Small Data and Process in Data Visualization: The Radical Translations Case Study

TL;DR

This paper examines how data visualization is used in digital humanities projects, focusing on small data, collaborative workflows, and theoretical perspectives, through a case study of the Radical Translations project.

Contribution

It provides a detailed case study of visualization practices in digital humanities, highlighting theoretical considerations and workflows for small data in interdisciplinary collaboration.

Findings

Visualization supports data curation and design in digital humanities.

Trade-offs in visualization approaches have epistemological implications.

Workflow integration enhances collaborative data exploration.

Abstract

This paper uses the collaborative project Radical Translations as case study to examine some of the theoretical perspectives informing the adoption and critique of data visualization in the digital humanities with applied examples in context. It showcases how data visualization is used within a King's Digital Lab project lifecycle to facilitate collaborative data exploration within the project interdisciplinary team - to support data curation and cleaning and/or to guide the design process - as well as data analysis by users external to the team. Theoretical issues around bridging the gap between approaches adopted for small and/or large-scale datasets are addressed from functional perspectives with reference to evolving data modelling and software development lifecycle approaches and workflows. While anchored to the specific context of the project under examination, some of the identified trade-offs have epistemological value beyond the specific case study iterations and its design solutions.