Appendix A — Books

Just as there is no teaching material specifically focused on digital book history, there are no books on this subject either. Once again, we can only recommend books on related topics.

Arnold, Taylor, and Lauren Tilton. 2015. Humanities Data in R: Exploring Networks, Geospatial Data, Images, and Text. Springer International Publishing. ISBN 978-3-319-20702-5 (Quantitative Methods in the Humanities and Social Sciences)
Bilbro, Rebecca, Tony Ojeda, and Benjamin Bengfort. 2018. Applied Text Analysis with Python. 1st edition. O’Reilly Media, Inc. ISBN 978-1-4919-6303-6
Gavin, Michael. 2023. Literary Mathematics: Quantitative Theory for Textual Studies. Stanford University Press. ISBN 978-1-5036-3282-0 (Stanford Text Technologies.)
Gonzales, Brighid M. 2020. Systems Librarianship: A Practical Guide for Librarians. Bloomsbury Publishing. ISBN 979-8-8818-7951-8 (Practical Guides for Librarians)
Gooding, Paul, Melissa M. Terras, and Sarah Ames, eds. 2025. Library Catalogues as Data: Research, Practice and Usage. Facet Publishing. ISBN 978-1-78330-658-9
Klinke, Harald. 2025. Cultural Data Science: An Introduction to R. Springer Nature Switzerland. ISBN 978-3-031-88130-5. (Quantitative Methods in the Humanities and Social Sciences)
Manovich, Lev. 2020. Cultural Analytics. The MIT Press. ISBN 978-0-262-03710-5
Karsdorp, Folgert, Mike Kestemont, and Allen Riddell. 2021. Humanities Data Analysis: Case Studies with Python. Princeton University Press. ISBN 978-0-691-17236-1
Crymble, Adam. 2021. Technology and the Historian: Transformations in the Digital Age. University of Illinois Press. ISBN 978-0-252-08569-7 (Topics in the Digital Humanities)
Jockers, Matthew L., and Rosamond Thalken. 2020. Text Analysis with R: For Students of Literature. Springer International Publishing. ISBN 978-3-030-39643-5 (Quantitative Methods in the Humanities and Social Sciences)
Nelson, Catherine. 2024. Software Engineering for Data Scientists: From Notebooks to Scalable Systems. O’Reilly. ISBN 978-1-0981-3620-8