A blog report after attending the Two-Week Summer School on Data Literacy in R for Students in Humanities at Charles University, Prague, Czech Republic (4–15 August 2025).
This blog details my experience after attending the Summer School on Data Literacy in R for Students in Humanities, hosted by LINDAT/CLARIAH-CZ at Charles University in Prague from 4 to 15 August 2025. This Summer School was fully funded through the ATRIUM Transnational Access (TNA) scheme. The program provided an intensive introduction to R programming tailored for humanities scholars with no prior coding experience. Over ten teaching days, I gained very good practical skills in data tidying, analysis, and visualization, while immersing myself in Prague’s rich cultural landscape.
Travelling to Prague The journey to Prague was one of the most exciting journeys I have ever taken. I had deep excitement of the experience I was to have in Prague for next two weeks as I had heard much from my mentors who had initially attended a conference in Prague in July for two weeks and they had shared much about how the city was beautiful and how it was rich in culture. With a background in archaeology, I was excited to be able to see the city’s golden landscape and the gothic architecture in the city. I arrived at the Vaclav Havel Airport and was greeted by a warm welcome banner ‘Welcome to Prague’. Navigating Prague’s transport system was a real test for me on the first night in town but with the help from the information desk at the airport, it was easier for me to take a bus ride to the hotel.
Overview of the Training Program The two-week course spanned ten teaching days (Monday to Friday each week), with a daily schedule of morning (9:00–12:10) and afternoon (14:00–17:10) 90-minute sessions, separated by a long lunch break for rest and informal discussions. Sessions alternated between lectures, self-paced Data Camp modules (requiring personal laptops and headphones), and small-group projects using cloud-based RStudio. No prior programming knowledge was assumed, making it accessible yet challenging. Core topics included:
- Data Tidying: Importing datasets, handling missing values, reshaping data with tidyverse packages (e.g., dplyr, tidyr).
- Basic Analysis: Descriptive statistics, summarization, and simple inferential tests using base R and ggplot2 for visualization.
- Scientific Visualization: Creating plots, histograms, and scatterplots to represent humanities data. The program awarded 2 ECTS credits upon completion, emphasizing practical application over theory.
Week 1 (4–8 August) https://ufal.github.io/R_BEGINNERS_SHORT/
Day 1: 4th August 2025. Woke up very early in the morning and took my breakfast at the hotel. I had no train tickets so I rushed to the train station to buy the tickets which would last me for the next two weeks. Navigating from the train station to the Faculty of Mathematics and Physics, School of Computer Science in Malostranské náměstí 25 was easy as the Google Maps led me straight to the faculty. We were introduced by Petr Polansky who we had been in constant communication with before the summer school. Petr introduced Dr. Silvie Cinkova who would be our tutor for the next two weeks. After introductions, Dr. Silvie introduced us to RStudio and we installed RStudio via cloud access. We also created our accounts on Data Camp. After this, we explored the RStudio and we created our first Quarto Document. We had a joint lunch with the group as we discussed what each one of us expected in the coming days. In the Afternoon, we navigated the RStudio for programming and the variable functions. Later we dived in the Data Camp and did the exercises for the day. The week was quite intense and we covered the following:
a) Introduction to reading CSV/TSV files with readr.
b) Exploring data frame with dplyr and ggplot2. We also covered renaming columns with base R and dplyr, filtering rows, plotting the data set and later commenting on the plot.
c) Data visualization. Data visualization combines statistics and data in a meaningful way. Here we did aesthetic scales and geometries with statistical transformations and we transformed data into line plots, bar plots, histograms and box plots using ggplot2. We also did alleviate overplotting with alpha and jitter.
d) Sub-setting and Aggregations with dplyr. https://ufal.github.io/R_BEGINNERS_SHORT/09_Aggregations_with_dplyr.html#dplyr-operations-on-data-frames
e) Mutation and other dplyr functions on the Gapminder billionaires’ data set. This involved tackling common plotting issues in ggplot2 and knitr. The weekend break allowed cultural outings as well as a rest after a busy week.
Week 2 (11–15 August) After a restful and a fun filled weekend, we resumed the classes and covered these topics: a) How to join several data frames with dplyr https://ufal.github.io/R_BEGINNERS_SHORT/12_JoiningDplyr.html . This was followed by an exercise on how to Join tables with dplyr and a discussion over the exercise or a live solution coding.
b) Data frames- Here we looked at the base-R way. We also worked in groups of 4 to make sense of someone else’s code. We presented the results in a poster and each group explained what they got.
c) The Purr Package which allows us to simplify iterations either with vectors or lists without having to deal with the loops and lets us to do the same thing over and over again with different inputs
d) Wrangling the outcome of an API service and how we can create one huge table with all indicators by joining the table. We also learnt on how to simplify the structure using different parameters.
e) Tidy R and String R. This involved transforming variables into different categories.
Since Thursday was almost our final day and most people were leaving the next day, we hang out at Letna Lookout Beer Garden for a drink as we reflected on the two weeks that were very educative and informative. The last day of the summer school. 15th August This was our final day of the summer school. We went through Writing Functions (the minimum) before having a self-assessment test (a small project consisting of learned workflows). After the assessment, we left the room having created bonds that will last for long and we hoped we would meet next time. Most people including myself were leaving later during the day but we were thankful for the summer school. The condensed format, adapted from a semester-long course, maintained a non-competitive atmosphere with ample support from the organizers.
Take home from the summer school Technical Skills • R’s power for humanities: I learned to transform messy tabular data into analyzable formats, reducing manual effort. Key takeaway: Packages like tidy verse democratize data work for non-coders. • Visualization as storytelling: Creating plots helped visualize patterns in cultural data, such as word frequencies in historical texts, enhancing interpretive research. • Reproducibility: Emphasizing scripts over point-and-click tools ensures research transparency, crucial for collaborative projects. Soft Skills and Broader Insights • Overcoming tech intimidation: Starting from zero, I gained confidence in troubleshooting, proving programming is accessible with patience but also having listening tutors makes it easy for you. • Interdisciplinary collaboration: Discussions with peers from linguistics, history, and archaeology highlighted R’s role in bridging disciplines. • Time management: Balancing intensive sessions with self-study taught efficient learning strategies on Data Camp made us have time management strategies which will be much useful in all our undertakings. Overall, the program equipped me to apply R in my research and my studies. • Adaptability: Cloud tools mitigated tech issues, reinforcing that programming is accessible without advanced hardware. • Ethical Considerations: Discussions on data bias in humanities datasets prompted reflection on how algorithms can perpetuate historical inaccuracies.
Cultural Experiences in the Czech Republic Prague’s vibrant summer atmosphere enriched the experience. Afternoons and weekends allowed exploration: • Historical Sites: Visited Prague Castle (world’s largest ancient castle) and Charles Bridge, marveling at Gothic architecture. A guided tour throughout these sites made it easy for me to understand and appreciate these well-preserved sites. • Local Cuisine and Socializing: I Sampled Czech cuisines and world-famous pilsner beer at outdoor terraces. Dinners at traditional pivnice (beer halls) facilitated cultural exchanges as I met people from different areas. • Daily Life: Wandering in the city streets and riding efficient trams offered insights into Czech resilience and hospitality. The multicultural participant group shared perspectives, enhancing global awareness.
Conclusion This summer school was more than just training; it was a cultural and intellectual adventure. We’ve not only gained skills in data wrangling with dplyr and tidyr, statistical modelling, and reproducible reporting with R-Markdown but also forged lifelong connections.
Vote of Thanks Special mention to Petr Polansky for your seamless guidance and responsiveness throughout the whole time. Also, special gratitude to our instructor Dr. Silvie Cinkova of the Institute of Formal and Applied Linguistics at Charles University, the way you structured the sessions, blending interactive Data Camp exercises with hands-on group projects, ensured that every concept was accessible and applicable to our research. Your patience during those “aha” moments, when a ggplot2 plot finally revealed hidden patterns in historical texts, will stay with us forever. Thank you for demystifying R and empowering us to integrate digital tools into our humanistic inquiries. Also grateful to the ATRIUM for the generous grant which covered for accommodation, subsistence and the travel expenses. Also, to the summer school participants, you made my time memorable and you are such a wonderful team to learn and be with.