VIII Encuentros de Centros de Documentación de Arte Contemporáneo en Artium - Eero Hyvönen

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Publishing and Using
Cultural Heritage Linked Data
on the Semantic Web
Documentation Congress 2016, Vitoria-Gasteiz, Spain
Eero Hyvönen, Prof., Director
Aalto University and University of Helsinki
Heldig – Helsinki Centre for Digital Humanities
http://heldig.fi
Semantic Computing Research Group (SeCo)
http://www.seco.tkk.fi/

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Contents
• Background: History 2002-2016
• Vision: Semantic Web of Cultural Heritage
• Challenges: Content Complexity & Production
• Solution: Linked Data Publishing Model ”Sampo”
• Realization: Three Sampo Applications

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Background: History 2002-2016

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History behind this talk
 Semantic Portals for Cultural Heritage
– 2004 MuseumFinland – Finnish Museums on the Semantic
Web
» http://www.museosuomi.fi
– 2008 CultureSampo – Finnish Culture on the Semantic Web 2.0
» http://www.kulttuurisampo.fi
– 2011 BookSampo – Fiction Literature on the Semantic Web
» http://www.kirjasampo.fi
– 2012 TravelSampo -- Mobile Contextualized Services of Cultural
Tourism
» http://www.travelsampo.fi
– 2015 WarSampo – Finnish World War II on the Semantic Web
» http://www.sotasampo.fi

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 Ontology and Data Services
– 2009 National Ontology Library Service ONKI
» http://onki.fi
– 2014 ONKI.fi -> Finto.fi of the National Library
» http://finto.fi
– 2014 Linked Data Finland Data Service & Tools
» http://ldf.fi
– 2016 Finnish Ontology Service for Historical Places and Maps
» http://hipla.fi
 Publications available at:
– http://www.seco.tkk.fi/publications/

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• Over 30 resarchers at SeCo including Eetu Mäkelä, Tomi
Kauppinen, Jouni Tuominen, Kim Viljanen, Tuukka
Ruotsalo, Suvi Kettula, Kaisa Hypen, Erkki Heino, Petri
Leskinen, Minna Tamper, Esko Ikkala, Mikko Koho, …
• Some 50 organizations involved
Joint Work During 2002-2016
Antikvaria-ryhmä

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Helsinki Centre for Digital Humanities
A new platform for collaboration 2016-
http://heldig.fi
Heldig

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The Vision:
Semantic Web of Cultural Heritage

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Wouldn’t it be nice if
 cultural organizations could publish easily their contents
together on the web just by pushing a button,
 the contents would be automatically linked with other
publishers contents and get semantically enriched,
 researchers and citizens could contribute with their own
contents and knowledge,
 …

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---
 contents could be accessed easily from different thematic
perspectives and contexts,
 intelligent search and browsing systems could find
answers to questions in addition to data records,
 the aggregated contents and services could be reused in
external applications easily,
 language barriers could be overcome?

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Yes!
This is the vision of our work

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Challenges:
Content Complexity & Production

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Problem 1: Cultural Content Compexity
- Heterogenous and Interlinked
Encyclopedia
Artifacts Maps
Videos
Buildings
Fine arts
Biographies
Narratives Literature
Cultural sites
Music

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Problem 2: Cultural Content Production System
- Distributed and Independent
Museums
Libraries
Archieves
Land survey
Linked Data
Web 2.0 sites
Media
Citizens

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Solution:
Linked Cultural Heritage Data

Ontology
Infrastructure
”Sampo” Model for Semantic CH Portals
Semantic
Metadata
Content
Providers
Land survey Museums
Archieves
Linked Data
Citizens
Libraries
Web 2.0 sites
Media

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How Does This Idea Work in Practise?

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Biographical Registries Collect
Data about Persons
henkilö nimi ammatti syntymapaikka ...
H1 Akseli Gallen-Kallela taiteilija Lemu
H2 Gustaf Mannerheim marsalkka Askainen
...
H1
Lemu
Artist
Person
”Akseli Gallen-Kallela”
H2
Askainen
Marshall
”Gustaf Mannerheim”
type
type
name
nanme
profession
profession
birthPlace
birthPlace
Biography Center
Person Name Profession Birth Place

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Art Museum Catalogs Paintings
...
T1
1929
Painting
creator
time
type
”Gustaf Mannerheim”nimi
subject
name
teos nimi tekijä aika aihe ...
T1 Mannerheimin muotokuva Akseli Gallen-Kallela 1929 Gustaf Mannerheim
T2 Aino-triptyykki Akseli Gallen-Kallela 1891 Aino, Kalevala
...
Art Museum Collection

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Land Survey Organizations Know Places
Varsinais-Suomen lääni Finland
Askainen
Lemu
Turku
kunta lääni
Askainen Varsinais-Suomen lääni
Helsinki Uudenmaan lääni
Lemu Varsinais-Suomen lääni
Turku Varsinais-Suomen lääni
...
part-of
part-of
part-of
part-of
County
type
Province
type
...
type
Land Survey

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Ontologies are Developed by Semantic Web
Researchers
Artist
Person
Marshall
Painting
Concept
Endurant
Place
Profession
County
subClassOf
TimePeriod
AbstractPerdurant
PhysicalObject
Province
KOKO-ontology
Subclass Hierarchy
FinnONTO
subClassOf
subClassOf
subClassOf
subClassOf

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RDF Connects and Harmonizes
Linked Data into a GGG
H1
Lemu
Artist
Person
H2
Askainen
Marshall
”Gustaf Mannerheim”
type
type
name
name
profession
profession
birthPlace
birthPlace
T1
1929
maalaus
tekijä
aihe
aika
tyyppi
Varsinais-Suomen lääni Finland
Turku
part-of part-of
part-of part-of
Concept
Endurant
Place
Profession
County
type
type
type
subClassOf
subClassOf
subClassOf
subClassOf
yläluokka
Time
subClassOf
A bstractPerdurant
PhysicalObject
Province
yläluokka
...
Portal
Triplestore
Serendipity: 1+1 > 2

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Why is This Useful?
Limitations of Non-semantic Data
• NBA-H26069-467
:object ”cup and plate” ;
:material ”porcelain” ;
:creationPlace ”Germany” ;
:creator ”Meissen”.
• This metadata cannot answer the following queries/questions:
– Find all vessels?
– Find all ceramic products?
– Find artifacts manufactured in Europe?
– Does the city of Meissen manufacture ceramics?

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Semantic Web Solution:
Understanding the Ontological Context
 NBA-H26069-467
:object ”cup and plate” ;
:object_concept object:cup ;
:object_concept object:plate ;
:material ”porcelain” ;
:material_concept object:porcelain ;
:creationPlace ”Germany” ;
:creationPlace_concept place:Germany ;
:creator ”Meissen”
:creator_concept actor:Meissen .
NBA-H26069-467
place:Germany
object:cup
creationLocation_concept
place:Europe
loc:partOf
rdfs:subClassOf
object:vessel
object_concept
object_concept
object:plate
rdfs:subClassOf
...
...
...
Find all vessels?
Find all ceramic products?
Find artifacts manufactured in Europe?
Does the city of Meissen manufacture
ceramics?
object ontology
place ontology
actor ontology
material ontology
place:Meissen
actor:Meissen
material:porcelain
material_concept
material:ceramic

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In Principle a Piece of Cake but …

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Content Production System
- Model
- Standards & Best Practices
- Ontology & Data Services
- Annotation and other tools
Content Infrastructure
- W3C etc. standards
- Ontology Infrastructure
- Metadata schemas
- Domain ontologies
- Linked Datasets
Portal
- Humans: user-interface
Data Service
- Machines: AJAX widgets, REST, Web Services, SPARQL
Cultural Heritage
Portal System
The Components of a Semantic Portal

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Content Production System Content Infrastructure
Visible Portal Application

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Developers View to Linked Data:
Rich Internet Applications (RIA)
Linked Data Service
WWW Standard Model
Application 1
Client Side
(Browser)
Application 2
Application N
Server Side
SPARQL End Point

Three Case Studies
Using the Sampo Model
CultureSampo
BookSampo
WarSampo

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CultureSampo
Finnish Culture on the Semantic Web 2.0
(Hyvönen et al., Museums & Web 2009)
(Mäkelä et al., SWJ 2012)

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Sampo Component 1/3
Infrastructure

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YSO
AFO
MAO
TAO
VALO
KOKO
...
...
KOKO – Linked Open Ontology Cloud
Your ontology?
Aligning ontologies
ONKI Ontology Service
(Hyvönen et al., ESWC 2009)

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End-users’ view
YSO
AFO
MAO
TAO
VALO
KOKO
KOKO Ontology

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Sampo Component 2/3
Content Creation Process

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CultureSampo Content Providers (28+) :
museums, libraries, archieves, researcher
organizations, media companies + citizens
International Content Providers
1 Geonames
2 Google (Maps)
3 Iconclass (vocab.)
4 Panoramio
5 Paul J. Getty Foundation (vocab.)
6 Wikipedia
Finnish Content Providers
1 Agricola – Suomen historiaverkko
2 Espoon kaupunginmuseo
3 Helsingin kaupunginkirjasto
4 Hiihtomuseo
5 Jyväskylän yliopisto, musiikin laitos
6 Kansallisbiografia
7 Kansallismuseo
8 Kuopion kulttuurihistoriallinen museo
9 Laatokan-Karjalan museo
10 Lahden kaupunginmuseo
11 Museovirasto
12 Pohjois-Karjalan museo
13 Radio- ja TV-museo
14 Seurasaaren ulkomuseo
15 Suomalaisen Kirjallisuuden Seura SKS
16 Suomen maatalousmuseo Sarka
17 Suomen merimuseo
18 Taideteollisen korkeakoulun kirjasto
19 Valtion taidemuseo
20 Veljekset Karhumäki Oy
21 Viipurin historiallinen museo
22 Yleisradio Oy
Thanks for
cooperation!

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Metadata Schemas
Metadata schema Content type
1 artifact artifacts
2 art paintings, sculpture, drawings, abstract art
3 literature novels, short stories, comics
4 WWW page WWW pages
5 poetry 3 subtypes of poetry
6 fictive object places and persons in Kalevala
7 folk music 5 subtypes of folk music
8 photograph photographs
9 aerial photograph aerial photos
10 actors persons, organizations
11 biography biographies
12 historical event historical events
13 skill cultural process descriptions
14 video documented processes
15 built objects buildings etc. in nature
16 archeological sites archeological sites

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Data Alignment Principles Used
 Dublin Core like metadata schemas
– Element subproperty-of hierarchies
– Dump-down principle
 Harmonized element values
– Taken from large shared domain ontologies
– Objects, Actors, Places, Actions, ...

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Events and Narratives as Semantic Glue
 Events and narratives make cultural heritage alive!
– Historical events
» Finnish history ontology
– Events and processes of intangible cultural heritage
» Farming, arts & craft, …
– Events in stories
» Semantic Kalevala (Finnish national Epic)

Preserving Intangible Cultural Heritage:
Cataloging Boot Making Process
Espoolainen Onni Wirlander valmistaa saappaat

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Process Graph of Making Leather Boots
(Kettula, Hyvönen, CIDOC 2012)

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Skill Documentation:
A Semantic Video Viewer
Semantic
recommendationsSemantic process
description
Dynamic information
about the video scene

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Narrative Semantic Web
- Case Semantic Kalevala
 National epic of Finland
 Compiled by Elias Lönnrot from
a vast collection of folk poems
 Publication
– 1835 ”Old Kalevala”
– 1849 ”New Kalevala”
» 50 poems, 22 795 lines
– Translated into some 60 languages since 1841
 Semantic Kalevala
– First translation in a ”machine” language (RDF)!

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Semantic Kalevala online:
The computer ”understands” the national epic Kalevala
Semantically annotated 50
poems of the national epic
- Events and narratives
Translation into modern Finnish
Links to
related art etc.

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CultureSampo RDF Knowledge Base
(March 17, 2009)
 Metadata
– 134,000 cultural collection items (artifacts, books, videos etc.)
– 285,000 other resources (places, persons etc.)
– 204 property types in metadata
 Ontologies
– KOKO ontologies (ca. 37,000 concepts)
– Additional international vocabularies
» AAT, ULAN, Iconclass
– 253 property types in ontologies
 Size
– 11,4 million triples
» 2,7 million triplets
» 8,7 million additional reasoned triplets

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Sampo Component 3/3
The Semantic Portal

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Portal Users
 Humans
– Semantic search
– 9 thematic application perspectives
 Machines (applications)
– Via APIs

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Semantic Search with
Result Categorization

Nine Thematic Perspectives
into Cultural Heritage
Three languages
Nine perspectives
Lately commented items
Lately viewed items

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Objects on the Map (by semantic relation)

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Historical Places an Areas on Maps
Semantic
recommendations
Historical
Helsinki 1640-1945

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Historical Maps on Google Maps
Wikipedia articles
Panoramio photos
Links to historical places

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Relational Search:
”How is A. Gallen-Kallela related to Napolean I ?”

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Finnish History Ontology
External web page
embedded in CultureSampo
Timeline of historical Events

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Intangible Cultural Heritage
Semantic
recommendationsSemantic process
description
Dynamic information
about the video scene

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Biography Perspective
Semantically
annotated
biographies
Links to related
works, persons,
places etc.

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Semantic Kalevala:
The computer ”understands” the national epic Kalevala
Semantically annotated 50
poems of the national epic
- Events and narratives
Translation into modern Finnish
Links to
related art etc.

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CultreSampo in Short
1. Highly cross-domain: 26 content types and 16 metadata
schemas
2. Sophisticated semantic annotation models including
events and processes
3. Semantic search and recommending techniques
4. Versatile selection of semantic visualizations (map views,
timelines, graphs, process visualization, semantic video
viewing)
5. Based on a large nation wide collaboratively maintained
infrastructure of ontologies and ontology services
6. Includes models of and tools for collaborative semantic
content creation
7. Services are available for machines, too.

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BookSampo
Fiction Literature on the Semantic Web
(Mäkelä et al., ISWC 2011; SWJ 2013)

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BookSampo – Finnish Fiction Literature on the Semantic Web
 Why
– Helping library customers in finding literature and related content
 How
– Semantic annotation of all Finnish fiction literature (for adults)
 Who
– Finnish Public Libraries and FinnONTO project
 When
– In use since 2011 (50 000+ monthly users)
» http://www.booksampo.fi
(Mäkelä et al., IFLA 2012, SWJ 2012)

Key Idea: Data Services Supporting
Linked Data in Applications
BookSampo LD
CultureSampo LD
API
API
YOUR NEXT
APPLICATION
API
LDF.fi
SPARQL
Endpoint

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WarSampo – Linked Death
Finnish WW2 on the Semantic Web
(Hyvönen et al., ESWC 2016)

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”We learn from history, that
we learn nothing from history”
Georg Wilhelm Friedrich Hegel
?

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WarSampo: two components
Data Service for Linked Open Data
http://ldf.fi
Applications based on the service
http://sotasampo.fi
Linked Data Service Applications (7)

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WarSampo Linked Open Data Cloud
7.6 milllion triples
in the knowledge graph

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Conceptual Data Model Core:
Extending CIDOC CRM

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Semantic Portal http://sotasampo.fi/en
7 Perspectives to War
More info: [Hyvönen et al., ESWC 2016; Koho et al., WHiSe 2016]
In-use semantic portal 2015
Nearly 20 000 end-users during first 3 days
1. Events 2. Persons 3. Army Units
4. Places 5. Deaths 6. Memoirs
7. Photos

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Use Cases
 Providing massive amounts of heterogenous WW2 data
 Reassembling the lives of the dead
 Supporting Digital Humanities Research

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Using the Data in Digital Humanities
- Data analysis & visualizations
Casualtiesofthe33rdinfantryregiment

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Conclusions: Semantic Web Makes a Difference
 End-user’s perspective
– Global view to heterogeneous, distributed contents
– Automatic content aggregation
– Semantic search
– Semantic browsing and recommendations
– Other intelligent services (knowledge discovery, personalization,
visualization, …)
 Content publisher’s perspective
– Distributed content creation
– Enriching each other’s contents semantically
– Automated link maintenance
– Shared content publication channel
– Reusing aggregated content in other applications

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But the Lunch is not Free
 More collaboration is need -> complicates work
 Integration of semantic portals with legacy systems
 Manual annotations are costly and may not scale up
 Automatic annotation lowers data quality

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”Intellectuals solve problems
- geniuses prevent them”
Albert Einstein
Key Lesson Learned:
create high quality semantic data
when cataloging

8181
http://seco.cs.aalto.fi/publications
https://www.amazon.com/Publishin
g-Cultural-Heritage-Synthesis-
Technology/dp/1608459977

VIII Encuentros de Centros de Documentación de Arte Contemporáneo en Artium - Eero Hyvönen

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VIII Encuentros de Centros de Documentación de Arte Contemporáneo en Artium - Eero Hyvönen