This hands-on workshop introduces the RAMEN Suite, an interoperable toolset for graph-based text and knowledge modelling in digital scholarly editing. Addressing well-known limitations of hierarchical XML structures in complex editorial scenarios, the workshop presents a reusable, domain-agnostic modelling framework that separates conceptual design from data capture.

At its core is the RAMEN meta-model, which defines a small set of generic concepts — such as collections, content, entities, and annotations — that can be refined into project-specific models using the modelling tool NORI. These models structure and constrain subsequent work in the ATAG Editor and the Entity Manager. ATAG enables fine-grained, character-level text and annotation modelling within a Neo4j graph database, while the Entity Manager supports the creation and linking of structured knowledge objects such as persons and places.

Participants will develop their own project-specific model, create annotated texts, and build interconnected knowledge structures. The workshop provides practical insight into how graph-based modelling can be integrated into editorial workflows while maintaining structural consistency and interoperability across projects.