AI-Aided Data-Driven Study of Historical Parchments' Making, Degradation, and Origin

Project Overview

Parchments, made from treated animal skins and used as writing materials from the 4th to 15th centuries, hold crucial historical documents. Their primary component, collagen, degrades over time through processes like oxidation and hydrolysis. Identifying parchment species and manufacturing traits is key to understanding economic and historical contexts, supported by emerging disciplines like biocodicology. This project leverages non-invasive optical and hyperspectral imaging, alongside AI and machine learning, to non-destructively analyze parchments.

What You Will Do

The student will extend non-invasive imaging methods (reflectance, fluorescence hyperspectral imaging, optical coherence tomography) to gather micro- to macroscopic data sets on parchments. They will develop AI algorithms to interpret multimodal data to determine parchment species, age, manufacturing methods, degradation states, and provenance. Supporting proteomics analyses will verify AI findings. The project involves large-scale analysis of parchment collections from UK and Belgian archives, including atmospheric exposure variations within manuscripts.

Expected Outcomes

The project aims to deliver a comprehensive, data-driven workflow integrating multimodal imaging and AI analysis, enabling accurate identification and dating of parchments and evaluating their conservation status. It will yield improved understanding of historical parchment material science and support preservation strategies for cultural heritage documents.

Why This Matters

Understanding and preserving historical parchments safeguards vital written records of European civilization. The adoption of AI and non-invasive techniques revolutionizes heritage science by allowing extensive, sensitive analysis crucial for conservation and scholarly study without damaging precious documents.