No abstract

Stand-off markup is widely considered as a possible solution for overcoming the limitation of inline XML markup, primarily dealing with multiple overlapping hierarchies. Considering previous contributions on the subject and implementations of stand-off markup, we propose a new TEI-based model for encoding, that still uses the regular TEI elements, but in a standoff manner. Our light notation moves the bulk of markup into a separate element, grouping layers of related textual features encoded via existing TEI elements (eg. or ) into individual elements; furthermore, our proposed notation provides a schema for referencing the transcription using the xml:id attribute. This approach is illustrated through a variety of examples. Our proof-of-concept transformation package works directly on the stand-off markup, without the necessity of reducing it back to inline TEI for parsing, querying and visualizing.

This article presents a commented history of automatic collation, from the 1940s until the end of the twentieth century. We look at how the collation was progressively mechanized and automatized with algorithms, and how the issues raised throughout this period carry on into today’s scholarship. In particular, we examine the inner workings of early collation algorithms and their different steps in relation to the formalization of the Gothenburg Model. The scholars working with automatic collation also offer fascinating insights to study the collaborations between Humanists and Computer Scientists, and the reception of computers by philologists.

Textual scholars use the collation for creating critical and genetic editions, or for studying textual transmission. Collation tools allow to compare the sources and detect the presence of textual variation; but they do not take into account the kind of variation involved. In this paper, we aim at enhancing the model used by software for semi-automatic collation. We provide a way to record descriptions of the variation and structure them into annotations. Annotations are stored in a relational database; a number of possible queries are suggested.