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This essay addresses two open challenge in the domain of digital scholarly editing: (1) formally defining the meaning of markup, and (2) allowing the reuse and exchange of textual data through a distributed editorial workflow that allows the editing of texts from multiple, diverging yet co-existing perspectives. We argue that successfully addressing these issues would promote the distribution and exchange of scholarly knowledge, on a technical as well as a theoretical level. The essay introduces ongoing work on a new data model for text called ‘TAG’ (Text-as-Graph) and its reference implementation ‘Alexandria’. The essay outlines how TAG, based on a hypergraph for text, can improve the modeling of complex literary texts, and how Alexandria supports the exchange of markup files in a way that sustains scholarly discourse. We discuss three components of TAG: first, the markup technology stack allows for the formal definition of the meaning of markup (‘markup semantics’); secondly, users can add multiple layers of markup that each represent an alternative perspective on text; and finally the editorial workflow is set up in a git-like distributed version management system. As a result, the TAG model provides for the synthesis of dispersed scholarly practices and the advancement of academic discourse.

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This paper explores the potential of combining the Text-As-Graph (TAG) and the XML data models. It proposes a digital editing workflow in which users can model, edit, and store text in TAG, and subsequently export the textual data to XML for further analysis or publication with XML-based tools. The conversion from TAGML to XML presents several interesting challenges on a technical level as well as a philological level. Overall, we argue that there may be many pragmatic reasons to encode cultural heritage texts in XML, but we have to be mindful of the XML framework becoming synonymous with the framework in which we conceptualize text. The paper therefore dives deep into the translation from conceptual model to logical model(s) and argues in favor of understanding the affordances and limitations of the technologies we use.

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