LINDAT / CLARIAH-CZ DH Data

Permanent URI for this collectionhttp://hdl.handle.net/20.500.12800/3

Digital Humanities data from partner institutions of LINDAT/CLARIAH-CZ project. If you are participating in LINDAT/CLARIAH-CZ project, please submit your work to this repository.

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Now showing 1 - 20 out of 25 results

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MalachNER

(Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2026-04-03) Brückner, Christopher; Roginer Hofmeister, Karin; Kocián, Jiří; Pecina, Pavel

MalachNER is a collection of transcripts of interviews with 13 Holocaust survivors in 10 languages, covering approximately 37 hours of speech in total, sourced from different archives (Visual History Archive, United States Holocaust Memorial Museum, Milan Šimečka Foundation). Domain experts tagged named entities in the denoised transcripts based on domain-specific annotation guidelines with entity types Person, Organization, Location, Camp, Ghetto, Date, and Miscellaneous. The dataset includes per-language training and test splits and the annotation guidelines.

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Ancient Egyptian Women's Database

(Charles University, Faculty of Arts, Czech Institute of Egyptology, 2026-07-02) Kelly, Susan

This dataset is the csv file of the data used to create the primary digital outcome of the Marie Skłodowska-Curie Actions (MSCA) Postdoctoral Fellowship project, “The Impact of Political and Climate Change on Women’s Agency: A Social Power Analysis” (IPOCCWWA - Grant No. 101148700). It comprises of a legacy archive containing women's biographical records with bibliographical data used for the online database: Ancient Egyptian Women's Database (AEWD). The link is: https://ancientegyptianwomensdatabase.cegu.ff.cuni.cz/. The database is licensed as open-access CC BY 4.0. The project was hosted at the Czech Institute of Egyptology, Charles University in Prague from June 2024 to June 2026. While the core fellowship focused intensively on the social power of women during the First Intermediate Period (FIP), the final dataset comprises a total of 2,165 individual records tracking women across the early historical phases of ancient Egypt (Dynasties 1-11). The dataset is the culmination of a long-term, multi-stage research trajectory spanning more than a decade of academic investigation into the social power of ancient Egyptian women: • Early Dynastic Core (Dynasties 1–3): The foundation of this data originated during the author’s master’s research focusing on women’s funerary monuments, which was subsequently expanded during the MSCA fellowship research to include a wider corpus of identified material culture. • Epigraphic Augmentation: The Early Dynastic records have been significantly enriched through the systematic inclusion of sealings, drawing primarily upon the foundational corpus and documentation established by Eva-Marie Engel. • Old Kingdom to FIP Reassessments (Dynasties 4–6 to 7–11): To ensure maximum chronological precision, records originally published in the author’s 2024 monograph underwent a rigorous audit. Several entries previously designated as Old Kingdom have been removed from those historic blocks and reintegrated with revised, more accurate attributions placing them securely within the First Intermediate Period. Legacy record numbers from the existing monograph: Kelly, Sue. 2024. Unveiling Female Social Power in Early Egypt, Oxford were deleted and replaced with new, standardized database identifiers. My research interdisciplinary methodology employs specific modes of operation across data collection, theoretical framework, and modeling. The data collection retrieved from funerary artefacts is collected in the same manner as any other blind study. I collect as many women as possible in the given timeframe, creating individual records, irrelevant if they hold any functional titles or what I call engagement titles. The reason for this is two-fold. Firstly, data regarding women without titles; even these null quantities add to the veracity of the statistical analysis that provides greater insight into the culture. Secondly, these women are often overlooked in traditional title studies, where research starts with the title and not the women. Each woman's record contains the data necessary for my research and forms the basis of the database. I consult primary sources in person where possible in museums and secondary sources. In particular, Melanie Pitkin’s seminal corpus of False Doors and stelae, and period specific works such as Edward Brovarski’s analysis of the Nag ed-Der material. Navigation of the data can be accessed via women's names, titles, geographical findspots, modern museum locations, artefact typology, and the source material and references.

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Content-specific classification of historical page images - annotated dataset

(Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2026-06-20) Lutsai, Kateryna; Křivánková, Dana

This dataset employs a comprehensive 11-label classification scheme to categorize scanned images of document pages. The types are based on their content and presentation format. The scheme distinguishes between visual content (drawings, maps, paintings, schematics, and photographs), textual content (handwritten, printed, or machine-typed), and hybrid formats that combine multiple elements. Special attention is given to layout characteristics, with separate labels designated for content presented in tabular or form-like structures versus paragraph or block formats. For instance, we differentiate between standard drawings (DRAW📈) and drawings with table-based legends (DRAW_L📈📏), as well as between regular photographs (PHOTO🌄) and those embedded within tabular layouts (PHOTO_L🌄📏).
The textual categories are particularly nuanced, distinguishing between three input methods—handwritten (✏️), printed (📄), and machine-typed (📄)—and further subdividing these based on structural organization. Text can appear in either tabular/form-like arrangements (LINE_HW, LINE_P, LINE_T) or in traditional paragraph/block formats (TEXT_HW, TEXT_P, TEXT_T). An additional TEXT📰 category accommodates mixed documents that combine multiple text types or include minor graphical elements, providing flexibility for complex real-world documents.
The dataset is organized using a 5-fold cross-validation structure, with each fold maintaining an 80-10-10 split for training, development, and test sets respectively. This partitioning information is documented in an accompanying CSV file, enabling robust model evaluation and the potential for ensemble approaches where models trained on different folds can be averaged together to create a more robust combined model, provided they share the same base architecture.

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OptiQ

(Institute of Philosophy of the Czech Academy of Sciences, 2026) Pavlíček, Ota; Lička, Lukáš; Škvrňák, Jan

The OptiQ project aims to create a database application for a corpus of medieval and early modern texts on the history of optics, which are preserved mainly in manuscripts. The project is based on David C. Lindberg's A Catalogue of Medieval and Renaissance Optical Manuscripts (1975). The database, which also includes Bohemian and Central European manuscripts and literature, provides access to other online relevant materials (digital manuscript catalogues, editions, manuscript facsimiles, author databases, etc.) according to the latest digital standards (e.g. IIIF). In synergy with Dr Lukáš Lička's research, supported by the Czech Grant Agency within the project Peckham's Age: The Role of Jan Peckham's Perspectiva communis in the Dissemination and Development of Optical Knowledge, 1279-1542, the database will be expanded in the last phase to include many newly discovered texts and manuscripts. This will constitute a scientific infrastructure corresponding to the current knowledge and research needs.

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UniQ

(Institute of Philosophy of the Czech Academy of Sciences, 2023) Pavlíček, Ota; Škvrňák, Jan

The UniQ project is dedicated to the Prague struggle over universals ca. 1348–1500, making information about the corresponding corpus of texts available in a digital environment. It includes primarily information about texts written at the University of Prague and texts available in Bohemia that are relevant to the dispute over universals, although their influence was broader.

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Anonymized Questionnaires and Response Data for the Bachelor Thesis "False Friends in Czech, Ukrainian and Russian in the Usage of Multilingual Ukrainian Speakers"

(Charles University, Faculty of Arts, 2026-06-13) Filonenko, Daria

This dataset contains anonymized responses from 60 participants collected as part of the empirical research for the bachelor’s thesis “False Friends in Czech, Ukrainian and Russian in the Usage of Multilingual Ukrainian Speakers.” It includes both the completed language test responses and a structured spreadsheet containing transcribed questionnaire answers. The dataset was used for statistical analysis, data visualization, and the evaluation of research hypotheses. All personally identifiable information was removed prior to publication to ensure participant anonymity and privacy.

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MusiCorpus v1.0

(Universitat Autònoma de Barcelona, Computer Vision Center, 2026-04-30) Torras, Pau; Mayer, Jiří; Badal, Carles; Dvořáková, Martina; Herzánová Vlková, Markéta; Asbert, Gerard; Dvořák, Vojtěch; Šomorjai, Samuel; Hajič jr., Jan; Fornés, Alicia

The MusiCorpus v1.0 dataset provides 1,309 pages of historical sheet music, primarily handwritten, with MusicXML transcriptions and symbol annotations, for training and evaluating Optical Music Recognition (OMR) systems in realistic conditions. It is the largest dataset of handwritten music to date and the first dataset containing a realistic representative sample of musical document collections from memory institutions. A large amount of musical heritage has been digitised by archival institutions, but the field of Optical Music Recognition (OMR) has struggled with making this music machine-readable and therefore findable despite progress in deep learning methods, because no datasets for training systems in realistic conditions were available. MusiCorpus is suitable for training and evaluating both end-to-end systems and object detection-based OMR systems and comparing their performance.

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Projekt_ZDH_transkripce

(Charles University, Faculty of Arts, Institue of Czech language and theory of communication, 2026-02-06) Frančová, Marie

Text written in kurrent transcribed through Transkribus and then finished by hand.

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Little Big Translation Literature – Czech and German Translations of Yiddish Literature as a Reflection of Changing Politics and Society

(Palacky University, Department of German Studies, 2025-12-15) Krappmann, Marie

In order to make the process of preparing analyses for a planned monograph about Czech and German translations of Yiddish texts transparent, five source texts were transcribed from Yiddish and Czech and German target texts were annotated. The intention of the annotations is to clarify the individual steps and aspects of the text translation analysis. The focus lies primarily on semantic and culturally conditioned shifts in the partial analyses. Shifts at the grammatical level and shifts conditioned by the different language structure are taken into consideration only if they are relevant to the analysis.

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Quality of Working Life 2024

(Faculty of Arts, Charles University, 2024-12) Vinopal, Jiří; Štěpánek, Martin

A regular survey conducted as part of the long-term monitoring of the quality of working life in the Czech Republic, carried out using the research tool SQWLi (https://www.pracovnipohoda.cz/o-projektu-kpz/o-projektu/indikator-sqwli/). Monitoring has been conducted since 2011, usually once a year, allowing the data to be linked into time series.

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Quality of Working Life 2023

(Faculty of Arts, Charles University, 2023-12) Vinopal, Jiří; Štěpánek, Martin

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Quality of Working Life 2022

(Faculty of Arts, Charles University, 2022-12) Vinopal, Jiří; Štěpánek, Martin

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Content-based annotation of page images from the (archaeological) historical archive

(Charles University in Prague, UFAL, 2025-10-10) Lutsai, Kateryna; Křivánková, Dana

This dataset employs a comprehensive 11-label classification scheme to categorize scanned images of document pages. The types are based on their content and presentation format. The scheme distinguishes between visual content (drawings, maps, paintings, schematics, and photographs), textual content (handwritten, printed, or machine-typed), and hybrid formats that combine multiple elements. Special attention is given to layout characteristics, with separate labels designated for content presented in tabular or form-like structures versus paragraph or block formats. For instance, we differentiate between standard drawings (DRAW📈) and drawings with table-based legends (DRAW_L📈📏), as well as between regular photographs (PHOTO🌄) and those embedded within tabular layouts (PHOTO_L🌄📏). The textual categories are particularly nuanced, distinguishing between three input methods—handwritten (✏️), printed (📄), and machine-typed (📄)—and further subdividing these based on structural organization. Text can appear in either tabular/form-like arrangements (LINE_HW, LINE_P, LINE_T) or in traditional paragraph/block formats (TEXT_HW, TEXT_P, TEXT_T). An additional TEXT📰 category accommodates mixed documents that combine multiple text types or include minor graphical elements, providing flexibility for complex real-world documents. The dataset is organized using a 5-fold cross-validation structure, with each fold maintaining an 80-10-10 split for training, development, and test sets respectively. This partitioning information is documented in an accompanying CSV file, enabling robust model evaluation and the potential for ensemble approaches where models trained on different folds can be averaged together to create a more robust combined model, provided they share the same base architecture. --- This item contains 318 files covered by a license prohibiting their public dissemination. If you need this full dataset including those files for replication of results, request permission from David Novák at the Institute of Archeology of the CAS, Prague: novak@arup.cas.cz For any other purposes, we recommend using the version of this dataset without these files that is otherwise identical (>99.99%) and released under a CC license: http://hdl.handle.net/20.500.12800/1-6184

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MIXPAR Database: Version 1.0 (September 2025)

(Filozofická fakulta, Univerzita Karlova, 2025-10-01) Štichauer, Pavel; Ripamonti, Fabio

MIXPAR: A Database of Mixed Perfective Auxiliation in Italo-Romance (v1.0). This is the first public release (v1.0) of the MIXPAR database, a large-scale dataset documenting auxiliary selection patterns in Italo-Romance dialects. The project focuses on mixed perfective paradigms—systems that alternate between essere (‘be’) and avere (‘have’) within the same TAM paradigm. The data is based on fieldwork and dialectal atlases and includes both structural pattern annotations and GPS-based geographic metadata, enabling advanced statistical and spatial modeling.

Three files are included:
(1) MIXPAR-database-long-format_withGPS_September-2025.xlsx: full version of the database in long format with detailed linguistic and geographical annotations.
(2) mixpar_for_R_final.csv: cleaned and pre-processed version optimized for statistical modeling in R.
(3) patterns_with_gps.csv: summary of auxiliary patterns by location and TAM, enriched with geographic coordinates.

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Stereotypes and Discourse Connectors in Czech

(Institute of Philosophy of the Czech Academy of Sciences, 2025-08-26) Gvoždiak, Vít

The purpose of the dataset is to test three variables: (i) the effect of argument order in Ale-constructions (But-constructions) “A, ale B” (“A, but B”): positive A, but negative (or stereotypical category) B vs. negative (or stereotypical category) A, but positive B; (ii) the effect of the discourse connector that introduces the conclusion following from the Ale-construction (“takže” (so/therefore) vs. “nicméně” (however/nevertheless)); (iii) the effect of propositional content (stereotypical vs. neutral) on inference of the conclusion. At the most general level, the dataset is divided into two groups according to the connective introducing the conclusion: 24 “takže” scenarios and 24 “nicméně” scenarios. Each of these two categories is further divided according to (non-)stereotypicality of content, i.e., 12 neutral (non-stereotypical) scenarios and 12 stereotypical scenarios (categories: age, gender, and nationality/ethnicity), and according to the order of arguments. In neutral scenarios: 6 scenarios with the structure “positive A [positive = argument for performing R], but negative B [negative = argument for performing non-R]”. See the README file for more information regarding the structure and use of the data.

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Swedish-speaking population of Finland - statistics

(Charles University, Faculty of Arts, 2025-06-17) Pšeničková, Andrea

data about the Swedish speaking minority in Finland from Finstat used for a report in PowerBI

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Bibliography of scholarly works on artificial consciousness

(Institute of Philosophy of the Czech Academy of Sciences, 2025-04-14) Marvan, Tomas; Mihálik, Jakub

A comprehensive bibliography of scholarly works on artificial consciousness. The bibliography focuses on English language works published in recent decades in academic journals, books and other scholarly outlets. When preparing this bibliography we searched existing scientific bibliographies, including OpenAlex (openalex.org) and PhilPapers (philpapers.org), and strived to exclude irrelevant search results. The resulting database currently has over six hundred entries. Our goal is to offer a useful, freely available bibliographical tool with advanced search functionality to researchers working in the interdisciplinary field of machine consciousness, AI and related topics. The live version of the database, which we try to regularly update, can be found on this link: https://artcon.flu.cas.cz/bibliography/ and can be added/downloaded in Zotero here: https://www.zotero.org/groups/5900684/artcon.

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Dataset used in the paper Uncovering Relationships using Bayesian Networks: A Case Study on Conspiracy Theories

(Proceedings of Machine Learning Research, 2024-09-11) Vomlel, Jiří; Kuběna, Aleš; Šmíd, Martin; Weinerová, Josefína

Dataset from a Czech university entrance exam. This dataset includes a test of active, open-minded thinking designed by Jonathan Baron, as well as a test of students’ attitudes toward various conspiracies. Data were analyzed in the paper J. Vomlel, A. Kuběna, M. Šmíd, J. Weinerová. Uncovering Relationships using Bayesian Networks: A Case Study on Conspiracy Theories, Proceedings of Machine Learning Research, Volume 246 : International Conference on Probabilistic Graphical Models, p. 470-485, International Conference on Probabilistic Graphical Models 2024 /12./, (Nijmegen, NL, 20240911) https://raw.githubusercontent.com/mlresearch/v246/main/assets/vomlel24a/vomlel24a.pdf

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Testimonies of Roma and Sinti

(Institute for Contemporary History, Czech Academy of Sciences, 2024-10-01) Čapková, Kateřina; Berkyová, Renata; Patočková, Radka; Zdařilová, Eva; Jandák, Marek

The key idea of our project is to convey to the widest possible readership detailed abstracts of the testimonies of Roma and Sinti and thus their personal and irreplaceable experience of the Second World War. We hope that the Testimonies of Roma and Sinti project will contribute to greater awareness of their genocide and will be an irreplaceable source of information for researchers, relatives of the victims, or anyone else interested in this important topic. First of all, we defined the project geographically: we focused on the testimonies of Roma and Sinti from the Bohemian lands (today's Czech Republic) and Slovakia. The second definition is that we are only processing printed testimonies into the database. A valuable, and extremely demanding, part of the database is the detailed abstracts of these testimonies prepared by Romani studies experts in cooperation with historians and linguistic stylists. These abstracts are important not only for Czech and Slovak readers, as many publications with testimonies are not easily accessible, but especially for users from abroad - whether researchers, members of Romani communities or any other interested parties - as the vast majority of the hundreds of published testimonies exist only in Czech, Slovak or Romani, and are thus inaccessible to most people from abroad. Within the database, the testimonies are analyzed according to several criteria, which allow detailed searches and their classification, for example, according to the type of war experience (internment, participation in armed struggle, hiding, etc.). In the analysis, we then focused mainly on geographical data. Therefore, projections of collected data on maps are an integral part of the database, which allow us to show the war trajectory of individuals and groups, to show, for example, the locations of mass murders or guerrilla fighting, or to search for testimonies related to a place.

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The Use of Machine Translation by Ukrainian War Refugees in Czechia

(Masaryk University, Faculty of Arts, 2024) Agapova, Anna; Špačková, Stanislava

Data from a questionnaire survey conducted from 2022-08-25 to 2022-11-15 and exploring the use of machine translation by Ukrainian refugees in the Czech Republic. The presented spreadsheet contains minimally processed data exported from the two questionnaires that were created in Google Forms in the Ukrainian and the Russian language. The links to these questionnaires were distributed by three methods: direct email to particular refugees whose contact details the authors obtained while volunteering; through a non-profit organisation helping refugees (Vesna women’s education institution) and on social networks by posting links to the survey in groups associating the Ukrainian community across Czech regions and towns. Since we asked potential respondents to spread the questionnaire further, we could not prevent it from reaching Ukrainians who had arrived in Czechia previously, or received temporary protection in other countries. Due to this fact, the textual answers to the question 1.5 "Which country are you in right now?" were replaced in the dataset by numbers (1 for the Czech Republic, 2 for other countries) in order for us to be able to separate the data of respondents not located in the Czech Republic, which were irrelevant for our survey. Also, in this version of the dataset, the textual answers to the question 1.6 "How many months have you been to this country?" were replaced by numbers, so that we could separate the data of respondents who arrived in the Czech Republic in February 2022 or later from the other data (0 for those staying in Czechia before February 2022, 1 for those staying in Czechia since February 2022 or later, 2 for those staying in other countries).

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