Transforming scholarship in the archives through handwritten text recognition:Transkribus as a case study

Purpose: An overview of the current use of handwritten text recognition (HTR) on archival manuscript material, as provided by the EU H2020 funded Transkribus platform. It explains HTR, demonstrates Transkribus, gives examples of use cases, highlights the affect HTR may have on scholarship, and evidences this turning point of the advanced use of digitised heritage content. The paper aims to discuss these issues. - Design/methodology/approach: This paper adopts a case study approach, using the development and delivery of the one openly available HTR platform for manuscript material. - Findings: Transkribus has demonstrated that HTR is now a useable technology that can be employed in conjunction with mass digitisation to generate accurate transcripts of archival material. Use cases are demonstrated, and a cooperative model is suggested as a way to ensure sustainability and scaling of the platform. However, funding and resourcing issues are identified. - Research limitations/implications: The paper presents results from projects: further user studies could be undertaken involving interviews, surveys, etc. - Practical implications: Only HTR provided via Transkribus is covered: however, this is the only publicly available platform for HTR on individual collections of historical documents at time of writing and it represents the current state-of-the-art in this field. - Social implications: The increased access to information contained within historical texts has the potential to be transformational for both institutions and individuals. - Originality/value: This is the first published overview of how HTR is used by a wide archival studies community, reporting and showcasing current application of handwriting technology in the cultural heritage sector

read_dataset_german_konzilsprotokolle

This dataset arises from the READ project (Horizon 2020). Images were provided and enriched under the lead of Dr. Dirk Alvermann (Universitätsarchiv Greifswald - Germany). All in all this dataset contains 8770 trainscribed textlines of handwritten historical documents from the late 18th century. Besides the images and page-files (containing geometric textline information and transcripts), lists dividing the dataset in train and test data are provided (each list element contains the corresponding image, textregion and textline identifiers and therefore an explicit mapping of a list element to a textline is possible). Furthermore sublists of the train list are given