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Linked Data for
Digital Humanities
SW4SH 2015
Victor de Boer
With input from Christophe Guéret, Serge ter Braake,
Niels Ockeloen, Antske Fokkens, Dirk Roorda, Lora
Aroyo, Johan Oomen, Oana Inel, Jan Wielemaker
Victor de Boer
Web & Media Group, CS, VU University Amsterdam
Netherlands Institute for Sound and Vision
Cultural Heritage
Digital History
Linked Data for Development
Digital History
Sub-discipline of digital humanities
Buzzword that people are embracing and at
the same time already getting tired of.
“ ..the use of digital media and computational
analytics for furthering historical practice,
presentation, analysis, or research”
--Wikipedia
Digital History
Part of the effort of historian is moved from
the physical archives to digital ones
Cross-domain collaboration
Img:www.doaks.org, www.dkrz.de
Data-driven research
Fig: Christophe Guéret
Tools and visualisations
http://armstrongdigitalhistory.org/, http://www.vcdh.virginia.edu/courses/fall07/hius401-f/,
http://digitalhistory.unl.edu/essays/thomasessay.php, http://www.philipvickersfithian.com/2013/05/gender-in-stacks-on-managing-small.html
“That is great. I would love that…
…but my research questions are slightly different.”
Img:Monty Python
Better
Enter your
(national) research
infrastructure here
Fig: C. Guéret
Aging
Data Tool
C. Guéret based on http://redmonk.com/jgovernor/2007/04/05/why-applciations-are-like-fish-and-data-is-like0wine/
Even better
Do not bake the data into the tool and treat
data as an end product.
Build tools on top of the data.
Make sure others can do so as well.
Fig: C. Guéret
Framework generic solutions with historians
1. Preprocess, Clean, Model, Link, Enrich data in a collaboration with
domain experts
2. Access heterogeneous datasets in a convenient way to get an
intuition of the character and anomalies of the (linked) data;
3. Perform arbitrary queries to retrieve results relevant to their
research questions;
4. Verify the veracity of query results, by following provenance links
to original material
5. Retrieve and analyze the data with tool of preference.
6. Republish and share results
Linked Data for Digital History
• Represent heterogeneous datasets with their own data models
– In one data format (RDF)
– Link what can be linked to integrate at project level (and beyond)
– Keep specificity of original data
• Links to other sources: re-use knowledge
• Common-sense or very specific
• Digital hermeneutics
• Allow multiple levels of semantic enrichment
– normalization
– through Named Graphs
– Provenance
• Linked Data is the (technically) best way to publish and share your
research data
Some examples
Dutch Ships and Sailors
The Problem:
((Maritime) historical) data is not integrated
• Researchers’ data is “lost”
– In different physical locations
– In different file formats
– In different semantic structures
• In a workshop, we identified 25+
maritime historical datasets.
– http://dutchshipsandsailors.nl
• We do not want to force one
monolithic data model for
integration
The solution: Linked Open Data
• Represent heterogeneous datasets
with their own data models
– In one data format (RDF)
– Link what can be linked to integrate at
project level (and beyond)
– Keep specificity of original data
• Links to other sources: re-use
knowledge
• Allow multiple levels of semantic
enrichment/ normalization
– through Named Graphs
– Provenance
What we did
1. Model four maritime historical datasets as
RDF
– Noordelijke Monsterrollen Database [J. Leinenga]
– Generale Zeemonsterrollen [M. van Rossum]
– Dutch Asiatic Shipping
– VOC Opvarenden
2. Link to each other (based on ships, ship types,
ranks, geography,…)
– Models and links evaluated by domain experts
3. Publish as Linked Open Data
4. Show how this data cloud can lead to new
types of integrated research questions
Modeling in collaboration with historians
dss:Record
gzmvoc:Telling
gzmvoc:telling-1046-De_Berkel
__bnode_1
gzmvoc:aziatischeBemanning
dss:Ship
gzmvoc:Schip
gzmvoc: schip-1046-De_Berkel
dss:has_ship
gzmvoc:schip
"1046"
“Schip”
“De Berkel”
rdfs:label
dss:scheepsnaam
gzmvoc:scheepsnaam
dss:ShipType
gzmvoc:Scheepstype
gzmvoc: type-Ship
dss:has_shiptype
gzmvoc:has_shiptype
gzmvoc:scheepstype
“21”
“Moorse
mattroosen”
dss:azRegistratieKop
gzmvoc:azAantalMatrozen
gzmvoc:telling
gzmvoc:heeft DAS heenreis
dss:Record
das:Voyage
das:voyage-1918_61
DIFFERENT but LINKED DATAMODELS
Modelling principles
Model each dataset as directly as possible
Only “syntactical” transformation to RDF
No normalization
Reusability
Transparency, trust
Normalize and link in second stage
store in separate RDF Named Graphs
Links to Historical Newspapers
[HARLINGEN, 24 October.] …gestrand.
Tevens is het berigt ontvan°e > dat het hier
behoorende schoonerschip Transit,
kapitein Schaap, in de Noordzee is
gezonken, nadat het achterschip was
weggeslagen ; een ligtmatroos verloor
daarbij het leven. Mede zijn hier drie
vreemde schepen met meer en minder
zware averij binnengeloopen.
- Andrea Bravo Balado
DAS
GZMVOC
MDB
VOCOPV
Begunstig
den
VOCOPV
Soldijboek
en
PROV
AAT
VOCOPV
Opvaren
den
foaf
owl:sameAs
dss:hasKBLink
rdfs:subClassOf,
rdfs:subPropertyOf
dss:DAS link
skos :exactMatch
ClioPatria Triplestore
Data live at Huygens Institute for Dutch
History
http://dutchshipsandsailors.nl/data
~30 Million triples
Dev. Server
http://semanticweb.cs.vu.nl/dss
Purl.org URIs redirect to live server w/
content negotiation
SPARQL endpoint
Web interface
Search, browse and query
• SPARQL for R package
Data analysis and visualisation
Dutch Ships and Sailors
• Linked Data principles are a great fit to digital
history requirements
– Heterogeneous models/datasets, light-weight
reusable integration
– Multiple levels of normalisation, through separate
named graphs
– SW Provenance matches Historical Provenance
• Watch out when you sail your Schooner into the
North Sea
DIVE
DIGITAL HUMANITIES RESEARCHERS
MediaresearcherLarsArveRøsslandoftheUniversityofBergen.(Photo:AndreasR.Graven)
EXPLORATIVE SEARCH
Digital Hermeneutics: The combination of digital
(Web) technology and theory of interpretation
Builds on AGORA PROJECT
Slide: Lora Aroyo
DATA: OPENIMAGES.EU
Open videos Netherlands Institute for Sound and Vision
~3000, mostly news broadcasts
Descriptions
DATA: DELPHER.NL
Scans of Radio bulletins (hand annotated)
1937 – 1984
1.5 Million OCR’ed and NErred
ENTITY EXTRACTION
CROWDTRUTH.ORG
ENTITY EXTRACTION
EVENTS CROWDSOURCING AND LINKING TO
CONCEPTS THROUGH CROWDTRUTH.ORG
SEGMENTATION & KEYFRAMES
LINKING EVENTS AND
CONCEPTS TO KEYFRAMES
SIMPLE EVENT MODEL (SEM),
OPENANNOTATION (OA) AND SKOS
DIVE:MEDIA OBJECT SEM:EVENT
SEM:PLACE
SEM:TIME
SEM:ACTOR
SKOS:CONCEPT
OA:ANNOTATION
LINKS TO EUROPEANA (MULTILINGUAL)
LINKS TO DBPEDIA
DIGITAL SUBMARINE UI
https://www.flickr.com/photos/benjcarson/245171885
https://www.flickr.com/photos/mibuchat/2774251415
INFINITY OF EXPLORATION
DEMO
DIVE.BEELDENGELUID.NL
DIVE
Data conversion pipeline includes
crowdsourcing, text analysis
Again provenance
Generic browsing doesn’t have to be boring
BiographyNet
Biographynet.nl
Starting point
Starting Point: Biography Portal of the
Netherlands; www.biografischportaal.nl
125,000 short biographical descriptions with limited
metadata from 23 Dutch biographical dictionaries
(~76,000 individuals)
What kind of historical questions can be
answered with these data with the help of
computational methods
Biographynet.nl
Methods developed in collaboration
Biographynet.nl
Biographynet conversion
Biographynet.nl
Johan Rudolph Thorbecke werd
in 1798 geboren op 14 januari
in Zwolle en komt uit een half-Duit
Johan Rudolph Thorbecke werd
in 1798 geboren op 14 januari
in Zwolle en komt uit een half-Duit
Linked Data for
BiograpyNet
Thorbecke
Biographical
Description
Provenance
Meta Data
NNBW
Person
Meta Data
“Thorbecke”
Biography
Parts
Birth
1798
Event
Biographical
Description
Enrichment NLP Tool
Person
Meta Data
Event
Birth
Johan Rudolph Thorbecke werd
in 1798 geboren op 14 januari
in Zwolle en komt uit een half-Duit
Zwolle
1798-01-14
Biographynet.nl
a
Provenance in Biographynet
Ensure credibility of the demonstrator, to evaluate its
performance and to improve the academic status of the tool
Information involved Sources, but also: NER input data, etc.
Processes involved All steps in enrichment, aggregation…
People involved Who was responsible for pipeline, tool,
Includes P-PLAN:* Allows for comparing the actual activity
and its input/output with the original plan and its variables
Biographynet.nl*Daniel Garijo, Yolanda Gil; http://www.opmw.org/model/p-plan
Interface for historians (mockup)
Biographynet.nl
Biographynet.nl
Biographynet
Data sustainably stored at historical research institute
Structured data accessible as LOD
Provenance through deep linking into enrichment
Generic browse / compare functionality for broad
historic research (prosopography)
Re-usability
Biographynet.nl
Verrijkt Koninkrijk
Het Koninkrijk der Nederlanden in de Tweede Wereldoorlog
History of German occupied Dutch society (1940-1945)
Published 1969 - 1991 in 14 volumes, 30 parts, 18.000 pages
1. Digitization
2. Open Data
3. Enriched access with Linked Data
Verrijkt Koninkrijk
Step 1: Lou de Jong’s “Het Koninkrijk” was digitized and made
available in a reusable format
Step 2: Named Entity Recognition and consolidation of the back-of-
the-book index provide structured vocabularies with links into the text
country, collection, doc-type, volume, chapter, section, sub-section, paragraph
Back-of-the-Book index Named Entities
Verrijkt Koninkrijk
Step 3: Enrichment with Linked Data makes new ways of
interaction and analysis possible
Back-of-the-Book index Named Entities
niod:Blitzkrieg
niod:oai_wo2_niod_nl_rec_102045
dct:subject
http://resolver.verrijktkoninkrijk.nl/nl.vk.d.reg.4.1386
botb:Blitzkrieg
skos:exactMatch
52
National-
Socialist
29%
Social-
Democrat
21%
Protestant
13%
Liberal
12%
R-Catholic
12%
Communist
8%
Jewish
5%
http://semanticweb.cs.vu.nl/verrijktkoninkrijk/
http://search.loedejongdigitaal.nl/
Results are links to paragraphs
re-usability
Reuse in comparative interface
Quantifying Historical Perspectives on WWII
http://qhp.science.uva.nl/
Verrijkt Koninkrijk
Textual data in digital repositories
Structured data accessible as LOD
Provenance
Simple tooling for primary research project
Re-usability
Shebanq
http://shebanq.ancient-data.org/
Nanopublications in digital history
Cf. http://www.slideshare.net/schambers3/nanopublications-in-the-arts-and-humanities
Shebanq
Source material shared in sustainable repo
Queries and metadata shared among
researchers
Working on Linked Data model based on
OpenAnnotation
Historical tool / data criticism
What happens between question/query and answer?
What happened to the original data?
Can we make the complex computer processes understandable
for ‘lay’ people?
A detailed and understandable (these two match poorly)
description of the process of preprocessing and enrichments
A detailed description of the way the data is visualized and the
choices made in the design
Historical tool criticism
… willingness from historians to invest the time to
learn about computer processes (at least the basic
principles)
Possibilities for education at universities to bridge
the gap between computer science and humanities
studies and make tool criticism an integral part of
student’s curricula
“Why do we still teach history student to decipher
17th Century handwriting, but not SQL”
Thank you!
Victor de Boer
http://victordeboer.com
v.de.boer@vu.nl
@victordeboer
Backup slides
MultimediaN E-Culture project (2006)
Museums have increasingly nice websites
But: most of them are driven by stand-alone collection
databases
Data is isolated, both syntactically and semantically
If users can do cross-collection search, the individual
collections become more valuable!
Semantic Search
E-Culture data cloud
Vocabulary alignment
“Easel-pieces”
RMA concept
“Schilderij”
RMA is the thesaurus
of Rijksmuseum
AAT artefact type
“Easel Piece”
“Painting”
AAT is Getty’s
Art & Architecture Thesaurus
http://e-culture.multimedian.nl/

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Sw4 sh slides

  • 1. Linked Data for Digital Humanities SW4SH 2015 Victor de Boer With input from Christophe Guéret, Serge ter Braake, Niels Ockeloen, Antske Fokkens, Dirk Roorda, Lora Aroyo, Johan Oomen, Oana Inel, Jan Wielemaker
  • 2. Victor de Boer Web & Media Group, CS, VU University Amsterdam Netherlands Institute for Sound and Vision Cultural Heritage Digital History Linked Data for Development
  • 3. Digital History Sub-discipline of digital humanities Buzzword that people are embracing and at the same time already getting tired of. “ ..the use of digital media and computational analytics for furthering historical practice, presentation, analysis, or research” --Wikipedia
  • 4. Digital History Part of the effort of historian is moved from the physical archives to digital ones Cross-domain collaboration Img:www.doaks.org, www.dkrz.de
  • 6. Tools and visualisations http://armstrongdigitalhistory.org/, http://www.vcdh.virginia.edu/courses/fall07/hius401-f/, http://digitalhistory.unl.edu/essays/thomasessay.php, http://www.philipvickersfithian.com/2013/05/gender-in-stacks-on-managing-small.html
  • 7. “That is great. I would love that… …but my research questions are slightly different.” Img:Monty Python
  • 9. Aging Data Tool C. Guéret based on http://redmonk.com/jgovernor/2007/04/05/why-applciations-are-like-fish-and-data-is-like0wine/
  • 10. Even better Do not bake the data into the tool and treat data as an end product. Build tools on top of the data. Make sure others can do so as well. Fig: C. Guéret
  • 11. Framework generic solutions with historians 1. Preprocess, Clean, Model, Link, Enrich data in a collaboration with domain experts 2. Access heterogeneous datasets in a convenient way to get an intuition of the character and anomalies of the (linked) data; 3. Perform arbitrary queries to retrieve results relevant to their research questions; 4. Verify the veracity of query results, by following provenance links to original material 5. Retrieve and analyze the data with tool of preference. 6. Republish and share results
  • 12. Linked Data for Digital History • Represent heterogeneous datasets with their own data models – In one data format (RDF) – Link what can be linked to integrate at project level (and beyond) – Keep specificity of original data • Links to other sources: re-use knowledge • Common-sense or very specific • Digital hermeneutics • Allow multiple levels of semantic enrichment – normalization – through Named Graphs – Provenance • Linked Data is the (technically) best way to publish and share your research data
  • 14. Dutch Ships and Sailors
  • 15. The Problem: ((Maritime) historical) data is not integrated • Researchers’ data is “lost” – In different physical locations – In different file formats – In different semantic structures • In a workshop, we identified 25+ maritime historical datasets. – http://dutchshipsandsailors.nl • We do not want to force one monolithic data model for integration
  • 16. The solution: Linked Open Data • Represent heterogeneous datasets with their own data models – In one data format (RDF) – Link what can be linked to integrate at project level (and beyond) – Keep specificity of original data • Links to other sources: re-use knowledge • Allow multiple levels of semantic enrichment/ normalization – through Named Graphs – Provenance
  • 17. What we did 1. Model four maritime historical datasets as RDF – Noordelijke Monsterrollen Database [J. Leinenga] – Generale Zeemonsterrollen [M. van Rossum] – Dutch Asiatic Shipping – VOC Opvarenden 2. Link to each other (based on ships, ship types, ranks, geography,…) – Models and links evaluated by domain experts 3. Publish as Linked Open Data 4. Show how this data cloud can lead to new types of integrated research questions
  • 18. Modeling in collaboration with historians dss:Record gzmvoc:Telling gzmvoc:telling-1046-De_Berkel __bnode_1 gzmvoc:aziatischeBemanning dss:Ship gzmvoc:Schip gzmvoc: schip-1046-De_Berkel dss:has_ship gzmvoc:schip "1046" “Schip” “De Berkel” rdfs:label dss:scheepsnaam gzmvoc:scheepsnaam dss:ShipType gzmvoc:Scheepstype gzmvoc: type-Ship dss:has_shiptype gzmvoc:has_shiptype gzmvoc:scheepstype “21” “Moorse mattroosen” dss:azRegistratieKop gzmvoc:azAantalMatrozen gzmvoc:telling gzmvoc:heeft DAS heenreis dss:Record das:Voyage das:voyage-1918_61 DIFFERENT but LINKED DATAMODELS
  • 19. Modelling principles Model each dataset as directly as possible Only “syntactical” transformation to RDF No normalization Reusability Transparency, trust Normalize and link in second stage store in separate RDF Named Graphs
  • 20. Links to Historical Newspapers [HARLINGEN, 24 October.] …gestrand. Tevens is het berigt ontvan°e > dat het hier behoorende schoonerschip Transit, kapitein Schaap, in de Noordzee is gezonken, nadat het achterschip was weggeslagen ; een ligtmatroos verloor daarbij het leven. Mede zijn hier drie vreemde schepen met meer en minder zware averij binnengeloopen. - Andrea Bravo Balado
  • 22. ClioPatria Triplestore Data live at Huygens Institute for Dutch History http://dutchshipsandsailors.nl/data ~30 Million triples Dev. Server http://semanticweb.cs.vu.nl/dss Purl.org URIs redirect to live server w/ content negotiation SPARQL endpoint Web interface
  • 24. • SPARQL for R package Data analysis and visualisation
  • 25. Dutch Ships and Sailors • Linked Data principles are a great fit to digital history requirements – Heterogeneous models/datasets, light-weight reusable integration – Multiple levels of normalisation, through separate named graphs – SW Provenance matches Historical Provenance • Watch out when you sail your Schooner into the North Sea
  • 26. DIVE
  • 27. DIGITAL HUMANITIES RESEARCHERS MediaresearcherLarsArveRøsslandoftheUniversityofBergen.(Photo:AndreasR.Graven) EXPLORATIVE SEARCH Digital Hermeneutics: The combination of digital (Web) technology and theory of interpretation
  • 28. Builds on AGORA PROJECT Slide: Lora Aroyo
  • 29.
  • 30. DATA: OPENIMAGES.EU Open videos Netherlands Institute for Sound and Vision ~3000, mostly news broadcasts Descriptions
  • 31. DATA: DELPHER.NL Scans of Radio bulletins (hand annotated) 1937 – 1984 1.5 Million OCR’ed and NErred
  • 32. ENTITY EXTRACTION CROWDTRUTH.ORG ENTITY EXTRACTION EVENTS CROWDSOURCING AND LINKING TO CONCEPTS THROUGH CROWDTRUTH.ORG SEGMENTATION & KEYFRAMES LINKING EVENTS AND CONCEPTS TO KEYFRAMES
  • 33. SIMPLE EVENT MODEL (SEM), OPENANNOTATION (OA) AND SKOS DIVE:MEDIA OBJECT SEM:EVENT SEM:PLACE SEM:TIME SEM:ACTOR SKOS:CONCEPT OA:ANNOTATION LINKS TO EUROPEANA (MULTILINGUAL) LINKS TO DBPEDIA
  • 36. DIVE Data conversion pipeline includes crowdsourcing, text analysis Again provenance Generic browsing doesn’t have to be boring
  • 38. Starting point Starting Point: Biography Portal of the Netherlands; www.biografischportaal.nl 125,000 short biographical descriptions with limited metadata from 23 Dutch biographical dictionaries (~76,000 individuals) What kind of historical questions can be answered with these data with the help of computational methods Biographynet.nl
  • 39. Methods developed in collaboration
  • 42. Johan Rudolph Thorbecke werd in 1798 geboren op 14 januari in Zwolle en komt uit een half-Duit Johan Rudolph Thorbecke werd in 1798 geboren op 14 januari in Zwolle en komt uit een half-Duit Linked Data for BiograpyNet Thorbecke Biographical Description Provenance Meta Data NNBW Person Meta Data “Thorbecke” Biography Parts Birth 1798 Event Biographical Description Enrichment NLP Tool Person Meta Data Event Birth Johan Rudolph Thorbecke werd in 1798 geboren op 14 januari in Zwolle en komt uit een half-Duit Zwolle 1798-01-14 Biographynet.nl
  • 43. a Provenance in Biographynet Ensure credibility of the demonstrator, to evaluate its performance and to improve the academic status of the tool Information involved Sources, but also: NER input data, etc. Processes involved All steps in enrichment, aggregation… People involved Who was responsible for pipeline, tool, Includes P-PLAN:* Allows for comparing the actual activity and its input/output with the original plan and its variables Biographynet.nl*Daniel Garijo, Yolanda Gil; http://www.opmw.org/model/p-plan
  • 44. Interface for historians (mockup) Biographynet.nl
  • 46. Biographynet Data sustainably stored at historical research institute Structured data accessible as LOD Provenance through deep linking into enrichment Generic browse / compare functionality for broad historic research (prosopography) Re-usability Biographynet.nl
  • 48. Het Koninkrijk der Nederlanden in de Tweede Wereldoorlog History of German occupied Dutch society (1940-1945) Published 1969 - 1991 in 14 volumes, 30 parts, 18.000 pages 1. Digitization 2. Open Data 3. Enriched access with Linked Data Verrijkt Koninkrijk
  • 49. Step 1: Lou de Jong’s “Het Koninkrijk” was digitized and made available in a reusable format Step 2: Named Entity Recognition and consolidation of the back-of- the-book index provide structured vocabularies with links into the text country, collection, doc-type, volume, chapter, section, sub-section, paragraph Back-of-the-Book index Named Entities
  • 50. Verrijkt Koninkrijk Step 3: Enrichment with Linked Data makes new ways of interaction and analysis possible Back-of-the-Book index Named Entities
  • 53. Results are links to paragraphs
  • 55. Reuse in comparative interface Quantifying Historical Perspectives on WWII http://qhp.science.uva.nl/
  • 56. Verrijkt Koninkrijk Textual data in digital repositories Structured data accessible as LOD Provenance Simple tooling for primary research project Re-usability
  • 58. Nanopublications in digital history Cf. http://www.slideshare.net/schambers3/nanopublications-in-the-arts-and-humanities
  • 59. Shebanq Source material shared in sustainable repo Queries and metadata shared among researchers Working on Linked Data model based on OpenAnnotation
  • 60. Historical tool / data criticism What happens between question/query and answer? What happened to the original data? Can we make the complex computer processes understandable for ‘lay’ people? A detailed and understandable (these two match poorly) description of the process of preprocessing and enrichments A detailed description of the way the data is visualized and the choices made in the design
  • 61. Historical tool criticism … willingness from historians to invest the time to learn about computer processes (at least the basic principles) Possibilities for education at universities to bridge the gap between computer science and humanities studies and make tool criticism an integral part of student’s curricula “Why do we still teach history student to decipher 17th Century handwriting, but not SQL”
  • 62. Thank you! Victor de Boer http://victordeboer.com v.de.boer@vu.nl @victordeboer
  • 63.
  • 65. MultimediaN E-Culture project (2006) Museums have increasingly nice websites But: most of them are driven by stand-alone collection databases Data is isolated, both syntactically and semantically If users can do cross-collection search, the individual collections become more valuable! Semantic Search
  • 67. Vocabulary alignment “Easel-pieces” RMA concept “Schilderij” RMA is the thesaurus of Rijksmuseum AAT artefact type “Easel Piece” “Painting” AAT is Getty’s Art & Architecture Thesaurus

Editor's Notes

  1. Humanities research foc As (digital) humanities researchers seek more (international and cross-domain) collaboration, integrating humanities datasets becomes more important to those researchers. One subdomain where this is very much prevalent is in (social) historical research. Often historical researchers collect data from historical archives for their specific research questions. However, these datasets are often not presented in sharable formats to other researchers. If they are shared at all, the datasets are published in a multitude of formats. To further the digital history agenda, it has been recognized that representing and sharing data is key [4, 10].
  2. “Published between 1969 and 1991, the 30 volumes still combine the qualities of an authoritative work for a general audience, and an inevitable point of reference for scholars” Digitized version online in 2011, crashing the server
  3. VIC: update namespaces
  4. How can we facilitate building applications on top of Linked Cultural Data
  5. TODO: Add here