DC Session 9 Visualisation

Sunoikisis Digital Classics, Spring 2020

Session 9. Text and data visualisation

Thursday March 12, 16:00 UK = 17:00 CET

Convenors: Aurélien Berra (Université Paris Nanterre), Matteo Romanello (École polytechnique fédérale de Lausanne)

YouTube link: https://youtu.be/KGtFcNQndog

Slides: Spring-2020-session-9-slides.pdf

Session outline

1. Introduction to data visualisation
2. Visualisation in textual analysis: exploring Homer in Voyant Tools and beyond
3. An example of visualisation for Digital Classics research: “Cited Loci of the Aeneid”

Seminar readings

• Hawkins, Laura F., “Computational Models for Analyzing Data Collected from Reconstructed Cuneiform Syllabaries”, Digital Humanities Quarterly 12.1, 2018, http://digitalhumanities.org:8081/dhq/vol/12/1/000368/000368.html.
• Rockwell, Geoffrey and Sinclair, Stéfan, “The Swallow Flies Swiftly Through: An Analysis of Humanist”, in Hermeneutica. Computer-Assisted Interpretation in the Humanities, Cambridge, Massachusetts, MIT Press, 2016, http://hermeneuti.ca/swallow-flies.

Other resources

• Data visualisation galleries
  • Holtz, Yan and Healy, Conor, From Data to Viz, https://www.data-to-viz.com, 2018.
  • Holtz, Yan, The R Graph Gallery, http://r-graph-gallery.com, 2018.
  • Holtz, Yan, The Python Graph Gallery, https://python-graph-gallery.com, 2017.
  • Kucher, Kostiantyn and Kerren, Andreas, Text Visualization Browser, https://textvis.lnu.se/, 2015.
• Healy, Kieran, Data Visualization: A Practical Introduction, Princeton, Princeton University Press, 2019, https://press.princeton.edu/books/hardcover/9780691181615/data-visualization – online draft, 2018, http://socviz.co/.
• Wilke, Claus O., Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, Sebastopol, CA, O’Reilly Media, 2019. Website version, 2019, https://serialmentor.com/dataviz/ – see especially chap. 5, “Directory of visualizations”, https://serialmentor.com/dataviz/directory-of-visualizations.html.
• Seeing Data. Developing Visualisation Literacy, 2016, http://seeingdata.org/.

Further reading

• Drucker, Johanna, “Humanities Approaches to Graphical Display”, Digital Humanities Quarterly 5.1, 2011, http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html.
• Friendly, Michael, “A Brief History of Data Visualization”, in Handbook of Computational Statistics: Data Visualization, Springer Verlag, 2006, 15-56. Available: http://www.datavis.ca/papers/hbook.pdf.
• Glinka K., Pietsch C. and Dörk M., “Past Visions and Reconciling Views: Visualizing Time, Texture and Themes in Cultural Collections”, Digital Humanities Quarterly 11, 2017. Available: http://digitalhumanities.org/dhq/vol/11/2/000290/000290.html.
• Jockers, Matthew, Text Analysis with R for Students of Literature, New York, Springer, 2014.
• Rockwell, Geoffrey and Sinclair, Stéfan, Hermeneutica. Computer-Assisted Interpretation in the Humanities, Cambridge, Massachusetts, MIT Press, 2016. Companion website: http://hermeneuti.ca.
• Rockwell, Geoffrey, “What is Text Analysis, Really?”, Literary and Linguistic Computing 18.2, 2003, 209-219. Available: http://www.geoffreyrockwell.com/publications/WhatIsTAnalysis.pdf.
• Schöch, Christof, “Big? Smart? Clean? Messy? Data in the Humanities”, Journal of Digital Humanities 2.3, 2013, http://journalofdigitalhumanities.org/2-3/big-smart-clean-messy-data-in-the-humanities/.
• Silge, Julia and Robinson, David, Text Mining with R, O’Reilly, 2017, http://tidytextmining.com/.
• Sinclair, Stéfan and Rockwell, Geoffrey, Voyant Tools, 2016, http://voyant-tools.org/. Tutorial: https://voyant-tools.org/docs/#!/guide/tutorial.
• Tufte, Edward R., The Visual Display of Quantitative Information, Cheshire, Connecticut, Graphic Press, 2nd ed., 2001.
• Wickham, Hadley and Grolemund, Garrett, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, O’Reilly Media, 2017, http://r4ds.had.co.nz/ – especially chap. 3, “Data visualisation”, https://r4ds.had.co.nz/data-visualisation.html.
• Wickham, Hadley, Ggplot2: Elegant Graphics for Data Analysis, New York, Springer, 2010 [1st ed. 2009].
• Wilkinson, Leland and Wills, Graham, The Grammar of Graphics, New York, Springer, 2005.

Exercise

• Select an Ancient Greek or Latin text to analyse and import it into Voyant Tools
• Explore several visualisations, and test the effect of applying a stopword list to understand the interest of this typical pre-processing step (Voyant provides customisable lists for both languages)
• Visualise and reflect: What do you observe? Which types of visualisation were most useful to get insights into this corpus, and why? Which visualisation seemed most obscure or least useful?
• Do the same analysis again on a lemmatised text (if you have used one of the texts suggested below, we also provide lemmatised versions): What is the impact of such linguistic annotation on the visualisations produced by Voyant?

Suggested texts (if you have no preferences):

• Iliad

  • Monro-Allen 1920 edition in Perseus (XML)
  • Lemmatised version of this edition (TXT) – extracted from the full morphosyntactic analysis in Perseus treebank data (XML)

• Odyssey

  • Murray 1919 edition in Perseus (TXT) and same edition in one compressed file with separate files for the books (ZIP, can be loaded into Voyant to get one “document” per book)
  • Lemmatised version of Murray edition in Perseus (TXT) – extracted from the full morphosyntactic analysis in Perseus treebank data (XML) – and lemmatised files for the same edition (ZIP)

• Sallust

  • Ahlberg 1919 edition (TXT) – extracted from the full morphosyntactic analysis in Perseus treebank data (XML)
  • Lemmatised version of Ahlberg edition (TXT) – extracted from the same source

For more texts, see Perseus Greek texts (XML) and Perseus Latin texts (XML).