Applied Data Analysis - Digital Humanities at Oxford Summer School 2026

This strand offers a stepping stone for those who have begun to learn python and want to apply it in their own work and research. It provides a practical foundation for humanities scholars and GLAM professionals, covering topics including: python packages for data analysis (pandas); how to get from messy to tidy data; basics of data analysis and visualization (matplotlib and plotly); geo mapping (geopandas); network analysis (networkx and gephi); and a range of natural language processing methods.

Classes are hands-on and interactive, and we will work with real-world data from the GLAM sector. Attendees are encouraged to bring their own projects and data to work on, and will receive practical support and advice tailored to their work.

This is an advanced workshop: familiarity with the main concepts of Python programming is required (e.g. main data types, `for` loops, `if/else` statements, using and writing functions). This could be acquired for example via previous attendance of the Text2Tech workshop or equivalent courses or self-learning.

We have prepared a "Python requirements check" notebook, available in two formats:
1° As a static notebook in the course's GitHub repository: https://github.com/dhlab-epfl/ADA-DHOxSS/blob/main/notebooks/0_python_assessment.ipynb

2° As a runnable online notebook in GoogleColab: https://colab.research.google.com/github/dhlab-epfl/ADA-DHOxSS/blob/main/notebooks/0_python_assessment.ipynb This second solution might be preferable to those who have not installed Python yet.

⚠️ After completing the requirements check, students are kindly asked to complete the following questionnaire as soon as possible: ADA-DHOxSS August 2025

If you are at ease with most of topics the questionnaire covers, you meet the programming requirements for this workshop. But do not worry if that is not the case entirely, there will be plenty of time to ask questions.

Exact timings are subject to change before summer school commences.

09:00 - 10:30: Opening Keynote: Information & Interaction: Scholarship at the Nexus of (Hu)Man and Machine

Abstract: The Digital Humanities are a broad community. It embraces methodological diversity, and brings together domain experts from across the wide landscape of the Humanities. Events such as the DHOxSS stand as testament to the richness of the field, and present us with unique opportunities for information exchange, knowledge acquisition, and upskilling. This talk takes a moment to recognise the community of DHers that has contributed to a body of work that uses the Linked Data information publication paradigm with datasets from the Humanities. These projects are case study examples that celebrate the ways in which the Digital Humanities are not just about developing computational systems, but also about the immense value and effect of human infrastructure as part of our research.

Speaker: Dr Terhi Nurmikko-Fuller (RMIT University)

Dr Terhi Nurmikko-Fuller is an Associate Professor, Information Interaction at the School of Computing Technologies at RMIT University in Melbourne, Australia.

10:30-11:00 Refreshment break

11:00-12:30 Introduction to Applied Data Analysis

Presentation of the strand, objectives and schedule
Introductions
Example of a data analysis application
Setting up systems

Speakers: Ellen Charlesworth and Alexander Shiarella

12.30-14:00 Lunch

14:00-15:30 The Basics – Using Pandas

Intro to Pandas: data types (series, dataframes)
Data loading
Data access (indexing)

Speakers: Ellen Charlesworth and Alexander Shiarella

15:30-16:00 Refreshment break

16:00-17:00 Project Session

Abstract:

Catching-up: assistance is provided to clarify any issue from the previous classes or in setting-up your Python environment.
Project: Attendees should bring their own mini-project to the class and work on it, individually or with others. This typically will require bringing your own data, although we can also provide some sample datasets.

09:00-10:30 Tidy data (part I)

* Why we clean data and the 80/20 rule

* Basic concepts of tidy data

Speakers: Ellen Charlesworth and Alexander Shiarella

10:30-11:00 Refreshment break

11:00-12:30 Tidy data (part II)

Manipulating data with Pandas
Operations on tidy data frames:
- - set, union join
- - select, apply transform

Speakers: Ellen Charlesworth and Alexander Shiarella

12:30-14:00 Lunch

14:00-15:30 Continuation of Tidy Data / Project Session

Catching-up: assistance will be provided for anyone with follow-up questions or remaining issues from the earlier sessions.
Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

Speakers: Ellen Charlesworth and Alexander Shiarella

15:30-16:00 Refreshment break

16:00 -17:00: Project session

Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

09:00-10:30 Data Handling (Part I)

Basic plotting, descriptions, analysis

Speakers: Ellen Charlesworth and Alexander Shiarella

10:30-11:00 Refreshment break

11:00-12:30 Data Handling (Part II)

Plotting with Pandas, matplotlib, seaborn, and plotly
Working with texts

Speakers: Ellen Charlesworth and Alexander Shiarella

12:30-14:00 Lunch

14:00-15:30 Visualising Data

Advanced plotting
A primer on good and bad visualisation practices
Applications to participant projects

Speakers: Ellen Charlesworth and Alexander Shiarella

15:30-16:00 Refreshment break

16:00 -17:00: Project session

Catching-up: assistance will be provided for anyone with follow-up questions or remaining issues from the earlier sessions.
Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

09:00-10:30 Working with Spatial Data (Geomapping)

An introduction to Pandas
Plotting spatial data

Speakers: Alexander Shiarella

10:30-11:00 Refreshment break

11:00-12:30 Natural Language Processing

Two talks from NLP professionals (each for 30 mins)
30 minutes of questions and practical exercises applying these concepts

Speakers: Miguel Arana-Catania and Nilo Pedrazzini

12:30-14:00 Lunch

14:00-15:30 Network Analysis

30 minute talk from a guest speaker
Followed by practical exercises using NetworkX

Speakers: Ellen Charlesworth

15:30-16:00 Refreshment break

16:00 -17:00: Project session

Catching-up: assistance will be provided for anyone with follow-up questions or remaining issues from the earlier sessions.
Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

Speakers: Ellen Charlesworth and Alexander Shiarella

09:00-10:30 Continuation of Working with Spatial Data / Project Session

Catching-up: assistance will be provided for anyone with follow-up questions or remaining issues from the earlier sessions.
Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

Speakers: Ellen Charlesworth and Alexander Shiarella

10:30-11:00 Refreshment break

11:00-12:30 Project Session

Catching-up: assistance will be provided for anyone with follow-up questions or remaining issues from the earlier sessions.
Project: Attendees will continue to work on their own mini-projects, applying the techniques from the earlier sessions to their data. Help will be provided one-on-one and through breakout groups for participants with similar questions.

Speakers: Ellen Charlesworth and Alexander Shiarella

12:30-14:00 Lunch

14:00-15:00 Participant Presentations

Participants will be asked to informally speak about their project (without slides for just 2-3 minutes) and what they have achieved over the week. The session aims to highlight next steps for attendees and point them in the direction to relevant resources.

Resources for self-guided learning (tailored to the group's projects) will be shared.

Speakers: Course participants

15:00-15:30 Refreshment break

15:30-17:00 Closing Keynote: AI, Archives, and the Synthetic Past

Abstract: What counts as the past when AI can generate voices, personas, and narratives from archival and digital traces? This presentation examines how artificial intelligence is reshaping relationships between memory, archives, and historical representation, and asks how these technologies are changing the ways the past is experienced in the present. Drawing on the Leverhulme Trust-funded research project Synthetic Pasts - including our critical-creative research on “AI afterlives” - the talk explores how computational systems simulate, mediate, distort, and commercialise forms of remembrance and cultural memory. It then invites digital humanities researchers to reflect on the conceptual, ethical, and methodological challenges that follow.

Speaker: Dr Jenny Kidd (University of Cardiff)

Dr. Jenny Kidd is a Reader in the School of Journalism, Media and Culture at Cardiff University and researches in the interdisciplinary fields of Digital Heritage and Digital Culture.