Introduction

LIFT (Linked data from TEI) is a Digital Humanities tool based on Python 2.7 for generating linked open data (LOD) out of TEI-encoded texts. This documentation is intended to provide you with an understanding of how LIFT works from the standpoint of both the technologies and the methodology employed. After reading this documentation, you should be able to use LIFT as is or modify its scripts to meet your specific project requirements.

LIFT offers five different TEI-to-LOD scripts written in Python 2.7. Each script addresses the transformation of a set of specific TEI entities (persons, persons and events, persons and relations, places, critical apparatus) to LOD. The scripts can be used independently from one another. An additional script comprehensive of all entities - except critical apparatuses (i.e. persons, events, relations, and places) - is also available. Another script for bibliographic entities is still under development.

This documentation, divided into four sections, serves a pedagogical purpose by demonstrating and discussing in detail a workflow for TEI-to-LOD transformation that does not require the use of XSLT and instead relies on Python (the lxml library is used for the processing of XML, while the RDFLib library is used for the creation of the RDF triples):

  1. Prepare your TEI document, which explains the encoding requirements for the input TEI document;

  2. The RDF graph, illustrating the structure and semantics of the generated knowledge graph by comparing the TEI input with the corresponding RDF output (this section also discusses why and how users might choose different ontologies for their projects or modify the scripts to work with different input data);

  3. How the scripts work, where users can access an interactive Jupyter notebook containing LIFT’s scripts with instructions and line-by-line explanations that are meant to help users develop the skills required to write their own transformation scripts;

  4. Further readings and resources, which lists relevant publications and provides examples of TEI digital scholarly editions which have been enriched by means of linked open data.

You can directly run the scripts from the web application (https://projects.dharc.unibo.it/lift/quickstart.html) or download them for local use (see How the scripts work for more detailed instructions ).