[PPT] - Jorge Gr Jo Gracia ia Jose Labra Jo Labra Ontology Engineering PowerPoint Presentation

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Jo Jorge Gr Gracia ia

Ontology Engineering Group (OEG) Universidad Politécnica de Madrid (UPM) jgracia@fi.upm.es

Multilingual Web Workshop Madrid (Spain) 7-8 May 2014 Jo Jose Labra Labra

Web Semantics Oviedo (WESO) University of Oviedo labra@uniovi.es

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Multilingual Web Workshop Madrid, May 2014 Multilingual Web Workshop Madrid, May 2014

} Motivation } The group } Main goals } Activities } Where are we now?

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Moti tivati tion

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349 1,906 635 2,201 1,984 676

Monolingual datasets Multilingual datasets January 2012 June 2012 December 2012

A. Gómez-Pérez, D. Vila-Suero, E. Montiel-Ponsoda, J. Gracia, and G. Aguado-de Cea,

"Guidelines for multilingual linked data," in Proceedings of the 3rd International Conference

n Web Intelligence, Mining and Semantics, ser. WIMS '13. New York, NY, USA: ACM, Jun. 2013.

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Multilingual Web Workshop Madrid, May 2014

2,567,324 10,250,936 3,154,779 10,594,338 12,272,806 3,365,930

RDF literals without language tag RDF literals with language tag January 2012 June 2012 December 2012

A. Gómez-Pérez, D. Vila-Suero, E. Montiel-Ponsoda, J. Gracia, and G. Aguado-de Cea,

"Guidelines for multilingual linked data," in Proceedings of the 3rd International Conference

n Web Intelligence, Mining and Semantics, ser. WIMS '13. New York, NY, USA: ACM, Jun. 2013.

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Vocabulary selection RDF generation Data Interlinking Web Publishing

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http ttp://example.org/Spain http ttp://example.org/I23AX4 X45 http ttp://example.org/Es España

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Th The g e grou roup

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Multilingual Web Workshop Madrid, May 2014 Multilingual Web Workshop Madrid, May 2014

W3C community group on Best Practises for Multilingual Linked (Open) Data

https://www.w3.org/community/bpmlod 

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Started on June 2013 bi-weekly telcos 3 chairs. Currently: 67 members from academia and industry

José Labra Jorge Gracia John McCrae

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and many

thers…

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Main Main g goals

als

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Multilingual Web Workshop Madrid, May 2014 Multilingual Web Workshop Madrid, May 2014

Crowdsourcing ideas from the community regarding best practices to produce multilingual linked (open) data. Documenting patterns and best practices for the creation, linking, and use of multilingual linked data.

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Multilingual Web Workshop Madrid, May 2014 Multilingual Web Workshop Madrid, May 2014

Linked Data for Language Technologies (LD4LT) BPMLOD Ontology lexica (Ontolex) Data on the Web Best Practices

Use Cases BP for LD in LT lemon specification BP for using lemon BP for Multlingual Data on the Web BP for Data on the Web

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Acti tiviti ties

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TOPIC classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

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TOPIC classification

NAMING

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Multilingual Web Workshop Madrid, May 2014 Multilingual Web Workshop Madrid, May 2014

Naming

Opaque URIs, Descriptive URIs, IRIs, …

Textual information

Language tags, linguistic information, …

Linking

Interlanguage links, owl:sameAs, …

Ontologies and vocabularies

Mono/multilingual vocabularies, ontology localisation…

Quality of MLOD Tools and examples of MLOD Other related aspects

licensing, legal aspects, …

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https://www.w3.org/community/bpmlod/wiki/Topic_classification

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TOPIC classification USE CASES

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USE CASES

1. Localization workflow [D. Lewis]
2. Lexicalisation of RDF Datasets [E. Montiel, G. Dunshire]
3. Ontology localisation [E. Montiel, L. Aguado, G. Dunsire]
4. Crosslingual linked data matching [J. Gracia]
5. Machine translation [T. Heuss]
6. Application localization [J. McCrae]

CASE STUDIES

1. Translations of multilingual terminologies for

libraries [G. Dunsire]

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https://www.w3.org/community/bpmlod/wiki/Use_cases_definition

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TOPIC classification USE CASES PATTERNS

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Difficult to establish a boundary between Patterns vs Best Practices vs Bad smells

By now: we identify the main practices Bad/Good may depend on the context/use case

Examples:

Patterns for naming and dereferencing

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} Example: URI for Armenia? Descriptive URIs http://example.org/Armenia ¡ Opaque URIs http://example.org/I23AX45 ¡ Full IRIs http://օրինակ.օրգ#Հայաստան ¡ Internationalized paths only http://example.org#Հայաստան ¡ Language in host name http://hy.example.org#Հայաստան ¡ http://en.example.org#Armenia ¡

May be unreadable for non-Latin alphabet users Difficult to be descriptive enough in some contexts %-encoding non-ASCII characters

http://example.org/Espa%3Fa

Human-readable Good tool support

Non Human-readable Difficult to handle by developers ¡

Independence between concept and language Maintenance: changes in text don't affect URI Suitable for LD generation

Security issues (spoofing) Unreadable for speakers of other languages Tool support Readable (for one language) Unreadable for speakers of other languages Less security issues Path readable (for one language) Where should we put the language tag? Dialects can become unwieldy Example: languages & sublanguages hy-‑Latin-‑IT-‑arevela ¡ Practical reasons

Independent development of datasets by language

Language in Path http://example.org/Armenia.en ¡ http://example.org/en/Armenia ¡ http://example.org/Armenia?lang=en ¡ Dialects ¡

Compatible with content negotiation

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} Which data should I return when accessing a URI?

No language content negotiation

Ignore Accept-language...all the data

Language content negotiation

Accept-‑language:en ¡ <> ¡rdfs:label ¡"Armenia"@en ¡. ¡ Accept-‑language:hy ¡ :<> ¡rdfs:label ¡"Հայաստան "@hy ¡. ¡ Clients have to filter triples in other languages Bandwidth overhead Easy to develop Consistency of data

Difficult to implement Looses data Less network overhead

http://example.org/Armenia ¡ http://example.org/Armenia ¡

Language content redirection

Accept-‑language:en ¡ 303 ¡ See ¡also: ¡http://example.org/Armenia.en ¡ Accept-‑language:hy ¡ 303 ¡ See ¡also:http://example.org/Armenia.hy ¡

http://example.org/Armenia ¡

More difficult to implement Not always feasible Keeps difference between concept and language representation ¡<> ¡rdfs:label ¡"Armenia"@en, ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡ ¡"Հայաստան"@hy ¡.

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TOPICS classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

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Some (future) EXAMPLES. Guidelines for: Linguistic Linked Data generation RDF and Ontology translation Multilingual Linked Data generation, publication and exploitation ...

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Wh Where are w ere are we n e now

w?

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TOPICS classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

We are here (Patterns for textual information)

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Thanks… and get involved!

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https://www.w3.org/community/bpmlod 

Jorge Gr Jo Gracia ia Jose Labra Jo Labra Ontology Engineering - - PowerPoint PPT Presentation

Moti tivati tion

Th The g e grou roup

W3C community group on Best Practises for Multilingual Linked (Open) Data

https://www.w3.org/community/bpmlod

Main Main g goals

Crowdsourcing ideas from the community regarding best practices to produce multilingual linked (open) data. Documenting patterns and best practices for the creation, linking, and use of multilingual linked data.

Acti tiviti ties

TOPIC classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

TOPIC classification

TOPIC classification USE CASES

TOPIC classification USE CASES PATTERNS

Difficult to establish a boundary between Patterns vs Best Practices vs Bad smells

Examples:

TOPICS classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

Some (future) EXAMPLES. Guidelines for: Linguistic Linked Data generation RDF and Ontology translation Multilingual Linked Data generation, publication and exploitation ...

Wh Where are w ere are we n e now

TOPICS classification USE CASES PATTERNS

BEST PRACTISES & GUIDELINES

Thanks… and get involved!

Next telco: Thursday 22nd May 10:00 CEST