Data underlying the publication: "Historical Watermark Matching: User-Guided System for Feature-based Recognition"

Watermarks in historical paper provide important evidence for tracing the provenance and production of written artifacts. However, existing digital archives rely primarily on semantic metadata, limiting accessibility and hindering systematic comparison. The paper "Historical Watermark Matching: User-Guided System for Feature-based Recognition" presents a user-guided recognition system for the syntax-based matching of historical watermarks. The system integrates automated image harmonization with interactive user input, allowing experts to refine denoising, binarization, and reconstruction processes for diverse watermark sources. Similarity is computed through features extracted from pre-trained convolutional networks and Zernike moments, enabling efficient retrieval of visually similar watermarks. Quantitative evaluations and qualitative studies with watermark experts demonstrate the system’s effectiveness, usability, and the immense potential that such a system has for improving the accessibility of watermark data. The system implementation and code are available at https://github.com/msmathcomp/historical_watermark_matching. This data set allows for the reproduction of the results from the paper.


Organization of the data

'db.pkl' The database used in both the quantitative and qualitative experiments of the paper. It encodes the features of the watermark images of the "Wasserzeichen-Informationssystem" (Watermark Information System, WZIS, https://www.wasserzeichen-online.de/. These features are used for automatic and user-guided comparison of the watermarks. In particular, the database allows for running the evaluation scripts within the repository https://github.com/msmathcomp/historical_watermark_matching.
'UEQ_Data_Analysis_Tool_Version12.xlsx' The filled-in evaluation tool for the User Experience Questionnaire (UEQ) [1]. We have entered the survey results within the 'Data' sheet of the file. All subsequent sheets are then computing the results automatically [2]. Section 4.3 of the paper has a corresponding discussion of these results.

[1] Bettina Laugwitz, Theo Held, and Martin Schrepp. 2008. Construction and Evaluation of a User Experience Questionnaire. In HCI and

Usability for Education and Work, Andreas Holzinger (Ed.). Springer Berlin Heidelberg, Berlin, Heidelberg, 63–76.

[2] Martin Schrepp, Andreas Hinderks, and Jörg Thomaschewski. 2014. Applying the User Experience Questionnaire (UEQ) in Different

Evaluation Scenarios. In Design, User Experience, and Usability. Theories, Methods, and Tools for Designing the User Experience, Aaron

Marcus (Ed.). Springer International Publishing, Cham, 383–392.