This workshop focuses on the fundamental steps of collecting, constructing, and exploring datasets. Are you interested in incorporating data-driven approaches into your research or integrating computational methodologies into your coursework? Then join this workshop provided by Bárbara Romero Ferron and Stefano Rapisarda, information and collection specialists at Utrecht University Library.

The preprocessing stage of your dataset

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.

Working with cultural data

Cultural 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 Literary texts, historical documents, paintings, and music, this is just the tip of the iceberg of a variety of data formats reflecting the complexity of the human species itself.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 cultural data needs to be transposed into the quantitative realm of data analysis. Here, data can be structured, organized, cleaned, checked, explored, visualized, and finally analyzed. This process may seem overwhelming for researchers with little background in data analysis, but it presents an incredible opportunity to explore the depths of cultural 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 visualizations. This 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:

1. Crafting, structuring, and constructing datasets
2. Cleaning and normalizing information
3. Critically evaluating datasets
4. Conducting insightful data analysis and visualizations
5. Publishing dataset

Follow up

For those interested, a follow-up hour to this workshop is scheduled for Thursday, March 14, from 13:00 to 14:00 hrs.

Level

No prior experience with data is required. This introductory course focuses on the fundamental steps of working with data.

Preparation

Participants should bring their laptops and, optionally, their own “messy” data, research questions, or datasets. This allows participants to apply the workshop’s learning objectives to their specific work.

Target audience

Due to our funding, priority will be given to humanities teachers, researchers, and students for this workshop. If you are affiliated with a different faculty or institution but interested in participating, please register to be placed on a waiting list. Notification of available spaces will be sent two weeks before the workshop.

To secure your spot, we encourage you to register as soon as possible, as registrations will be processed on a first-come, first-served basis. If you find yourself unable to attend, we kindly request that you cancel your registration by sending an email to CDH@uu.nl. This will allow us to offer the spot to another interested participant. Thank you for your cooperation.