When working with variant texts, scholars often struggle to express textual complexities in a formal, machine-processable manner: it is the familiar balance between standardization and flexibility (Eide 2015). In textual scholarship, this is further complicated by linguistic, cultural, and disciplinary differences (Spadini et al. 2016; Bleeker et al. 2025a). As of yet, there is no shared vocabulary to describe textual variation, tools and datasets lack interoperability (Martignano 2023a), and visualizations are often project-specific and not reusable (Franzini et al. 2019).

The international working group “VIDIT” (Visualising and Investigating Differences in Texts) aims to address these challenges by (1) developing a taxonomy of core concepts related to textual variation, and (2) establishing best practices for collation and visualization tools (Bleeker and Nava, 2025b). This poster provides an update of VIDIT’s activities, focusing on the methodological approach and the first taxonomy results.

The taxonomy development has three stages. First, core concepts of text variation are collaboratively identified. For each concept, examples are gathered from texts from different periods and genres, along with definitions from scholarly publications, tool documentation, and encoding guidelines. Rather than imposing a single definition, we identify the range of meanings and contexts of use. Second, these concepts are structured following knowledge organization principles: identifying hierarchies, clarifying overlaps and distinctions, and documenting conditions under which different definitions apply. Third, the taxonomy is aligned with existing ontologies in the field (Giovannetti 2019, Martignano 2023b, Spadini 2019[2023]).

Our methodology has raised several questions, among others relating to the balance between comprehensiveness and usability. When and how to prioritise consensus over diversity? How to ensure the taxonomy’s relevance as digital methods evolve, and how to couple the taxonomy with the TEI Guidelines? We welcome feedback on the above questions as well as on our methodological approach and the first taxonomy results.