SubsidieMeestersTool for the Analysis of Information Transfer in Manuscript Cultures
The TInTraMac project develops a free, flexible research tool to encourage scholars to adopt digital methods for analyzing manuscript texts, enhancing accessibility and collaboration in textual studies.
Projectdetails
Introduction
This PoC project aims to alleviate the hesitancy of scholars working on texts preserved in manuscripts or other handwritten media, to adopt advanced digital methodologies in their research.
Project Objectives
The project focuses on developing a free, shareable, flexible, low-threshold research tool, which may be used as a starting point for researchers interested in studying the textual transmission of information in manuscript cultures.
Tool Features
The tool will take the form of:
- A pre-designed but flexible data model
- A data-input framework
- A database solution
Through this framework, data can be queried and exported for further analysis using relevant tools for statistical and network analysis.
User Support
It will be accompanied by:
- A detailed user manual guiding users through the workflow from data input to analysis
- Tutorial videos explaining in non-specialist terms to scholars of historical textual corpora the procedures leading from database design and population to the application of relevant analytical tools
Additionally, it will contain a description of best practices and recommendations for the organization of collaborative team-based project implementation.
Adaptability
The tool will be designed in such a way as to be easily adapted to a wide range of research projects on any type of textual corpus, regardless of its language or genre.
Accessibility and Impact
The TInTraMac research tool will be freely downloadable and non-profit. It aims to save significant time and resources for researchers and research projects focusing on large-scale textual corpora based on handwritten sources from manuscript cultures.
By promoting groundbreaking research, it clearly demonstrates the benefits of employing such advanced digital methods in their fields. At the same time, it aims to lower the threshold of adoption by making the TInTraMac research tool freely available, and it seeks to flatten the learning curve for non-specialist users by making it highly accessible.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 150.000 |
| Totale projectbegroting | € 150.000 |
Tijdlijn
| Startdatum | 1-8-2023 |
| Einddatum | 31-1-2025 |
| Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- UNIVERSITETET I OSLOpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Building an AI-tool to facilitate the integration, accessibility, and usability of heterogeneous cultural heritage data on medieval manuscripts.ManuscriptAI aims to integrate and enhance access to medieval manuscript data using machine learning, promoting digital preservation and inclusivity in Europe's cultural heritage narrative. | ERC Proof of... | € 150.000 | 2024 | Details |
The Lost Manuscripts of Medieval Europe: Modelling the Transmission of TextsLostMa investigates the evolution of human cultures through the transmission of written artefacts, using AI and complexity science to analyze and simulate textual survival and loss. | ERC Starting... | € 1.499.235 | 2024 | Details |
Migrations of Textual and Scribal Traditions via Large-Scale Computational Analysis of Medieval Manuscripts in Hebrew ScriptMIDRASH aims to develop an interdisciplinary methodology using advanced technologies to study and reconstruct medieval Hebrew manuscripts, enhancing understanding of Jewish literary culture and its historical significance. | ERC Synergy ... | € 10.296.259 | 2023 | Details |
An Application for leveraging large-scale historical textbasesHistText is a user-friendly application designed for large-scale data mining of historical texts, enabling scholars to extract insights from vast multilingual corpora using advanced machine learning techniques. | ERC Proof of... | € 150.000 | 2024 | Details |
A prototype system for obtaining and managing training data for multilingual learningThe project aims to empower less-resourced language communities to create parallel corpora for machine translation, enhancing language preservation and cultural heritage through an open-source prototype. | ERC Proof of... | € 150.000 | 2023 | Details |
Building an AI-tool to facilitate the integration, accessibility, and usability of heterogeneous cultural heritage data on medieval manuscripts.
ManuscriptAI aims to integrate and enhance access to medieval manuscript data using machine learning, promoting digital preservation and inclusivity in Europe's cultural heritage narrative.
The Lost Manuscripts of Medieval Europe: Modelling the Transmission of Texts
LostMa investigates the evolution of human cultures through the transmission of written artefacts, using AI and complexity science to analyze and simulate textual survival and loss.
Migrations of Textual and Scribal Traditions via Large-Scale Computational Analysis of Medieval Manuscripts in Hebrew Script
MIDRASH aims to develop an interdisciplinary methodology using advanced technologies to study and reconstruct medieval Hebrew manuscripts, enhancing understanding of Jewish literary culture and its historical significance.
An Application for leveraging large-scale historical textbases
HistText is a user-friendly application designed for large-scale data mining of historical texts, enabling scholars to extract insights from vast multilingual corpora using advanced machine learning techniques.
A prototype system for obtaining and managing training data for multilingual learning
The project aims to empower less-resourced language communities to create parallel corpora for machine translation, enhancing language preservation and cultural heritage through an open-source prototype.
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