What is it about?
This article features all the developments in Assyriology in terms of Digital Humanities concerning visual tasks like recognizing cuneiform glyphs on clay tablets being among the oldest documents in the world.
Featured Image
Photo by Lei Mu on Unsplash
Why is it important?
Digital approaches to the highly specialized field of Assyriology come from a number of different subdisciplines of computer science as well as humanities institutions. This article gives a concise overview of the important developments starting in the late 1960s leading up to most recent approaches. The overview about challenges, datasets, mathematical models, digital tools etc. is important to understand what has been done and achieved to push forward the digital aspects and the attached chances to gain insights in early human history.
Perspectives
The article has a certain focus on the cuneiform signs imprinted into clay being among the oldest documents existing in astonishing numbers. As sketched in the outline there is also a computer linguistic side to this work highlighting the computer vision aspects, which should be treated with an additional article. More importantly we hope to spark even more interest into this exciting topic having many interesting challenges in the interdisciplinary combination of ancient history and computer science.
Hubert Mara
Martin-Luther-Universitat Halle-Wittenberg
Read the Original
This page is a summary of: Digital Assyriology—Advances in Visual Cuneiform Analysis, Journal on Computing and Cultural Heritage, June 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3491239.
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Resources
GigaMesh Software Tutorials
Several videos for the use of the GigaMesh Research Software within archaeology as well as cuneiform studies i.e. assyriology.
HeiCuBeDa Hilprecht – Heidelberg Cuneiform Benchmark Dataset for the Hilprecht Collection
Collection of 1977 clay tablets with cuneiform writing acquired with a 3D-scanner. Includes normalized images, curvature data, metadata and the 3D-models as a benchmark dataset for machine learning.
HeiCu3Da Hilprecht – Heidelberg Cuneiform 3D Database – Hilprecht Collection
Browse- and searchable collection of 3D-models and renderings of cuneiform tablets based on the related HeiCuBeDa dataset.
Contributors
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