Title Modeling a Body of Literature in TEI: Bibliotheca Hagiographica Syriaca Electronica

Encoded by   Vanessa Hannesschläger

Encoded by   Daniel Schopper


The Creative Commons Attribution 4.0 International (CC BY 4.0) License applies to this text.


The project publishes born-digital reference works in TEI. "Bibliotheca Hagiographica Syriaca Electronica" 1 is a set of metadata records describing a particular genre of Middle Eastern literature: saints’ lives written in the Syriac language. This poster describes

  • the process of transforming a legacy (tabular) dataset into TEI and
  • the decisions made in creating a schema for encoding and modeling metadata about a body of literature. is now revising this TEI schema for an expanded project which will describe all of Syriac literature, a corpus which has had little previous scholarly classification or description. considered a number of methodological questions, which arose from using TEI to model "works" (in the sense defined by FRBR2). While TEI is frequently used to represent the content of specific manuscripts (or other textbearing objects) and create editions of works, we found that the use of TEI for born-digital metadata records was less common. We found a number of advantages in using TEI over other metadata or bibliographic formats (e.g. MARC, Dublin Core). In addition, we made encoding decisions about how to apply the TEI guidelines to the following questions:

  • How can TEI model relationships among works, especially different recensions of the same work or whole-to-part relationships?
  • How can TEI express the relationships of works to their manuscript witnesses, editions, and translations?
  • How can TEI express the relationship of works to persons with alleged authorial or editorial responsibility for it, whether genuine, pseudonymous, anonymous, or attributed?

This poster presents our preliminary schema for modeling a body of literature in TEI, for which the authors actively seek feedback, suggestions, and criticism. We are particularly interested in learning from similar projects which have used TEI to map or model metadata about large and heterogeneous literary canons.