06 Linked Data Engineering - 1

Information Service Engineering , Prof. Dr. Harald Sack, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure & AIFB - Karlsruhe Institute of Technology

Information Service Engineering Lecture 6: Linked Data Engineering - 1

Prof. Dr. Harald SackFIZ Karlsruhe - Leibniz Institute for Information InfrastructureAIFB - Karlsruhe Institute of Technology

Summer Semester 2017

This file is licensed under the Creative Commons Attribution-NonCommercial 3.0 (CC BY-NC 3.0)

http://creativecommons.org/licenses/by-nc/3.0/


Information Service EngineeringLast Lecture: Natural Language Processing (4)

2.1 NLP and Basic Linguistic Knowledge

2.2 NLP Applications

2.3 NLP Techniques

2.4 NLP Challenges

2.5 Evaluation, Precision and Recall

2.6 Regular Expressions

2.7 Finite State Automata

2.8 Tokenization

2.9 Language Model and N-Grams

2.10 Part-of-Speech Tagging

● Language Model and N-grams● Markov Assumption● Text Corpora● Maximum Likelihood Estimation● Average Branching Factor● Smoothing● POS-Tagging● Word Categories● Hidden Markov Models


Information Service Engineering

3. Linked Data Engineering


Information Service EngineeringLecture 6: Linked Data Engineering - 1

3.1 Knowledge Representations and Ontologies

3.2 Semantic Web and the Web of Data

3.3 Linked Data Principles

3.4 How to name Things - URIs

3.5 Resource Description Framework (RDF) as simple Data Model

3.6 Creating new Models with RDFS

3.7 Querying RDF(S) with SPARQL

3.8 More Expressivity with Web Ontology Language (OWL)

3.9 Wikipedia, DBpedia, and Wikidata

3.10 Linked Data Programming


Understanding Information

PLUTO

Never Forget!

(1930-2006)

https://solarsystem.nasa.gov/multimedia/gallery/01_Stern_03_Pluto_Color_TXT.jpg

Information Service Engineering , Prof. Dr. Harald Sack, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure & AIFB - Karlsruhe Institute of Technologyhttps://solarsystem.nasa.gov/multimedia/gallery/01_Stern_03_Pluto_Color_TXT.jpg

PLUTO

Never Forget!

(1930-2006)


Text: ”Pluto“

Entity MappingDisambiguation

Pluto a Disney cartoon character

Pluto a Roman god

Pluto a song by Björk

HMS Pluto a shipDisambiguation

● solution of linguistic ambiguities

Pluto a dwarf planet

...

Information Understanding

3. Linked Data Engineering / 3.1 Knowledge Representations and Ontologies


Text: ”Pluto“

Entity Mapping

Pluto Entity

Dwarf Planet

is a

Class

Planet

is a subclass of

Class

● The Meaning (Semantics)

of entities and classes must

be defined explicitly.




Pluto

Dwarf Planet

Planet

is a subclass of

● The Meaning (Semantics) is expressed with the help of

knowledge representations (Ontologies)

Natural Object

Astronomical Objectsdiscovered in 1930

CelestialBody

Minor Planets visited by Spacecraft

(more classes)

is a

is a subclass ofis a

is a

Logical Inference




Pluto

Planet

● The Meaning (Semantics) is expressed with the help of

knowledge representations (Ontologies)

name string

radius integer

discovered date / time

discoverer Person

is a

domain range

range

range

range

domain

domain

domain

classes classesproperties




What is Knowledge?


BeliefsTruths

Knowledge

Traditional Definition: „Knowledge is a subset of all true beliefs“

To represent knowledge, we need a formal knowledge representation => Ontologies


Ontologies in Computer Science


"An ontology is an explicit, formal specification of a shared conceptualization. The term is borrowed from philosophy, where an Ontology is a systematic account of existence. For AI systems, what ‘exists’ is that which can be represented.“

according to Thomas R. Gruber: A Translation Approach to Portable Ontology Specifications.Knowledge Acquisition, 5(2):199-220, 1993.

conceptualization: abstract model (domain, identified relevant concepts, relations)

explicit: meaning of all concepts must be defined

formal: machine understandable

shared: consensus about ontology


How to represent Ontologies?


● Ontologies can be represented via Classes, Relations and Instances● Classes are abstract groups, sets, or collections of objects and

represent ontology concepts● Classes are characterised via attributes ● Attributes are name-value pairs

„The address contains the name, title,and place of residence of the personaddressed“

informal description

Address• given name <string>• family name <string>• street <string>• ZIP code <int>• city <string>• …

semi-formal description




● Classes can be related to other classes● Relations are special attributes, whose values are objects of (other)

classes

Celestial Body

Planet Artificial Satellite

Space Mission

Name

Mission to the Moon

has name

is subClass of is subClass of

is visited by is part of

is subClass of




● For Relations and Attributes Rules (Constraints) can be defined that determine allowed/valid values

Person

Astronaut Student

AddresshasAddress

is subClass of is subClass of

Woman

Man

is subClass of

is subClass of

Woman ⋂ Man = ∅constraint

n : m

1 : 1




● Instances describe individuals of an ontology

Artificial Satellite

Celestial Body

is subClass of

dbr:New_Horizons

“New Horizons”

hasTitle

Pluto

has target

is a

Terminological Knowledge

Assertional Knowledge

Dwarf Planetis a

is subClass of














● The Web of Data is an upgrade of the Web of Documents

● It’s the Web as a huge decentralised database (knowledge base) of machine-accessible data

Third Generation: The Web of DataData Centered Processing

„The web of human-readable document is being merged with a web of machine understandable data. The potential of the mixture of humans and machines working together and communication through the web could be immense.“

Tim Berners-Lee, The World Wide Web: A very short personal history, May 1998

3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

http://www.w3.org/People/Berners-Lee/ShortHistory.html


● How does the user access the information?

Advantages● Information can be automatically selected, aggregated,

remixed and published according to personal preferences

personalassistant

intelligentInfrastructure

servicesuser

Informationaggregation & filtering

Third Generation: The Web of DataData Centered Processing

3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

http://lod-cloud.net/versions/2017-02-20/lod.svg




1. Identification (URI) & address (URL)e.g. http://kit.edu

URL

HTTP

address

2. Communication / protocol (HTTP)GET /index HTTP/2Host: kit.edu

HTML

reference

communication

WEB

3. Representation language (HTML)Rima studies at <a href=”http://kit.edu”>KIT</a>.

Thanks to http://www.slideshare.net/fabien_gandon

The Basic Architecture of the Web3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data


Linked Data and the Web of Data3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

Where do the Links come from…?

...and what do they mean?


The Semantic Web and the Web of Data3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

● 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 implicit (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 and the Web of Data3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

„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"

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

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


3. Linked Data Engineering / 3.1 The Web of Data


The Semantic Web Technology Stack3. Linked Data Engineering / 3.2 Semantic Web and the Web of Data

http://dbpedia.org/resource/PlutoPluto

URI - Uniform Resource Identifier

http://dbpedia.org/resource/Pluto




RDF Resource Description Framework

:Pluto rdf:type dbo:Planet .:Pluto foaf:name “Pluto”@en .:Pluto dbo:discoverer :Clyde_Tombaugh .:Pluto dbo:discovered “1930-02-18”^^xsd:date .:Clyde_Tombaugh rdf:type dbo:Person .:Clyde_Tombaugh dbo:birthdate “1906-02-04”^^xsd:date ....

:Pluto rdf:type dbo:Planet .

RDF Subject RDF Property RDF ObjectRDF Triple






RDF Schema

dbo:Planet rdf:type owl:class .dbo:Planet rdfs:subClassOf dbo:CelestialBody .dbo:discovered rdf:type rdf:Property .dbo:discovered rdfs:domain owl:Thing .dbo:discovered rdfs:range xsd:date .dbo:discoverer rdf:type rdf: Property .dbo:discoverer rdfs:domain owl:Thing .dbo:discoverer rdfs:rang dbo:Person ....

http://dbpedia.org/ontology/Planet

Planet Persondbo:discoverer

CelestialBody

rdfs:subClassOf





logical constraint

Person

Pluto Clyde_Tombaughdbo:discoverer

new:LivingPeople new:DeadPeople∩ = ∅

rdf:type

rdfs:subClassOf

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

description logics

+ logical rules

classes

entities



try SPARQL query at public DBpedia SPARQL endpoint

Look for all Astronauts who have been on a

Space Mission which ended in a Desaster

PREFIX dcterms: <http://purl.org/dc/terms/>

PREFIX dbp: <http://dbpedia.org/property/>

PREFIX dbc: <http://dbpedia.org/resource/Category:>

SELECT distinct ?astronaut ?mission

FROM <http://dbpedia.org/>

WHERE {

?astronaut rdf:type dbo:Astronaut;

dbp:mission ?mission .

?mission dcterms:subject dbc:Space_accidents_and_incidents .

}

http://dbpedia.org/sparql?default-graph-uri=http%3A%2F%2Fdbpedia.org&qtxt=PREFIX+dcterms%3A+%3Chttp%3A%2F%2Fpurl.org%2Fdc%2Fterms%2F%3E%0D%0APREFIX+dbp%3A+%3Chttp%3A%2F%2Fdbpedia.org%2Fproperty%2F%3E%0D%0APREFIX+dbc%3A+%3Chttp%3A%2F%2Fdbpedia.org%2Fresource%2FCategory%3A%3E%0D%0A%0D%0ASELECT+distinct+%3Fastronaut+%3Fmission+%0D%0AFROM+%3Chttp%3A%2F%2Fdbpedia.org%2F%3E%0D%0AWHERE%7B%0D%0A%3Fastronaut+rdf%3Atype+dbo%3AAstronaut%3B+%0D%0A+++++++++++dbp%3Amission+%3Fmission+.%0D%0A%3Fmission+++dcterms%3Asubject+dbc%3ASpace_accidents_and_incidents+.%0D%0A%7D+%0D%0A&format=text%2Fhtml&CXML_redir_for_subjs=121&CXML_redir_for_hrefs=&timeout=3000000&debug=on




Look for all Astronauts who have been on a

Space Mission which ended in a Desaster

try SPARQL query at public DBpedia SPARQL endpoint
















The Web of Data and how we make use of it

3. Linked Data Engineering / 3.3 Linked Data Principles

Linked Data● Linked Open Data (LOD) denote

publicly available (RDF) Data in the

Web, identified via URI and accessible

via HTTP. Linked data link to other data

via URI.

The Web of Data● 9,960 datasets

● >149 billion facts

● >800 million links

(April 2017)

http://stats.lod2.eu/http://lod-cloud.net/

http://stats.lod2.eu/

http://stats.lod2.eu/

http://lod-cloud.net/

http://lod-cloud.net/

Information Service Engineering , Prof. Dr. Harald Sack, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure & AIFB - Karlsruhe Institute of Technologyhttp://www.bbc.co.uk/music

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

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


Data Access in the traditional Web3. Linked Data Engineering / 3.3 Linked Data Principles

● Data can only be found on the Web, if it is available at some website

Browser

Web Server

JDBC

HTTP



● There is a number of different (proprietary) Web APIs, data exchange

formats, and Mashups on top of that

Database 1 Database 2 Database 3 Database 4

WebAPI 1

WebAPI 2

WebAPI 3

WebAPI 4

Mashup


In the traditional Web...3. Linked Data Engineering / 3.3 Linked Data Principles

● Data is locked up in small data islands

● Other applications usually cannot access this data...

Database

DatabaseDatabase

DatabaseDatabase

Database

Database

Database

Database

Database



http://www.w3.org/2009/Talks/0204-ted-tbl/#(22)




How to get rid of Closed Data Island?3. Linked Data Engineering / 3.3 Linked Data Principles

● Apply Linked Data technology

○ to publish (structured) data on the web

○ to draw connections from one data source to data from other data sources

Database 1 Database 2 Database 3 Database 4

RDF data RDF data RDF data RDF data


Linked Data Principles

1. Use URIs as names for things.

2. Use HTTP URIs, so that people can look up those names.

3. When someone looks up a URI, provide useful information,

using the standards (RDF, SPARQL)

4. Include links to other URIs, so that they can discover more

things.

(Tim Berners-Lee, Linked Data, 2006, http://www.w3.org/DesignIssues/LinkedData.html)

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


The Benefit of using Linked Data at BBC Music Website

● Information is dynamically aggregated from external, publicly available data (Wikipedia, MusicBrainz, Last.FM, Discogs,...)

● no Screen Scraping

● no specialized API

● all data available as Linked Open Data

● data access via simple HTTP Request

● data is always up-to-date without manual interaction


Linked Open Data3. Linked Data Engineering / 3.3 Linked Data Principles

○ Public Linked Data resources in the Web, licensed as Creative Common CC-BY

○ Tim Berners-Lee‘s 5-Star Criteria for Linked Open Data

Available on the web (whatever format) but with an open licence, to be Open Data★

★★ Available as machine-readable structured data(e.g. excel instead of image scan of a table)

★★★ as (2) plus non-proprietary format (e.g. CSV instead of excel)

★★★★★ All the above, plus: link your data to other people’s data to provide context

★★★★ All the above plus: use open standards from W3C(RDF and SPARQL) to identify things, so that people can point at your stuff














What is this?



Semiotic Triangle3. Linked Data Engineering / 3.4 How to name Things - URIs

sender

receiver

is a substitute for

Symbol Objectstands for

refers tosymbolizes

“apple”

Concept

shared concept

Ogden, Richards: Semiotic Triangle, 1923


Uniform Resource Identifier3. Linked Data Engineering / 3.4 How to name Things - URIs

● A Uniform Resource Identifier (URI) defines a simple and extensible schema for worldwide unique identification of abstract or physical resources (RFC 3986).

● A Resource can be every object with a clear identity (according to the context of the application)

○ as e.g., web pages, books, locations, persons, relations among objects, abstract concepts, etc.

● URI concept is already established in various domains, as e.g., ○ the Web (URL), ○ Books and publications (ISBN, ISSN), ○ Digital Object Identifier (DOI)


URL URIidentify

on the webwhat exists

identifywhat existson the web

http://www.mywebsite.org/ http://hpi.de/harald_foaf.rdf#me

Thanks to http://www.slideshare.net/fabien_gandon


Linked Data and the Web3. Linked Data Engineering / 3.4 How to name Things - URIs

URI

HTTP

address

HTML

reference

communication

WEB

Information Service Engineering , Prof. Dr. Harald Sack, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure & AIFB - Karlsruhe Institute of Technologyhttp://commons.wikimedia.org/wiki/File:Eiffel_tower_from_trocadero.jpg

Resource

http://www.tour-eiffel.fr/

URI

identifies

Metadata: Content-type: text/htmlData:<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"><html> <head> <title>Le site officiel de la Tour Eiffel</title> ...</html>

represents (stands for)

Representation

Presentation

defines

The Eiffel Tower is described (designated) by the web page

Designator

Designatum

describes

http://www.tour-eiffel.fr/index.html

http://www.tour-eiffel.fr/index.html


3. Linked Data Engineering / 3.4 How to name Things - URIs

http://commons.wikimedia.org/wiki/File:Eiffel_tower_from_trocadero.jpg

What if a URI does not exist (yet)?

● Define a URI by yourself:

○ avoid overlaps → use your own website as namespace

○ enable documentation at the same place → HTTP Content Negotiation

● Use separate URIs for the resource (Designatum) and its documentation

(Designator) via

○ HTTP Content Negotiation and/or

○ URI references (e.g. via "#" fragment identifier)



HTTP Content NegotiationLet‘s try an example:

● I want to have information about the Eiffel Tower from DBpedia

http://dbpedia.org/ resource/Eiffel_Tower

http://dbpedia.org/ page/Eiffel_Tower

1

2 HTTP/2 303 See Other

HTTP GET requestAccept Header: text/html

URI represents Designator3HTTP GET requestAccept Header: text/html

URI represents Designatum

HTML Document4http://commons.wikimedia.org/wiki/File:Eiffel_tower_from_trocadero.jpg

http://dbpedia.org/resource/Eiffel_Tower










HTTP Content NegotiationLet‘s try another example:

● I want to have machine readable information about the Eiffel Tower from DBpedia

http://dbpedia.org/ resource/Eiffel_Tower

http://dbpedia.org/ data/Eiffel_Tower

1

2 HTTP/2 303 See Other

HTTP GET requestAccept Header: application/rdf+xml

URI represents Designator3

URI represents Designatum

RDF Document4

HTTP GET requestAccept Header: application/rdf+xml

http://commons.wikimedia.org/wiki/File:Eiffel_tower_from_trocadero.jpg





http://dbpedia.org/data/Eiffel_Tower






HTTP Content Negotiation

Let‘s try it ourselves:● I want to have information about the Eiffel Tower from DBpedia

● I want to have machine readable information about the Eiffel Tower from DBpedia

curl -L -H "Accept: text/html" http://dbpedia.org/resource/Eiffel_Tower

curl -L -H "Accept: application/rdf+xml" http://dbpedia.org/resource/Eiffel_Tower



Linked Data and the Web

URI

HTTP

address

HTML

reference

communication

WEB


Linked Data Principles

1. Use URIs as names for things.

2. Use HTTP URIs, so that people can look up those names.

3. When someone looks up a URI, provide useful information,

using the standards (RDF, SPARQL)

4. Include links to other URIs, so that they can discover more

things.

(Tim Berners-Lee, Linked Data, 2006, http://www.w3.org/DesignIssues/LinkedData.html)

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



Linked Data and the Web

URI

HTTP

address

RDF

reference

communication

WEBof Data














3. Linked Data Engineering / 3.5 Resource Description Framework (RDF) as simnple Data Model

How to represent knowledge?

intuitive knowledge representation with a directed graph

● How do I represent the following fact:“Pluto has been discovered in 1930” in an intuitive way?

Plutosubject

has been discovered inpredicate

1930object



Resource Description Framework

URI or Literal

URI

URIPlutosubject

has been discovered inpredicate

1930object




● RDF Statements (RDF-Triple):

Subject Property Object / ValueURI URI URI / Literal RDF Building Blocks

<http://dbpedia.org/resource/Pluto> <http://dbpedia.org/ontology/discovered> “1930” .

N-Triples Serialization

<http://dbpedia.org/resource/Pluto> “1930”<http://dbpedia.org/ontology/discovered> graph

representation





<http://dbpedia.org/resource/Pluto>“1930”

<http://dbpedia.org/ontology/discovered>

<http://dbpedia.org/resource/Clyde_Tombaugh><http://dbpedia.org/ontology/discoverer>

“1906-02-04”

<http://dbpedia.org/ontology/birthdate>

<http://dbpedia.org/resource/Streator,_Illinois>

<http://dbpedia.org/ontology/birthplace>

“Quiet Surprise in the Prairie”<http://dbpedia.org/ontology/motto>




RDF is a Triple Model i.e. every piece of knowledge is broken down into( subject , predicate , object )

http://www.slideshare.net/fabien_gandon

RDF is a Graph Modeli.e. every piece of knowledge is interpreted as( vertex , edge , vertex )




<http://dbpedia.org/resource/Pluto> <http://dbpedia.org/ontology/discovered> “1930” .<http://dbpedia.org/resource/Pluto> <http://dbpedia.org/ontology/discoverer> <http://dbpedia.org/resource/Clyde_Tombaugh> .<http://dbpedia.org/resource/Pluto> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://dbpedia.org/ontology/CelestialBody> .<http://dbpedia.org/resource/Pluto> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://schema.org/place> . … … ...

<http://dbpedia.org/resource/Clyde_Tombaugh> <http://dbpedia.org/ontology/birthdate> “1906-02-04” .<http://dbpedia.org/resource/Clyde_Tombaugh> <http://dbpedia.org/ontology/birthplace> <http://dbpedia.org/resource/Streator,_Illinois> . … … ...

<http://dbpedia.org/resource/Streator,_Illinois> <http://dbpedia.org/ontology/motto> “Quiet Surprise in the Prairie” .<http://dbpedia.org/resource/Streator,_Illinois> <http://www.w3.org/2003/01/geo/wgs84_pos#lat> “41.120834”^^xsd:float .<http://dbpedia.org/resource/Streator,_Illinois> <http://www.w3.org/2003/01/geo/wgs84_pos#long> “-88.835281”^^xsd:float . … … ...

Subject Property Object

RDF Triples







Individuals (Entities)







Classes







Literals







Properties







Vocabularies / Ontologies














3. Linked Data Engineering - 1 Bibliography

● Tim Berners-Lee, James Hendler, Ora Lassila: The Semantic Web, Scientific American,

284(5), pp. 34-43(2001).

● S. Hitzler, S. Rudolph,

Foundations of Semantic Web Technologies, Chapman / Hall, 2009.

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


3. Linked Data Engineering - 1 Syllabus Questions

● What is knowledge?

● How does knowledge representation work?

● What is an ontology? (Definition and Explanation)

● What are typical constituents of an ontology?

● What is the Semantic Web?

● What is the difference between URI and URL

● What’s the difference between identification and representation ?

● Explain HTTP Content Negotiation human readable and machine readable resources

● What is an RDF triple?

Education

06 Linked Data Engineering - 1