1. 1. Introduction Visualization Methods Medieval Corpus Conclusion Medieval Literature in Modern Times: Visualization Methods Olga Scrivner Indiana University HASTAC 2015 1 / 24
2. 2. Introduction Visualization Methods Medieval Corpus Conclusion Merging Digital Humanity and Medieval Collections 20th century 2 / 24
3. 3. Introduction Visualization Methods Medieval Corpus Conclusion Merging Digital Humanity and Medieval Collections 20th century 21th century http://cosmolearning.org/videos/bayeux-tapestry-animated-version/2 / 24
4. 4. Introduction Visualization Methods Medieval Corpus Conclusion Digital Collection Types 1 Collection of scanned images (Metadata search) http://libwww.freelibrary.org/medievalman/ 3 / 24
5. 5. Introduction Visualization Methods Medieval Corpus Conclusion Digital Collection Types 2 Encoded collection (Text search) http://www.tei-c.org/release/doc/tei-p5-doc/en/html/MS.html 4 / 24
6. 6. Introduction Visualization Methods Medieval Corpus Conclusion Digital Humanity Manifesto 2.0 (2009) 1st Wave: The rst wave of digital humanities work was quantitative, mobilizing the search and retrieval powers of the database, automating corpus linguistics, stacking hypercards into critical arrays 2nd Wave: The second wave is qualitative, interpretive, experiential, emotive, generative in character, concentrating on new publication models and tools for creating and curating digital repositories (Berry, 2011) 5 / 24
7. 7. Introduction Visualization Methods Medieval Corpus Conclusion 3rd Wave (Berry, 2011) Concentration on the computationality, search, retrieval and analysis originated in humanity-based work. 6 / 24
8. 8. Introduction Visualization Methods Medieval Corpus Conclusion Visual Analytics in Literature Visual Analytics - The science of analytical reasoning facilitated by visual interactive interfaces (Thomas et all., 2005) Graphs, maps and trees for literature analysis (Moretti, 2005) 7 / 24
9. 9. Introduction Visualization Methods Medieval Corpus Conclusion Visual Analytics in Literature Word clouds to analyze a novel (Vuillemot et al., 2009) 8 / 24
10. 10. Introduction Visualization Methods Medieval Corpus Conclusion Visual Analytics in Literature Social network graphs of characters in Greek tragedies (Rydberg-Cox, 2011) 9 / 24
11. 11. Introduction Visualization Methods Medieval Corpus Conclusion Visual Analytics in Literature Literary ngerprint and summaries (Oelke et al., 2012) 10 / 24
12. 12. Introduction Visualization Methods Medieval Corpus Conclusion Visual Analytics in Literature Tracking emotion and sentiment in fairy tales (Mohammad, 2012) 11 / 24
13. 13. Introduction Visualization Methods Medieval Corpus Conclusion Goals 1 Make Medieval literature accessible and interactive 2 Develop methods for multi-level annotation 3 Explore novel visualization techniques http: //www.netanimations.net/Moving-picture-treasure-chest-with-shining-gold-animated-gif.gif 12 / 24
14. 14. Introduction Visualization Methods Medieval Corpus Conclusion Current project - Medieval Occitan Occitan (Provencal) constitutes an important element of the literary, linguistic, and cultural heritage in the history of Romance languages 13 / 24
15. 15. Introduction Visualization Methods Medieval Corpus Conclusion Current project - Medieval Occitan Occitan (Provencal) constitutes an important element of the literary, linguistic, and cultural heritage in the history of Romance languages Provencal poetry is a predecessor of French lyrics Occitan is the only administrative language in Medieval France, besides Latin (Belasco,1990) 13 / 24
16. 16. Introduction Visualization Methods Medieval Corpus Conclusion The 13th century Romance of Flamenca The nest and most striking example of all medieval romances (Muscatine, 1957) This romance presents a very intriguing love story between the beautiful Flamenca, who is imprisoned in a tower by her jealous husband Archambaut, and the sharp-witted knight Guillem.14 / 24
17. 17. Introduction Visualization Methods Medieval Corpus Conclusion Corpus Annotation: XML and HTML Interactive online database with access to a glossary, to translations of verses, and to comments (Meyer, 1895,1901) http://nlp.indiana.edu/~obscrivn/Introduction.html 15 / 24
18. 18. Introduction Visualization Methods Medieval Corpus Conclusion Parallel Alignment: English-Old Occitan 16 / 24
19. 19. Introduction Visualization Methods Medieval Corpus Conclusion Search Tool ANNIS Annotation levels: word, lemma, part of speech, syntactic category, speakers, events, emotion, sentiment, parallel alignment 17 / 24
20. 20. Introduction Visualization Methods Medieval Corpus Conclusion Sentiment Analysis (Plutchik, 1980) (Mohammed, 2011)18 / 24
21. 21. Introduction Visualization Methods Medieval Corpus Conclusion User-Friendly Query Interface in ANNIS http://nlp.indiana.edu:8085/annis-gui-3.1.7/19 / 24
22. 22. Introduction Visualization Methods Medieval Corpus Conclusion Google Charts (GoogleViz R package) https://code.google.com/p/google-motion-charts-with-r/ 20 / 24
23. 23. Introduction Visualization Methods Medieval Corpus Conclusion Google Charts mychart < gvisLineChart(df, xvar=event, yvar=c(positive, negative) plot(mychart)21 / 24
24. 24. Introduction Visualization Methods Medieval Corpus Conclusion Motion Charts Motion=gvisMotionChart(df, idvar=emotion, timevar=event) plot(Motion) 22 / 24
25. 25. Introduction Visualization Methods Medieval Corpus Conclusion Discussion 1 Which visual analytics techniques can be applied in your digital projects? 23 / 24
26. 26. Introduction Visualization Methods Medieval Corpus Conclusion Discussion 1 Which visual analytics techniques can be applied in your digital projects? 2 How much programming is needed in Digital Humanity? http://www.bible-history.com/babylonia/literature.gif 23 / 24
27. 27. Introduction Visualization Methods Medieval Corpus Conclusion References Mohammad, Saif. 2013. From Once Upon a Time to Happily Ever After: Tracking Emotions in Novels and Fairy Tales. In Proceedings of the ACL Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH), 2011, Portland, OR. Moretti, Franco. 2005. Graphs, maps, trees: abstract models for a literary history. R.R. Donnelley & Sons. Oelke, Daniela, Dimitrios Kokkinakis and Mats Malm. 2012. Advanced Visual Analytics Methods for Literature Analysis. In Proceedings of the 6th EACL Workshop, 35-44. Rydberg-Cox, Je. 2011. Social Networks and the Language of Greek Tragedy. Journal of the Chicago Colloquium on Digital Humanities and Computer Science. 1(3): 1-11. Thomas, James and Kristin Cook. 2005. Illuminating the Path: the Research and Development Agenda for Visual Analytics. National Visualization and Analytics Center. Vuillemot, Romain, Tanya Clement, Catherine Plaisant and Amit Kumar. 2009. Whats Being Near Martha? Exploring Name Entities in Literary Text Collections. In Proceedings if the IEEE Symposium. Atlantic City, New Jersey. 107-114. 24 / 24