Resources

This section contains resources and guides on the skills, methods, and tools we will be using for the course. These resources reorganize and augment the list of resources listed under the Content page for each week.

Main resources for the course

• Hadley Wickham et al., R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, Second edition (O’Reilly, 2023), https://r4ds.hadley.nz.
  • This should be your primary go to reference for anything about working with data in R.
• Tidyverse website
  • Website that brings together documentation on the tidyverse packages. If you cannot remember how to do something in the tidyverse, this is a great resource.
• Kieran Healy, Data Visualization: A Practical Introduction, (Princeton University Press, Forthcoming), https://socviz.co.
• Quarto documentation
  • We will be working a lot with quarto documents and creating websites using Quarto. If you need to know how to do something with quarto, go here first.

Bibliography

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Ahnert, Ruth, and Sebastian E. Ahnert. “Protestant Letter Networks in the Reign of Mary I: A Quantitative Approach.” English Literary History 82, no. 1 (2015): 1–33. https://doi.org/10.1353/elh.2015.0000.

Ahnert, Ruth, and Sebastian E. Ahnert. Tudor Networks of Power. Oxford University Press, 2023. https://doi.org/10.1093/oso/9780198858973.001.0001.

Ahnert, Ruth, Sebastian E. Ahnert, Catherine Nicole Coleman, and Scott B. Weingart. The Network Turn: Changing Perspectives in the Humanities. Cambridge University Press, 2020.

Albrecht, Kim, Ruth Ahnert, and Sebastian Ahnert. Tudor Networks. Http://tudornetworks.net/, n.d.

Antonov, Michael, Gábor Csárdi, Szabolcs Horvát, et al. Igraph Enables Fast and Robust Network Analysis Across Programming Languages. arXiv:2311.10260. arXiv, 2023. https://arxiv.org/abs/2311.10260.

Arnold, Taylor, and Lauren Tilton. “New Data? The Role of Statistics in DH.” In Debates in the Digital Humanities 2019, edited by Matthew K. Gold and Lauren F. Klein. University of Minnesota Press, 2019.

Blevins, Cameron. “Space, Nation, and the Triumph of Region: A View of the World from Houston.” Journal of American History 101, no. 1 (2014): 122–47. https://doi.org/10.1093/jahist/jau184.

Broman, Karl W., and Kara H. Woo. “Data Organization in Spreadsheets.” The American Statistician 72, no. 1 (2018): 2–10. https://doi.org/10.1080/00031305.2017.1375989.

Bryan, Jennifer. Excuse Me, Do You Have a Moment to Talk about Version Control? Preprint. PeerJ Preprints, 2017. https://doi.org/10.7287/peerj.preprints.3159v2.

Dombrowski, Quinn. “Minimizing Computing Maximizes Labor.” Digital Humanities Quarterly 16, no. 2 (2022). https://doi.org/10.63744/nkueftfvhghb.

Estrellado, Ryan A., Emily A. Freer, and Isabella C. Velásquez. “What Does Data Science in Education Look Like?” In Data Science in Education Using R. Https://datascienceineducation.com/c03, n.d.

Friendly, Michael, and Howard Wainer. A History of Data Visualization and Graphic Communication. Harvard University Press, 2021.

Healy, Kieran. Data Visualization: A Practical Introduction. Princeton University Press, 2019.

Healy, Kieran, and James Moody. “Data Visualization in Sociology.” Annual Review of Sociology 40, no. 1 (2014): 105–28. https://doi.org/10.1146/annurev-soc-071312-145551.

Kerschbaumer, Florian, Linda Von Keyserlingk-Rehbein, Martin Stark, and Marten Düring, eds. The Power of Networks: Prospects of Historical Network Research. Routledge, 2020. https://doi.org/10.4324/9781315189062.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. Chapter 9 Making Maps with R Geocomputation with R. 2019.

Luhmann, Niklas. Communicating with Slip Boxes: An Empirical Account. Https://luhmann.surge.sh/communicating-with-slip-boxes, 1981.

Medici, Catherine. “Using Network Analysis to Understand Early Modern Women.” Early Modern Women 13, no. 1 (2018): 153–62. https://doi.org/10.1353/emw.2018.0058.

Ognyanova, Katherine. Network Visualization with R. 2025.

Pebesma, Edzer, and Roger Bivand. Spatial Data Science: With Applications in R. 2025.

Rawson, Katie, and Trevor Muñoz. “Against Cleaning.” In Debates in the Digital Humanities 2019, edited by Matthew K. Gold and Lauren F. Klein. University of Minnesota Press, 2019.

Rennie, Nicola. The Art of Data Visualization with Ggplot2: The TidyTuesday Cookbook. CRC Press, 2025.

Risam, Roopika, and Alex Gil. “Introduction: The Questions of Minimal Computing.” Digital Humanities Quarterly 16, no. 2 (2022).

Ryan, Yann C., and Sebastian E. Ahnert. “The Measure of the Archive: The Robustness of Network Analysis in Early Modern Correspondence.” Journal of Cultural Analytics 7 (2021): 57–88. https://doi.org/10.22148/001c.25943.

Schrag, Zachary M. The Princeton Guide to Historical Research. Princeton University Press, 2021. https://doi.org/10.2307/j.ctv1pdrrc9.

Scott, John, and Peter Carrington, eds. The SAGE Handbook of Social Network Analysis. SAGE Publications Ltd, 2014. https://doi.org/10.4135/9781446294413.

Solokov, Alex. “Beyond the Binary: Improving Data Visualization for Intersectional Identities.” Nightingale: Journal of the Data Visualization Society, March 2025.

Tennekes, Martijn, and Jakub Nowosad. Spatial Data Visualization with Tmap: A Practical Guide to Thematic Mapping in R. 2025.

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Wickham, Hadley. “A Layered Grammar of Graphics.” Journal of Computational and Graphical Statistics 19, no. 1 (2010): 3–28. https://doi.org/10.1198/jcgs.2009.07098.

Wickham, Hadley. Ggplot2: Elegant Graphics for Data Analysis. Second Edition. Use R! Springer, 2016. https://doi.org/10.1007/978-3-319-24277-4.

Wickham, Hadley. “Tidy Data.” Journal of Statistical Software 59, no. 10 (2014). https://doi.org/10.18637/jss.v059.i10.

Wickham, Hadley, Mara Averick, Jennifer Bryan, et al. “Welcome to the Tidyverse.” Journal of Open Source Software 4, no. 43 (2019): 1686. https://doi.org/10.21105/joss.01686.

Wikle, Olivia, and Evan Peter Williamson. “Static Web Methodology as a Sustainable Approach to Digital Humanities Projects.” The Code4Lib Journal, no. 60 (April 2025).

Wilke, Claus. Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures. O’Reilly Media, 2019.

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