The domain as unifier, how focusing on social history can bring technical fields together

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