Cartographic Sign Detection Dataset (CaSiDD)
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<<< This dataset is not released yet. Release date: 1st September, 2025. >>>The Cartographic Sign Detection Dataset (CaSiDD) comprises 796 manually annotated historical map samples, corresponding to 18,750 cartographic signs, like icons and symbols. Moreover, the signs are categorized into 24 distinct classes, like tree, mill, hill, religious edifice, or grave. The original images are part of the Semap dataset [1]. The dataset is published in the context of R. Petitpierre's PhD thesis: Studying Maps at Scale: A Digital Investigation of Cartography and the Evolution of Figuration [2]. Details on annotation, and statistics on annotated cartographic signs are provided in the manuscript. Organization of the data To come soon. Descriptive statistics Number of distinct classes: 24 + hapaxesNumber of image samples: 796Number of annotations: 18,750Study period: 1492–1948. Use and Citation For any mention of this dataset, please cite : @misc{casidd_petitpierre_2025, author = {Petitpierre, R{\'{e}}mi and Jiang, Jiaming}, title = {{Cartographic Sign Detection Dataset (CaSiDD)}}, year = {2025}, publisher = {EPFL}, url = {https://doi.org/10.5281/zenodo.16278381}}@phdthesis{studying_maps_petitpierre_2025, author = {Petitpierre, R{\'{e}}mi}, title = {{Studying Maps at Scale: A Digital Investigation of Cartography and the Evolution of Figuration}}, year = {2025}, school = {EPFL}} Corresponding author Rémi PETITPIERRE - remi.petitpierre@epfl.ch - ORCID - Github - Scholar - ResearchGate Work ethics 85% of the data were annotated by RP. The remainder was annotated by JJ, a master's student from EPFL, Switzerland. License This project is licensed under the CC BY 4.0 License. Liability We do not assume any liability for the use of this dataset. References Petitpierre R, Gomez Donoso D, Krisel B (2025) Semantic Segmentation Map Dataset (Semap). EPFL. https://doi.org/10.5281/zenodo.16164782 Petitpierre R (2025) Studying Maps at Scale: A Digital Investigation of Cartography and the Evolution of Figuration. PhD thesis. École Polytechnique Fédérale de Lausanne.
