1.
The domain as unifier, how focusing on social
history can bring technical fields together
Marieke van Erp
marieke.van.erp@vu.nl

2.
About me
• Researcher in the Computational Lexicology &
Terminology Lab at Vrije Universiteit Amsterdam
• Language Technology + Semantic Web
• Collaborations with humanities, cultural heritage &
information professionals in CATCH, EU FP7 & CLARIAH
projects
image source: http://www.bsbstaalbouw.nl/previews/2010/11/9/media_210_49423_media_210_49423_w600.jpg

3.
Domains
(Social) History
Language
Technology
Semantic Web

4.
Language Technology
• aims to research & develop tools to extract information
from text
• information retrieval, machine translation, deep reading
• majority of the datasets in the field are ‘current’
newspaper texts
• researchers are interested in finding out how their tool
behaves in a different domain

5.
Semantic Web
• aims to create a machine readable Web
• knowledge modelling, formats, knowledge
representation, data sharing
• Linked Open Data cloud provides entry point to many
structured data sources
• many more users could benefit from Semantic Web
technology

6.
(Social) History
• interested in:
• people
• events
• many historians are interested in dealing with:
• larger text corpora
• quantitative methods
image source: https://upload.wikimedia.org/wikipedia/commons/7/74/York_Pioneers'_social_re-union_St_George's_Hall,_Toronto,_March_3,_1911_(HS85-10-23694).jpg

7.
Components
(Social) History
Language
Technology
Semantic Web
knowledge
modelling &
representation
knowledge
knowledge
information
extraction
event extraction
named entity
recognition and linking
vocabularies
vocabularies
entity graphs
standardisation
people & events
statistics
structured data
structured data

8.
• Goal of the project: interlink Rijksmuseum and Sound and Vision
collections through events
• Digital Hermeneutics (History)
• Recognise events and participants in object descriptions (Language
Technology)
• Model events and Narratives (Semantic Web)
• Van Den Akker, C., Legêne, S., Van Erp, M., Aroyo, L., Segers, R., van
Der Meij, L., Van Ossenbruggen, J., Schreiber, G., Wielinga, B., Oomen,
J. and Jacobs, G., 2011, June. Digital hermeneutics: Agora and the
online understanding of cultural heritage. In Proceedings of the 3rd
International Web Science Conference (p. 10). ACM.

9.
Components
(Social) History
Language
Technology
Semantic Web
knowledge
modelling &
representation
event extraction
people
& events

10.
Not only useful for historians
• http://www.newsreader-project.eu
• http://www.understandinglanguagebymachines.org/stories-and-world-views-as-a-
key-to-understanding-language/
• http://www.cltl.nl/projects/current-projects/visualizing-uncertainty-and-perspectives/

11.
• How can computational tools help in analysing digitised
biographies (History)
• Extract person names & information about persons from
text (Language Technology)
• Model relationships between them (SemWeb)

12.
A Prosopography of Dutch Ministers (1575-1815)

13.
Components
(Social) History
Language
Technology
Semantic Web
knowledge
modelling &
representation
named entity recognition
people
& what they did
relationship extraction

14.
WP3

15.
WP3

16.
Components
(Social) History
Language Technology
Semantic Web
knowledge
knowledge modelling
information
extraction
people & events
entity graphs
event
extraction
vocabularies

17.
How to make this happen?

18.
image source: https://static.pexels.com/photos/7096/people-woman-coffee-meeting.jpg

19.
Going forward
• What questions would you like to answer with Language Technology &
Semantic Web?
• What awesome tools & skills do you have?
• What datasets do you have?
• How do you like your coffee?
image source: http://www.independent.ie/incoming/article31308951.ece/ALTERNATES/h342/tea.jpg

20.
http://mariekevanerp.com
Thank you