International Digital Oral History Lab
A Digital Oral History Lab Project 2024 — present

MeDoraH.

Mixed-methods Digital Oral History

Advancing digital humanities research methodology through semantic web technologies and computational oral history analysis — extending the Hidden Histories corpus with a German-language stream.

Methodology Hermeneutic analysis
NLP Cross-lingual text mining (EN/DE)
Ontology OWL/RDF knowledge graph
Data principles FAIR
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About MeDoraH

Building upon Hidden Histories' foundational work, MeDoraH represents an innovative advancement in digital humanities research methodology. This collaborative venture between University College London and TU Darmstadt introduces cutting-edge semantic web technologies and digital methods to oral history research.

MeDoraH enriches the existing Hidden Histories interview corpus by incorporating ten new German-language interviews, broadening our understanding beyond the Anglophone world.

Hidden Histories MeDoraH Project lineage
Methodological innovation

The project pioneers a novel methodological framework combining traditional oral history approaches with advanced computational techniques, enabled by a comprehensive knowledge graph and specialized ontologies. Through innovative natural language processing across English and German sources, MeDoraH creates structured representations of oral history interviews adhering to FAIR data principles.

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Technical Impact

This technical infrastructure supports sophisticated analyses while preserving the nuanced nature of oral history research. Our interactive portal enables researchers, digital humanists, and oral historians to explore this enhanced interview corpus, facilitating novel investigations into the formation and evolution of digital humanities as a field.

Project outputs include semantically enriched interview transcriptions, a pioneering oral history ontology, and new methodological frameworks for digital oral history research.

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Project Resources

Three entry points into MeDoraH's methodological contributions — the metadata framework, the FAIR-compliant data, and the published scholarship behind them.

R / 01

Metadata Structure

Discover the comprehensive metadata framework underpinning MeDoraH's approach to oral history data.

 
Type Metadata framework
Format OWL / RDF
View details
R / 02

FAIR Data Principles

Access structured representations of oral history interviews strictly following FAIR data principles.

 
Type Data resources
Access Open access
Access data
R / 03

Publications & Outputs

Browse publications, research outputs, and scholarly contributions from the project team.

 
Type Research output
Source Lab repository
Read articles
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Technical Toolkits

Our NLP pipeline and ontology definitions are openly available on GitHub for reproduction, scrutiny and extension.

Repo / 01

MeDoraH NLP

GitHub

A suite of text mining and knowledge graph construction tools for processing historical narratives.

NLP Toolkit Hermeneutic Analysis Clustering
View on GitHub
Repo / 02

MeDoraH Ontology

GitHub

Ontology and schema definitions providing the formal knowledge representation layer of the platform.

Ontology OWL / RDF FAIR Data
View on GitHub