googleblog.blogspot.com/2008/07/we-knew-web-was-big.html

http://googleblog.blogspot.com/2008/07/we-knew-web-was-big.html

http://searchengineland.com/smx-video-googles-matt-cutts-on-caffeine-launch-43933

http://searchengineland.com/smx-video-googles-matt-cutts-on-caffeine-launch-43933

Dr. Harald Sack, Hasso-Plattner-Institut Potsdam, Workshop: Interaktion und Visualisierung im Datenweb (IVDW 2012), Braunschweig, 20.09.2012

...and it‘s getting bigger every minute!



http://www.visualnews.com/2012/06/19/how-much-data-created-every-minute/



http://www.visualnews.com/2012/06/19/how-much-data-created-every-minute/



26 Multimedia, Real-Time Data, Sensor Data, ....

Semantic Web Technologien Quo vadis WWW ?



27 Multimedia, Real-Time Data, Sensor Data, ....

Semantic Web Technologien Quo vadis WWW ?


Vorlesung Semantic Web, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam

28

and all the things will connect with social networks...



29



29 • what is important and how do you know?

• what is information, what is advertisement?

• what does the information mean?

• how credible/trustworthy is the information?

• what belongs together?• what is redundant?

• Humans have contextual knowledge, world knowledge and experience to solve the problem

Information in the WWW



30

• The Web is supposed to be used by humans.• The Web is based on the markup language HTML

• HTML describes• how information is presented • how information is linked • but not, what the information means



31



32

Semantics (greek σεμαντικος = pertains to the character, the study of meaning) is part of the linguistics focussed on

•Sense and •Meaning

of language or symbols of language. It is the study of interpretation of signs or symbols as used by agents or communities within particular circumstances and contexts.

Semantics asks, how sense and meaning of complex concepts can be derived from simple concepts based on the rules of syntax.

The semantics of a message depends of its context and pragmatics.

Semantics



33

Syntax (greek σψνταξις = Arrangement, Ordering) as in grammatics denotes the study of the principles and processes by which sentences are constructed in particular languages.

• In formal Languages, syntax is just a set of rules, by which well formed expressions can be created from a fundamental set of symbols (alphabet).

• in computer science, syntax defines the normative structure of data.

Syntax


http://en.wikipedia.org/wiki/Sentence_(linguistics)

http://en.wikipedia.org/wiki/Sentence_(linguistics)

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

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


34

Context (lat. contextus = interweaved) denotes the surrounding of a symbol (concept) in an expression resp. its relationship with surrounding expressions (concepts) and further related elements,

Contexts denotes all elements of any sort of communication that define the interpretation of the communicated content, as e.g., • general contexts:

place, time, interrelation of action in a message• personal or social contexts:

relation between sender and receiver of a message

Context



35

Pragmatics (greek. πραγμα = action) reflects the intention by which the language is used to communicate a message.

In linguistics pragmatics denotes the study of applying language in different situations. Pragmatics studies the ways in which context contributes to meaning.

Pragmatics



36

In the (traditional) Web there is no explicit semantics.Donnerstag, 18. Oktober 12


37

Problem 1: Information RetrievalDonnerstag, 18. Oktober 12


37

Problem 1: Information Retrieval

• traditional keyword-based search leads to many not relevant results•different meanings•polysemy•different contexts

• traditional keyword-based search does not find all results•synonyms and metaphors•missing context definition



38

Problem 2: Information Extraction

•can only be solved ,correctly‘ by a human agent

•heterogeneous distribution and order of information

•Software agent does not have sufficient• knowledge of contexts•world knowledge and•experience

• to solve the problem


Problemfeld 2: Informationsextraktion


39

•implicit knowledge, i.e. information does not have specified explicitely, but must be derived via logical deductions from available information.



40

Problem 3: Maintenance

• the more complex and voluminous a website, the more complicated is the maintenance of the only weakly structured data.

•Problems:•syntactic and semantic (link)

consistency•correctness• timeliness



41

Problem 4: Personalization

•Adaption of the presented information content to personal requirements

•Problems: • from where do we get the

required (personal) information?

•personalization vs. data security



42

GAME OVER



43









44

Tim Berners-Lee, Semantic Web Roadmap, Sept 1998

„The Web was designed as an information space, with the goal that it should be useful not only for human-human communication, but also that machines would be able to participate and help… “

From World Wide Web to the Web of Data


http://www.w3.org/DesignIssues/Semantic.html

http://www.w3.org/DesignIssues/Semantic.html


45 Precondition:• Content can be read and

interpreted correctly (= „understood“) by machines

Natural Language Processing• Technologies of traditional

Information Retrieval (Search Engines)




46

Semantic Web• Natural language web content will

be explicitly annotated with semantic metadata

• Semantic metadata encode the Meaning (Semantics) of the content and can be read and interpreted correctly by machines


Precondition:• Content can be read and

interpreted correctly (= „understod“) by machines

Natural Language Processing• Technologies of traditional

Information Retrieval (Search Engines)


Semantic Web Technologies , Dr. Harald Sack, Hasso-Plattner-Institut, Universität PotsdamDonnerstag, 18. Oktober 12


48

„Understanding“ Content on the Web



49




49

Text: „Why snub me, Fab?“




49

• Disambiguationsolution of linguistic ambiguities





49

• Disambiguationsolution of linguistic ambiguities


Fabio Capello ?

Entity MappingDisambiguation

FAB ?

FAB ?

Manager of the UK national Football team

the Film Advisory Board

Federación Atlética de Bolivia

Fab Melo ? Brazilian Basketball Player

Fab ? a detergent

Fab ? a Canadian gay magazine

Fabrizio Moretti ? Drummer of The Strokes



http://en.wikipedia.org/wiki/Federaci%C3%B3n_Atl%C3%A9tica_de_Bolivia





50

Fabio Capello

Entity Mapping

Entity

• The Meaning (Semantics) of entitiesand classes must be defined explicitly.





50

Fabio Capello

Entity Mapping

Entity

Soccer Manager

is a

Class






50

Fabio Capello

Entity Mapping

Entity

Soccer Manager

is a

Class

Person

is subclass of

Class






51

Fabio Capello (entity)

Soccer Manager

is a

(class)

Class-membership has class

•The Meaning (Semantics) is expressed with the help of well suited knowledge representations (Ontologies)




51

Fabio Capello (entity)

Soccer Manager

is a

(class)

Class-membership has class

Person

is subclass of

(class)

superclass

subclass

is subclass of





52

Fabio Capello

Soccer Manager

Person

is aEntities

Classes

is subclass of

„Understanding“ Content on the Web (III)




52

Fabio Capello

Soccer Manager

Person PlacebirthPlace

is aEntities

Classes

is subclass of





52

Fabio Capello

Soccer Manager


is aEntities

Classes

is subclass of

San CanzianbirthPlace

is a





52

Fabio Capello

Soccer Manager


DatebirthDate

is aEntities

Classes

is subclass of


is a





52

Fabio Capello

Soccer Manager


DatebirthDate

is aEntities

Classes

is subclass of


is a

birthDate1946-06-18

is a





53

Tim Berners-Lee, James Hendler, Ora Lassila: The Semantic Web, Scientific American, 284(5), pp. 34-43(2001)

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"


http://www.bibsonomy.org/author/Berners-Lee

http://www.bibsonomy.org/author/Berners-Lee

http://www.bibsonomy.org/author/Hendler

http://www.bibsonomy.org/author/Hendler

http://www.scientificamerican.com/article.cfm?id=the-semantic-web

http://www.scientificamerican.com/article.cfm?id=the-semantic-web


54•The Meaning of Information (Semantics) is made explicit by

formal (structured) and standardized knowledge representations (Ontologies).

• Thus it will be possible,

•to process the meaning of information automatically

•to relate and integrate heterogeneous data

•to deduce implicite (not evident) information from existing (evident) information in an automated way

The Semantic Web is kind of a global database that contains a universal network of semantic propositions.

The Semantic Web - a Web of Data



55

Das Semantic Web

•

Semantic Web ...towards an „intelligent“ Web



56

Fabio Capello http://dbpedia.org/resource/Fabio_Capello

URI - Uniform Resource Identifier



http://dbpedia.org/page/Fabio_Capello



57

http://dbpedia.org/resource/Fabio_Capello

http://de.wikipediapedia.org/wiki/Fabio Capello





http://de.wikipediapedia.org/wiki/Lukas_Podolski

http://de.wikipediapedia.org/wiki/Lukas_Podolski


58







59


RDF Resource Description Framework

:Fabio_Capello dbpp:birthPlace :San_Canzian .:Fabio_Capello dbpp:birthDate “1946-06-18“ .:Fabio_Capello rdfs:type dbpo:SoccerManager .:Fabio_Capello rdfs:type dbpo:Person ....

:Fabio_Capello rdf:type dbpo:SoccerManager .

RDF Tripel RDF Subject RDF Property RDF Object






60

http://dbpedia.org/ontology/SoccerManager

dbpo:SoccerManager rdf:type owl:class .dbpo:SoccerManager rdfs:subClassOf dbpo:Person .dbpo:SoccerManager rdfs:label “SoccerManager“ .dbpp:birthPlace rdf:type rdf:Property .dbpp:birthPlace rdfs:domain dbpo:Person .dbpp:birthPlace rdfs:range dbpo:Place .dbpp:birthDate rdf:type rdf:Property .dbpp:birthDate rdfs:domain :Person .dbpp:birthDate rdfs:range xsd:date ....

RDF Schema


DatebirthDate

SoccerManager

is subclass of






61

Fabio Capello

LivingPeople

PersonDate

birthDate1946-06-18

birthDate

is a

is a

is subclass of

DeadPeople∩ =∅

logical constraintis subclass of

+ Rules (Description Logics)

∀x.∃y.hasDeathDate(x,y) ∧ Person(x) ∧ Date(y) → DeadPeople(x)

entities

classes




62

SELECT DISTINCT ?l ?l2 ?g FROM <http://dbpedia.org> WHERE { ?s rdf:type dbpo:SoccerPlayer . ?s dbpp:nationalteam ?o . ?s rdfs:label?l FILTER langMatches( lang(?l), "EN" ) . ?s dbpp:nationalgoals ?g FILTER(?g>10). ?s dbprop:nationalteam ?nat . ?nat rdfs:label ?l2 FILTER langMatches( lang(?l2), "EN" ) .} ORDER BY DESC(?g)

Look for all Soccer Playersthat have scored more than 10 goals as member of anational team.



http://dbpedia.org

http://dbpedia.org

http://dbpedia.org/property/nationalteam

http://dbpedia.org/property/nationalteam


63


Look for all Soccer Players that have scored more than 10 goals as member of a national team.



64

Problem: Data Quality....

Look for all Soccer Players that have scored more than 10 goals as member of a national team.




65









66 Linked Data□ Linked Open Data (LOD) denote publicly available (RDF) Data in the Web, identified via

URI and accessable via HTTP. Linked data link to other data via URI.

Semantic Web Technologies Semantic Web Applications

The ,Web of Data‘• >31 billion facts• >500 million links

(Oct. 2011)



67

http://www.bbc.co.uk/music





68

What is so special about the BBC Music Website?• Information is dynamically aggregated from

external, publicly available data (Wikipedia, MusicBrainz,...)

• no Screen Scraping• no specialized API• data available als Linked Open Data• data access via simple HTTP Request• data is always up-to-date without manual

interaction



69

Search Engines - Document Retrieval•Search Engine Query String: “Jaguar of 2000“



69

• Refine ,jaguar‘ CAR or ANIMAL or OPERATINGSYSTEM etc. ?Refine: CAR




70

• Name: Jaguar E Type• Category: Car• ...• ConstructionYear <Integer>• technicalParameter• CylinderCapacity <Integer>• Power <Integer>• ...

• ...

Knowledge Representation(Ontologie, Linked Data)




70

•Refine ,2000‘ ConstructionYear or technicalParameter ?Refine: ConstructionYear

• Name: Jaguar E Type• Category: Car• ...• ConstructionYear <Integer>• technicalParameter• CylinderCapacity <Integer>• Power <Integer>• ...

• ...

Knowledge Representation(Ontologie, Linked Data)




71Search Engines - Document Retrieval• General Problems:

• correct interpretation of query string

• correct identification of entities

• automatic disambiguation

• usability

• personalization



72

Search Engines - Fact Retrieval•Query String:

“Where can I fill up the tank at a considerable discount?“

Answer : - Hohenfelden, xy-Str. 32 -> Super leaded, 1,99 € - fuel-efficient route will be passed to navigation - drive only at half throttle for saving fuel…



73

dbpedia-owl:mission

dbpedia:Neil_Armstrong

dbpedia:Apollo_11dbpedia-owl:mission

category:Apollo_program

dcterms:subject

dbpedia:Apollo_13

dcterms:subject

yago:Space_accidents_and_incidents

rdf:type

rdf:type

dbpedia:Space_Shuttle_Challenger

dbpedia-owl:mission

dbpedia:Buzz_Aldrin

dbpedia:Michael_Collins

Search Engines - Exploratory Search



74

Intelligent Agents in the Semantic Web

User

retrieval service(e.g. Google)

WWW documents

presentation service(e.g. Firefox)

WWW



74

Intelligent Agents in the Semantic Web

User

retrieval service(e.g. Google)

WWW documents

presentation service(e.g. Firefox)

WWW

WWW documents

SemanticWeb

User

personalassistant

intelligentinfrastructure

services



75

3 Generations of Web Documents

staticweb pages

HTML / CSS

1. Generation



75


staticweb pages

HTML / CSS

1. Generation

interactiveweb pages

dynamischeweb pages

JavaScript / Applets

Data Base AccessTemplate-based

Generation

2. Generation



75


staticweb pages

HTML / CSS

1. Generation

interactiveweb pages

dynamischeweb pages

JavaScript / Applets

Data Base AccessTemplate-based

Generation

2. Generation

adaptiveweb pages

virtualweb pages

User ModelsMachine Learning

Online Layout

NetbotsInformation ExtractionPresentation Planning

3. Generation



76 Toolbox for the Semantic Web•Standardized languages to express semantics of information content

in the Web (XML/XSD, RDF(S), OWL, RIF)•Tools to use semantic information in the Web (RDFa, GRDDL, ...)

•Various fields of computer science:• artificial intelligence

• linguistics

• cryptography

• data bases

• theoretical computer science

• computer architecture

• software engineering

• systems theory

• computer networks



77









78

Next Lecture...

URI/URL - Designator and Designated

Brushup your XML and XML Schema...

Resource Description Framework



79

• P. Hitzler, S. Roschke, Y. Sure: Semantic Web Grundlagen, Springer, 2007.

• P. Hitzler, M. Krötzsch, S. Rudolph:Foundations of Semantic Web Technologies,CRC Press, 2009.

Semantic Web Technologies Bibliography


http://www.amazon.de/gp/product/3540339930/ref=as_li_ss_tl?ie=UTF8&tag=moresemantic-21&linkCode=as2&camp=1638&creative=19454&creativeASIN=3540339930


http://www.amazon.de/gp/product/142009050X/ref=as_li_ss_tl?ie=UTF8&tag=moresemantic-21&linkCode=as2&camp=1638&creative=19454&creativeASIN=142009050X

http://www.amazon.de/gp/product/142009050X/ref=as_li_ss_tl?ie=UTF8&tag=moresemantic-21&linkCode=as2&camp=1638&creative=19454&creativeASIN=142009050X


80

• T. Heath, Ch. BitzerLinked Data - Evolving the Web into a Global Data Space,Morgan & Claypool, 2011.

Semantic Web Technologies Bibliography




Lecture Semantic Web Technologies, Dr. Harald Sack, Hasso-Plattner-Institut, Universität Potsdam

81

□Bloghttp://semweb2013.blogspot.com/

□Webseitehttp://www.hpi.uni-potsdam.de/studium/lehrangebot/itse/veranstaltung/semantic_web_technologien-3.html

□bibsonomy - Bookmarkshttp://www.bibsonomy.org/user/lysander07/swt1213_01

Semantic Web Technologies Further Reading


http://semweb2013.blogspot.com

http://semweb2013.blogspot.com

http://www.hpi.uni-potsdam.de/studium/lehrangebot/itse/veranstaltung/semantic_web_technologien-3.html






http://www.bibsonomy.org/user/lysander07/swt1213_01




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Semantic Web Technologies - 01 - From Internet to the Web of Data

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