Linked Data from TEI (LIFT): A Teaching Tool for TEI to Linked Data Transformation

https://openmethods.dariah.eu/2024/03/04/lift/ OpenMethods introduction to: Linked Data from TEI (LIFT): A Teaching Tool for TEI to Linked Data Transformation 2024-03-04 16:34:17 TEI editions are among the most used tool by scholarly editors to produce digital editions in various literary fields. LIFT is a Python-based tool that allows to programmatically extract information from digital texts annotated in TEI by modelling persons, places, events and relations annotated in the form of a Knowledge Graph which reuses ontologies and controlled vocabularies from the Digital Humanities domain. Françoise Gouzi https://projects.dharc.unibo.it/lift/# Blog post Analysis Content Analysis Creation Data Editing English Enrichment Information Retrieval Interpretation Linked open data Manuscript Modeling Programming Research Activities Research Techniques Text Tools via bookmarklet

“Introduction by OpenMethods guest editors Cristian Santini and Sebastian Still (DHd2024, Passau)”

TEI editions are among the most used tool by scholarly editors to produce digital editions in various literary fields. LIFT is a Python-based tool that allows to programmatically extract information from digital texts annotated in TEI by modelling persons, places, events and relations annotated in the form of a Knowledge Graph which reuses ontologies and controlled vocabularies from the Digital Humanities domain.

Retrieving such a collection of interconnected entities, would be of great value with respect to re-use the information hidden in any well-structured XML-Edition and especially when connecting a digital edition with norm data or other digital projects from similar domains. Not only from a humanistic point of view, but particularly from a technical perspective the possibilities to build on top of such data are increased immensely.

While the standard maintained by TEI is long-established in the DH domain, there is a gap between the work which was carried in the scholarly editing domain and that related to Linked Open Data and Knowledge Graphs. The main challenge in that respect is the transition from a document-centric approach (TEI) to a data-centric approach (RDF).

The LIFT package, available on Github and published with thorough documentation, provides a series of scripts based on libraries such as lxml and RDFlib, that parse an XML document and convert it to a RDF Graph. In order to understand the functionality of this software, the authors provide a Jupyter Notebook organized step-by-step. The authors emphasize the accessibility of this tool also due to the fact that it was developed as a teaching tool for the degree in Digital Humanities and Digital Knowledge at the University of Bologna: in this program, students have to master both the principles of scholarly editing and those of LOD and Semantic Web.

In conclusion, this work realized by the DHarc at the University of Bologna is an initial step that paves the way for the integration of practices in scholarly editing and LOD, in order to envision new technologies and methodologies in the DH domain that provide high interoperability, machine-readability and explorability by leveraging the LOD cloud.

With LIFT, we […] aim to encourage further research into the development of open-source, user-friendly tools aiding the mutual integration of digital scholarly editions and the cultural heritage linked open data cloud. Such tools have the potential to make digital humanities, and especially knowledge representation, a more inclusive field of study and research.

Linked to Research Article: https://www.digitalhumanities.org/dhq/vol/16/2/000605/000605.html

Source: LIFT