Download - AgRelOn: An Agent Relationship Ontology
| 23 | AgRelOn : MTSR Cádiz | November 29, 20121
AgRelOn: The Agent Relationship Ontology
Berenike Litz, Aenne Löhden, Jan Hannemann, Lars G. Svensson
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When digitising cultural heritage data, one important goal is to put the content into a network of entities
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Metadata specialists build this network through the use of authority files
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GND
ICONCLASS
LCSHNAF
DDCAAT
VIAF
AGROVOC
TGN
RAMEAU
STW
The connections between persons in our authority data is described through manual annotations
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A more formalised method is necessary in order to make this information machine-understandable
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http://d-nb.info/gnd/118543601
http://d-nb.info/gnd/11855042X
„Hesse, Hermann“@de
„Gundert, Hermann“@de
gnd:preferredNameForThePerson
gnd:preferredNameForThePersonex:grandfatherOf
We developed an ontology describing those relations
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AgRelOn aims to enable semantic searchability of personal relations
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In CONTENTUS, we performed named entity recognition and wanted to explore the relations
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11 22 33 44 55 66
Face Logo
Text Person
Speaker 1 Speaker 2
Image
Text
Title
Knowledge base
FilmInformation about actors, director, producers, music, sequence, year of production. Short description of the picture, video sequence…What is in the film, rights.Any other relevant information as short summary of content for fast access…
Related booksYear of printing, editions, authors, summary of the book….
Related internet linksYear of printing, editions, authors, summary of the book….
Related music scoreYear of printing, editions, authors, summary of the book….
Related films Year of printing, editions, authors, summary of the book….
Related songsYear of printing, editions, authors, summary of the book….
Related newsYear of printing, editions, authors, summary of the book….
Digitisation
Automatic quality analysis and optimisation
Automatic content ana- lysis and meta- data generation
Semiautomatic semantic linking
Open know- ledge network
semantic multimedia search
COREProfessionals(Media archives…)
MANTELAutomated(Learning)
SHELLEnd-user(wikipedia)
We investigated other vocabularies, and had problems with ontological commitment
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Vocabularies for agents and agent relations- BIO- FoaF- genont, srcont- RELATIONSHIP- SIOC
Vocabularies for meta-statements
- OPMV- Provenance Vocabulary
Investigated vocabularies:
Library and cultural heritage vocabularies
- CIDOC CRM- DC- EDM- MADS- METS- MIX- MODS- RDA- SKOS- Old DNB Linked Data-Model
A further requirement was a good fit with the project specific CONTENTUS ontology
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The modelled relationships are based on actual data from a GND predesessor
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Beside kinship, modelling of artistic and other relations was important
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We modelled meta-knowledge by using n-ary relations
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The ontology was populated through several sources
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AgRelOn
PND
Web 2.0
The ontology has been evaluated successfully in several research projects
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A subset of AgRelOn relations are used in the GND
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… … …
bete Beteiligte Tf; Tb; Ts; Tu
beza Bekanntschaft mit Tp
bezb Beziehung beruflich Tp
bezf Beziehung familiär Tp
bilh Bildhauer Tg; Tu
… … …
malr Maler Tu
mitg Mitglied Tp (008 pxl;pxg;pif)
musi Musiker Tb; Tf
… … …
The ALEXANDRIA relationship browser helps exploring networks of people
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Of particular interest is the SMMS developed in CONTENTUS
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But is this level of granularity really necessary?
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http://d-nb.info/gnd/118543601
http://d-nb.info/gnd/11855042X
foaf:knows
The connections between entities in the authority file were given using textual descriptions, but we needed something machine-understandable
| 23 | AgRelOn : MTSR Cádiz | November 29, 201220
http://d-nb.info/gnd/118543601
http://d-nb.info/gnd/11855042X
„Hesse, Hermann“@de
„Gundert, Hermann“@de
gnd:preferredNameForThePersonex:grandfatherOf
We developed an ontology describing those relations
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Particularly the relation hierarchy made UI design easier
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AgRelOn – for the relation between Kallimachos and Tim Berners-Lee
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