Conference Agenda

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Session Overview
Session
Thu 2a: Methods (2): Variants
Time:
Thursday, 29/Sep/2016:
11:00am - 12:30pm

Session Chair: Piotr Banski, IDS Mannheim
Location: Johannessaal (Johannes hall)
Dr. lgnaz Seipel-Platz 2, 1010 Vienna, 1. floor

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Presentations

Writing under the Magnifying Glass. Encoding the Text in Progress

F. Armaselu

Centre virtuel de la connaissance sur l'Europe (CVCE), Luxembourg

Iser (1974) draws attention to the dual nature of text, determined by its actual structure and the reader's involvement supplying what is not there. This involvement implies an "active interweaving of anticipation and retrospection" and depends on the boundaries imposed by the written versus unwritten text and on the "virtual dimension of the text", nor the text itself or the reader's imagination, but the "coming together of text and imagination" (pp. 282, 279). In his reflections on photography, Barthes (1981) defines a similar dynamics, that of the “unspeakable which wants to be spoken”, manifested through the “punctum”, often a detail which triggers the spectator’s subjectivity, resulting in something added to the photograph, an addition of “what is nonetheless already there” (pp. 19, 55).

The present study proposes a view on the coming together of text and imagination, anticipation and retrospection, written and unwritten, unspeakable wanting to be spoken, from a different perspective: that of the text in progress, in its gradual development during the process of writing. The proposal is centred on a textual model (z-text) and interface (z-editor) (Armaselu, 2010, 2014) allowing to keep trace of the evolving text and to explore it “under the magnifying glass" by zoom-in and zoom-out (z- reading). Z-text writing (z-writing) consists of the expansion of already written fragments (z-lexias) by gradually adding new details to them. The model is based on TEI encoding, to each level (phase of development) corresponding an XML-TEI file. The z-lexias are marked-up by <anchor> elements and identifiers recording the ancestors-descendants relationships engendered in the process. The paper will discuss the textual model/interface and further ways of analysis/visualisation/transformation potentially supported by the encoding, inspired by concepts and studies such as genetic graphs (Burnard et al., 2010) or informational entropy (Shannon, 1948) applied to linguistic analysis (Marcus, 1970).


Tomayto, tomahto? Encoding variant taxonomies in TEI

H. Bermudez Sabel

Universidade de Santiago de Compostela, Spain

The inherent flexibility of the digital format has favoured the rise of editions that enable access to every witness of a particular textual work. These types of editions might have different goals and seek to answer different research questions, but they usually coincide in drawing attention to the importance of textual variants. To maximize the computational analysis that may be practised with the variants in different witnesses, a complex taxonomy that reflects the diversity of cases is required.

Many scholars have taken into consideration the recommended TEI method to encode the types of variants –that is, through the attributes @cause or @type inside the <rdg> element[1]– and most agree in evaluating it as insufficient[2] .These attributes are not able to enclose the hierarchy intrinsic to complicated taxonomies or the overlap of classes in an efficient way. However, the TEI Guidelines do offer a valid module for encoding this complex issue: feature structures[3].

This proposal does not advocate for a controlled vocabulary to categorize types of variants. What it offers instead is a pliable encoding method that allows the editor to include multiple layers of information in each apparatus tagset. As a way to examine the advantages of this method, I will present a practical case in which two “classical” taxonomies (textual: addition, deletion, transposition, and mutation; and substantive against non-substantive types) are combine with a goal-specific multi-layered categorization in a highly efficient way.

[1] TEI Consortium, eds. “12.1.1 The Apparatus Entry.” TEI P5: Guidelines for Electronic Text Encoding and Interchange. 3.0.0. Last updated on 2016-03-29.. http://www.tei-c.org/release/doc/tei-p5-doc/en/html/TC.html#TCAPEN (2016-05-12).

[2] View discussions in the TEI mailing list searching for key words such as “types of edits” and/or “encoding variants.”

[3] TEI Consortium, eds. “18 Feature Structures.” TEI P5: Guidelines for Electronic Text Encoding and Interchange. 3.0.0. Last updated on 2016-03-29. http://www.tei-c.org/release/doc/tei-p5-doc/en/html/FS.html (2016-05-12).


Documenting Transmission: The Analysis of the Folk Process using Versioning Machine 5.0

R. Bleier1, R. Breen2

1University of Graz; 2Maynooth University

The Versioning Machine (VM) is a framework and an interface for displaying multiple versions of a text encoded according to the Text Encoding Initiative (TEI) Guidelines. The most recent release of VM contains a new text-audio linking feature which has originally been developed by members of the Modernist Versions Project and is now a standard component of VM 5.0. The new text-audio feature facilitates parallel reading of a version of a text and at the same time listening to an audio version. Our project attempts to utilise and extend this new feature of VM 5.0 in order to allow the comparison of different versions of a folk song and analyse the ‘folk process’.

The ‘folk process’ describes the transmission and transformation of literary and artistic material from person to person in both an oral and literary context. As the stories, art, and musical traditions of a community are passed down from generation to generation, they are subject to organic changes in form, context, narrative and performance. As song forms or tropes travel, they may adopt new musical characteristics, while maintaining a core lyrical or thematic story. In a Digital Humanities context, this raises the question of whether or not a tool like VM 5.0 can be used to document and observe these changes in a way that extends our consideration of these processes.

Our paper will first introduce the new audio feature of VM 5.0. During his MA thesis, Richard Breen encoded several versions of the folk song ‘The Unfortunate Rake’. Using the VM, he has linked the lyrics to audio versions of the song, and subsequently was able to observe lyrical comparisons and contrasts. Using this example, the paper will examine the potential of using VM 5.0 to trace the folk process in action.



 
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