Release Notes: Workshop on Cultural Data (Version 1.0)
This is the first release of the Workshop on Cultural Data, designed to introduce participants to the principles, tools, and methods for working with cultural datasets.
Overview
The initial phase of conducting a data-driven analysis revolves around the dataset itself. Cultural or historical data may not always be readily available in machine-readable or digital formats. In humanities fields, researchers often find themselves responsible for collecting and creating the dataset. This step plays a pivotal role in shaping the direction of the research. The dataset's structure and content are influenced by the research questions, and when working with existing datasets, the content becomes a defining factor for future inquiries. Therefore, gaining a thorough understanding of the preprocessing stage for your data is crucial. This knowledge proves invaluable when exploring new tools, programming languages, or computational analyses.
Humanities data consists of a myriad of forms resulting from human expression, culture, history, and thoughts. Literary texts, historical documents, paintings, and music, this is just the tip of the iceberg of a variety of data formats reflecting the complexity of the human species itself. These data have been mainly studied with traditional scholarly methods, however, the technological developments of our time (AI among others) now offer the unprecedented opportunity to unveil connections, patterns, and new thrilling insights from the most diverse and large datasets in a very short amount of time.
To exploit this opportunity, the qualitative nature of humanities data needs to be transposed into the quantitative realm of data analysis. Here, data can be structured, organised, cleaned, checked, explored, visualised, and finally analysed. This process may seem overwhelming for researchers with little background in data analysis, but it presents an incredible opportunity to explore the depths of humanities data, uncovering narratives that transcend traditional research boundaries.
This workshop is a hands-on experience where we guide participants through the process of creating datasets containing cultural and historical data. We cover the entire journey, from the collection to running basic analyses and visualisations. This two-day workshop provides participants with an opportunity also to bring their own datasets and actively engage with them through the workshop.
Workshop Objectives:
Upon completion of this workshop, participants will gain proficiency in the following areas:
- Crafting, structuring, and constructing datasets.
- Cleaning and normalizing information.
- Critically evaluating datasets.
- Conducting insightful data analysis and visualizations.
Key Features
- Comprehensive introduction to cultural data concepts.
- Hands-on tutorials covering:
- Data collection and preparation.
- Visualization techniques for cultural data.
- Case studies highlighting cultural data applications.
- Interactive sessions with Q&A and peer collaboration.
Target Audience
- Researchers, students, and professionals interested in cultural studies, data science, or digital humanities.
- No prior experience in data science is required, but familiarity with programming is beneficial.
Included Materials
- Workshop slides and handouts.
- Example cultural datasets for practice.
- Step-by-step guides for the exercises.
- Resources for further learning.
Technical Requirements
- Laptop with the following installed:
- Python 3.11+
- Required libraries/packages (to be specified in the pre-workshop instructions).
- Access to the internet for downloading materials and accessing resources.
Acknowledgments
This workshop has been developed by Barbara Romero-Ferron, Stefano Rapisarda, and Chiara Livio from the Utrecht University Library