Separating the chronicles using Python

Before we enter the world of digital handwriting analysis in the next few blog posts, here is a brief insight into the pre-processing of the data.

As mentioned in the last blog post, there are four volumes of Philipp Gumpenhuber’s chronicles in the Theatre Collection of the Houghton Library at Harvard University ( So far, these are linked by a single IIIF manifest. Each volume is a separate entity and holds a mosaic of events and performances that deserves to be presented and analyzed individually.

But first, what is IIIF? IIIF (International Image Interoperability Framework) provides a standardized method for presenting materials from libraries and archives worldwide, enabling, for example, the examination of high-resolution digital copies of documents. More information about IIIF can be found on the official website at

Thanks to the Python programming language, we are able to process each work individually and thus give it back its digital independence. This division is important for detailed analyses using Transkribus ( Through this careful separation, we have created four autonomous digital manifests that allow us to faithfully capture and validate individual works.

Therefore, Christina Dittmann created Python scripts that split a large IIIF manifest into individual, autonomous manifests. Through this process, each volume regains its digital identity and becomes ready for detailed transcription using Transkribus.

The process can be divided into four key steps: (1) the integration of the overall manifest into Python, (2) the division of the manifest into individual volumes based on the existing structure, (3) the creation and formatting of standalone IIIF manifests for each individual volume, and (4) a validation to ensure interoperability and correct function.

The entire process and associated code are publicly available in the GitHub repository at, providing a resource for anyone interested in working at the intersection of history and digital technology.

OpenEdition suggests that you cite this post as follows:
Christina Dittmann (June 19, 2024). Separating the chronicles using Python. GuDiE. Retrieved July 16, 2024 from

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