Ontologies to describe data on the Web 19th October 2016, Vitoria VIII Encounter of documentation centres of contemporary art
María Poveda Villalón mpoveda@fi.upm.es ETSI Informaticos Universidad Politécnica de Madrid Campus de Montegancedo s/n 28660 Boadilla del Monte, Madrid, Spain
Twitter: @MariaPovedaV
Context – Ontology Engineering Group / ODI Madrid Directors: A. Gómez-Pérez, O. Corcho Position: 8th in the UPM ranking (200 groups) Founded: 1994
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Research Group (30 people) Experience on 1. 2. 3.
Ontologies, Semantic Web, Linked Open Data Semantic E-science Multilingualism
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ODI Madrid : Madrid Node of the Open Data Institute
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Projects § § §
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>25 @ W3C, ISO, OASIS, etc.
https://github.com/oeg-upm
Impact of publications H-index (scholar) § §
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http://www.oeg-upm.net/
Standardization activities §
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27 EU projects (7 as coordinator) 54 National Projects 27 contracts with companies
Asunción Gómez-Pérez (h:50, citations 14852) Oscar Corcho García (h: 36, citations 8152)
@oeg-upm
Services to the Spanish community § § §
170+ Past Collaborators 50+ Past Visitors
esDbpedia linkeddata.es vocab.linkeddata.es
Slide from “Open Data” by A. Gómez-Pérez”
2
License
• This work is licensed under the Creative Commons Attribution – Non Commercial – Share Alike License • You are free: • to Share — to copy, distribute and transmit the work • to Remix — to adapt the work
• Under the following conditions • Attribution — You must attribute the work by inserting • “[source http://www.oeg-upm.net/]” at the footer of each reused slide • a credits slide stating: “Ontologies to describe data on the Web” by M. Poveda Villalón” • Non-commercial • Share-Alike 3
Ontologies and data on the web
Why? 4
Current Web
http://directoriomuseos.mcu.es/dirmuseos/realizarBusquedaSencilla.do
5
Current Web
Need of semantics for machines
維多利亞 阿拉瓦 博物館 0056 0069 0074 006F 0072 0069 0061 002D 0047 0061 0073 0074 0065 0069 007A 000A...
http://directoriomuseos.mcu.es/dirmuseos/realizarBusquedaSencilla.do
6
Current Web Which museums have Spanish artists’ exhibitions? Exhibition 1: Rubens
Exhibition 1: Dalí
Exhibition 2: Dalí
Exhibition 2: Munch
Exhibition 3: Picasso
Next…
Museum 1
Museum 2
Painters: Dalí (Figueras) 1904… Munch (Adalsbruk) 1863... Picasso (Málaga) 1881… Rubens (Siegen) 1577...
Encyclo pedia
7
Spain … Cataluña Gerona Figueras … Andalucía Málaga
Geography institute
Current Web
Need of (meaningful) links Exhibition 1: Rubens Exhibition 2: Dalí Exhibition 3: Picasso
Museum 1
Exhibition 1: Dalí
? ?
Exhibition 2: Munch
?
Painters: Dalí (Figueras) 1904… Munch (Adalsbruk) 1863... Picasso (Málaga) 1881… Rubens (Siegen) 1577...
Spain
? ?
Next…
Encyclo pedia
Museum 2
8
… Cataluña Gerona Figueras … Andalucía Málaga
Geography institute
Ontologies and data on the web
No semantics Isolated data
Why?
What? 9
Semantic Web and Linked Data
The collection of Semantic Web technologies provides an environment where application can query that data, draw inferences using vocabularies, etc. Exhibition 1: Rubens
Exhibition 1: sameAs Dalí
Exhibition 2: Dalí
Exhibition 2: Munch
aboutAuthor
Exhibition 3: Picasso aboutAuthor
Museum 1
offersExhibition
offersExhibition
aboutAuthor
wasBornIn
Painters: Dalí (Figueras) 1904… Munch (Adalsbruk) 1863... Picasso (Málaga) 1881… Rubens (Siegen) 1577... wasBornIn
Next…
sameAs
sameAs
sameAs
Museum 2
Spain … Cataluña isPartOf Gerona Figueras … Andalucía Málaga
Linked Data is the collection of interrelated datasets on the Web https://www.w3.org/standards/semanticweb/data 10
Ontologies and data on the web
No semantics
Semantic Web
Isolated data
Linked Data
Why?
What?
How? 11
Linked Data Principles • Use URIs to identify things (everything, persons, works, places, etc.) • Use HTTP protocol allowing others to retrieve information about those URIs • Provide useful information using standards as the RDF data model to describe resources
Subject
predicate
• Link to other URIs
https://www.w3.org/DesignIssues/LinkedData.html 12
Object
Vocabularies (ontologies) Vocabularies define the concepts and relationships used to describe and represent an area of concern. Definition taken from: http://www.w3.org/standards/semanticweb/ontology
13
Ontologies: Knowledegde and Data
Knowledge level Concepts Taxonomies Relationships Attribuites Axioms
Ontology
Data level
Instances of concepts Relations between intstances
Instances
Slide taken from“Vocabularios” by A. Gómez-Pérez”
14
Knowledge and data example
Exhibition 1: Rubens
Exhibition 1: sameAs Dalí
Exhibition 2: Dalí
Exhibition 2: Munch
aboutAuthor
Exhibition 3: Picasso aboutAuthor
Museum 1
offersExhibition
offersExhibition
aboutAuthor
wasBornIn
Painters: Dalí (Figueras) 1904… Munch (Adalsbruk) 1863... Picasso (Málaga) 1881… Rubens (Siegen) 1577... wasBornIn
Next…
sameAs
sameAs
sameAs
Museum 2
15
Spain … Cataluña isPartOf Gerona Figueras … Andalucía Málaga
Knowledge and data example Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
isPartOf (T) Country
Topic
U
City Author
exhibits ArtWork
hasTopic
wasBornIn
hasAuthor
AutonomuosCommunity
<<owl:inverseOf>>
ArtWork
Province
isAuthorOf
• OWL: Web Ontology Language • Based on RDF • Standard for the web
https://www.w3.org/TR/owl-ref/ 16
Implementation
17
Evaluation
http://oops.linkeddata.es
• Ontology editors
18
+
• Reasoners: • Pellet • Fact • Hermit • etc
Documentation â&#x20AC;¢ Ejemplo owl y html
https://github.com/dgarijo/Widoco/ 19
Registries (share & reuse) Organizational level (OEG)
Community
http://vocab.linkeddata.es/
http://lov.okfn.org 20
Handle versions and distributed environments Evaluation reports
HTML documentation
Diagrams
Permanet ids
Content negotiation
Bundle
http://ontoology.linkeddata.es
Previsualization
Knowledge and data example Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
City
hasAuthor
hasTopic
isPartOf (T)
Author
wasBornIn
Province AutonomuosCommunity
ArtWork
isAuthorOf
museum1 m1exhi1
Figueras museum2 Gerona
m1exhi2
Dali
m1exhi3 Picasso
Spain Malaga
m2exhi1 Munch
m2exhi2
Rubens Data level
22
Knowledge and data example Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City
hasAuthor
hasTopic
Author
wasBornIn
Province AutonomuosCommunity
ArtWork
isAuthorOf offersExhibition offersExhibition
m1exhi1
museum1 Figueras museum2
m1exhi2
Gerona
offersExhibition
Dali
m1exhi3 Picasso
Spain Malaga
m2exhi1 Munch
m2exhi2
Rubens Data level
23
Knowledge and data example Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City Author
hasAuthor
hasTopic
wasBornIn
Province AutonomuosCommunity
ArtWork
isAuthorOf offersExhibition offersExhibition
m1exhi1
museum1 Figueras museum2
m1exhi2
offersExhibition
Gerona
hasExhibitionTopic
Dali
m1exhi3 Picasso
hasExhibitionTopic
Spain Malaga
m2exhi1
hasExhibitionTopic Munch
m2exhi2
Rubens
hasExhibitionTopic hasExhibitionTopic
Data level
24
Knowledge and data example Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City Author
hasAuthor
hasTopic
Province
wasBornIn
AutonomuosCommunity ArtWork
isAuthorOf offersExhibition offersExhibition
m1exhi1
isPartOf
museum1 Figueras museum2
m1exhi2
offersExhibition
Gerona
hasExhibitionTopic
Dali
wasBornIn isPartOf
m1exhi3 Picasso
hasExhibitionTopic
Spain
wasBornIn Malaga
m2exhi1
hasExhibitionTopic isPartOf
Munch
m2exhi2
Rubens
hasExhibitionTopic hasExhibitionTopic
Data level
25
Benefits • Provide semantics/context • Disambiguation, prevent errors • Facilitate data reuse
26
Whoâ&#x20AC;&#x2122;s birthday is today? Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
Whoâ&#x20AC;&#x2122;s birthday is today? Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
5th of November 2016
Clue 1
London
Whoâ&#x20AC;&#x2122;s birthday is today? Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986 Happy birthday Oliver!
5th of November 2016
Clue 2
Whoâ&#x20AC;&#x2122;s birthday is today? Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
Happy birthday Linda!
5th of November 2016
Describe your data Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
U.S. date format MM/DD/YYYY
U.K date format DD/MM/YYYY
5th of November 2016
Describe your data Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
U.S. date format MM/DD/YYYY
U.K date format DD/MM/YYYY
5th of November 2016
Happy birthday Linda and Oliver!
Just one more thing
Keep describing Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
U.S. date format MM / DD / YYYY
U.K date format DD / MM / YYYY
YYYY
MM
ISO 8601
DD
Just one more thing
Keep describing Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
U.S. date format MM / DD / YYYY
U.K date format DD / MM / YYYY
YYYY
MM
ISO 8601
DD
Just one more thing
Keep describing Linda was born on the 11/05/1983
Oliver was born on the 05/11/1986
U.S. date format MM / DD / YYYY
U.K date format DD / MM / YYYY
YYYY
MM
ISO 8601
DD
Benefits • Provide semantics/context • Disambiguation, prevent errors • Facilitate data reuse • Facilitate data integration • Different formats, sources, schemas, languages..
38
Benefits • Provide semantics/context • Disambiguation, prevent errors • Facilitate data reuse • Facilitate data integration • Different formats, sources, schemas, languages..
• Facilitate dataset maintenance • Reasoning, inference
39
Inference Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City Author
hasAuthor
hasTopic
Province
wasBornIn
AutonomuosCommunity ArtWork
<<owl:inverseOf>> isAuthorOf
offersExhibition offersExhibition
m1exhi1
isPartOf
museum1 Figueras museum2
m1exhi2
offersExhibition
Gerona
hasExhibitionTopic
Dali
wasBornIn isPartOf
m1exhi3 Picasso
hasExhibitionTopic
wasBornIn Spain
m2exhi1
hasExhibitionTopic Munch
m2exhi2
Rubens
hasExhibitionTopic hasExhibitionTopic
Malaga
isPartOf Data level
40
Inference Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City Author
hasAuthor
hasTopic
Province
wasBornIn
AutonomuosCommunity ArtWork
<<owl:inverseOf>> isAuthorOf
offersExhibition offersExhibition
m1exhi1
isPartOf
museum1 Figueras museum2
m1exhi2
offersExhibition
Gerona
hasExhibitionTopic
Dali
wasBornIn isPartOf
m1exhi3 Picasso
hasExhibitionTopic
hasPart
wasBornIn Spain
m2exhi1
hasExhibitionTopic Munch
m2exhi2
Rubens
hasExhibitionTopic hasExhibitionTopic
Malaga
isPartOf Data level
41
Inference Knowledge level Exhibition
Museum
offersExhibition
startingDate:: dateTime endingDate:: dateTime
hasPart (T)
isLocatedAt
<<owl:inverseOf>>
(1..1) name:: string (F) Place
hasExhibitionTopic
Country
Topic
U exhibits ArtWork
isPartOf (T)
City Author
hasAuthor
hasTopic
Province
wasBornIn
AutonomuosCommunity ArtWork
<<owl:inverseOf>> isAuthorOf
offersExhibition offersExhibition
m1exhi1
isPartOf
isPartOf
museum1 Figueras museum2
m1exhi2
offersExhibition
Gerona
hasExhibitionTopic
Dali
wasBornIn
hasPart isPartOf
m1exhi3 Picasso
hasExhibitionTopic
hasPart m2exhi1
hasExhibitionTopic Rubens
hasExhibitionTopic hasExhibitionTopic
Spain
hasPart
Munch
m2exhi2
hasPart
wasBornIn
Malaga
isPartOf Data level
42
Benefits • Provide semantics/context • Disambiguation, prevent errors • Facilitate data reuse • Facilitate data integration • Different formats, sources, schemas, languages..
• Facilitate dataset maintenance • Reasoning, inference • Mechanism used in the Web of Data
43
Ontologies and data on the web
Ontologies No semantics
Semantic Web
Technology
Isolated data
Linked Data
Principles
Why?
What?
How? 44
Who?
datos.bne.es
is subject (OP5003)
is subject (OP1007)
has subject (OP1008)
Person
(bne:C1005)
created by (OP1005) creator of (OP5001)
Concept
(skos:Concept)
has subject (OP1006)
has subject (OP1010) realized through (OP1002)
Work
Expression
has subject (OP3008)
materialized in (OP2001)
exemplified by (OP3001)
realization of (OP2002)
Item
Manifestation (bne:C1003)
(bne:C1002)
(bne:C1001) (bne:C1001)
materialization of (OP3002)
(bne:C1004) exemplar of (OP4001)
45
Otros ejemplos
46
Otros ejemplos
47
Otros ejemplos
â&#x20AC;Ś
48
Ontologies and data on the web
Ontologies No semantics
Semantic Web
Technology
Isolated data
Linked Data
Principles
Examples
Why?
What?
How?
Who?
49
1 conclusion
The vocabulary and semantics behind your records are what actually brings meaning to the data. Handle them with care.
50
Questions?
Thanks for you attention
Ontologies No semantics
Semantic Web
Technology
Isolated data
Linked Data
Principles
Examples
Why?
What?
How?
Who?
51
Ontologies to describe data on the Web 19th October 2016, Vitoria VIII Encounter of documentation centres of contemporary art
María Poveda Villalón mpoveda@fi.upm.es ETSI Informaticos Universidad Politécnica de Madrid Campus de Montegancedo s/n 28660 Boadilla del Monte, Madrid, Spain
Twitter: @MariaPovedaV