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Welcome to SODHA, the Belgian federal data archive for social sciences and the digital humanities!

Here you can find and deposit social science and digital humanities data in reusable form. Published datasets receive a DOI, making them citable like other types of publications. SODHA promotes open data by enabling reuse of research data and by safely preserving datasets in the long term.

SODHA is the Belgian service provider in the Consortium of European Social Science Data Archives (CESSDA) and is hosted by the State Archives of Belgium. SODHA was built with the help of DEMO (UCLouvain) and Interface Demography (VUB).

You can consult the SODHA Guide here, and you can read our policies here.

Want to learn more about SODHA? Consult our brochure or our presentation on the State Archives' website.

If you have any question, you can contact us at sodha@arch.be.
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41 to 50 of 2,772 Results
SEAD Platform Survey
Mar 24, 2025
Gevaert, Jessie; Vanroelen, Christophe; Van Aerden, Karen; Doms, Jens; Vandevenne, Elief, 2025, "SEAD Platform Survey", https://doi.org/10.34934/DVN/JOFL09, Social Sciences and Digital Humanities Archive – SODHA, V1
The SEAD Platform Survey is conducted by the SEAD (Sustainable Employment in the Age of Digitalization) Consortium consisting of partners from VUB (Vrije Universiteit Brussel), KU Leuven, ULiège (University of Liège) and ULB (Université libre de Bruxelles) - funded by Belspo. The...
Replication Data for: 4000 AI tools - 50 categories - TasticAI
Replication Data for: 4000 AI tools - 50 categories - TasticAI
Feb 27, 2025
BUREAU, Olivier, 2025, "Replication Data for: 4000 AI tools - 50 categories - TasticAI", https://doi.org/10.34934/DVN/KW6BV5, Social Sciences and Digital Humanities Archive – SODHA, V1, UNF:6:0OQxqyCsirkXlwENiEcEcQ== [fileUNF]
Introducing an extensive and openly accessible dataset custom-tailored for AI researchers and data scientists, this repository encompasses an impressive array of over 4,000 AI tools, meticulously categorized into more than 50 distinct classifications, generously made available by...
ai tool summary.png
ai tool summary.png
Feb 27, 2025 - Replication Data for: 4000 AI tools - 50 categories - TasticAI
PNG Image - 134.7 KB - MD5: 645e526e587157b6cd9815d36076c296
Tastic AI - Opensource - AI tools.tab
Feb 27, 2025 - Replication Data for: 4000 AI tools - 50 categories - TasticAI
Tabular Data - 6.4 MB - 7 Variables, 4665 Observations - UNF:6:0OQxqyCsirkXlwENiEcEcQ==
Italian Citizens’ Preference for Technocratic Ministers
Feb 27, 2025
Vittori, Davide; Pilet, Jean-Benoit; Rojon, Sebastien; Paulis, Emilien; Theuwis, Marie-Isabel, 2025, "Italian Citizens’ Preference for Technocratic Ministers", https://doi.org/10.34934/DVN/CZWD06, Social Sciences and Digital Humanities Archive – SODHA, V1, UNF:6:0oVU9x/Yro2X6EomTy2rsg== [fileUNF]
The datasets consist of two cross-sectional waves designed to measure Italian citizens' preferences for technocratic ministers. Each wave includes approximately 5,000 respondents and features an experimental component. In Wave 1, the experiment assesses preferences for policies i...
Italy - First wave - Dataset.tab
Feb 27, 2025 - Italian Citizens’ Preference for Technocratic Ministers
Tabular Data - 4.9 MB - 68 Variables, 5003 Observations - UNF:6:90ay5dHhgeSilM4GAlBWuQ==
Dataset - Wave 1
Italy - First wave - Questionnaire.xlsx
Feb 27, 2025 - Italian Citizens’ Preference for Technocratic Ministers
MS Excel Spreadsheet - 31.6 KB - MD5: 999885fc5441e14f0e5b2c0768ad30e0
Questionnaire and codebook of the dataset - Wave 1
Italy - Second wave - Dataset.tab
Feb 27, 2025 - Italian Citizens’ Preference for Technocratic Ministers
Tabular Data - 9.9 MB - 92 Variables, 5006 Observations - UNF:6:b5gfqIRTORrGx7ckCSp9Qg==
Dataset - Wave 2
Italy - Second wave - Questionnaire.xlsx
Feb 27, 2025 - Italian Citizens’ Preference for Technocratic Ministers
MS Excel Spreadsheet - 42.2 KB - MD5: 82cb8ef418261690d7e7ce3dafbdf78b
Questionnaire and codebook of the dataset - Wave 2
Stemtest 2024 / Test Electoral 2024
Feb 26, 2025
Walgrave, Stefaan; Rihoux, Benoît; Goovaerts, Ine; Jacobs, Laura; Lefevere, Jonas; Matthieu, Joke; Mongrain, Philippe; Tsoulou-Malakoudi, Artemis; Van Campenhout, Matthias; Uyttendaele, Laura; Nuytemans, Michiel; Henkens, Eva, 2025, "Stemtest 2024 / Test Electoral 2024", https://doi.org/10.34934/DVN/SOCUOL, Social Sciences and Digital Humanities Archive – SODHA, V1, UNF:6:nFYI1+gL7Cj3fsMD0kiLzg== [fileUNF]
This deposit accompanies the datasets related to the development of Stemtest 2024 / Test Electoral 2024, a voting advice application developed in the context of the 2024 general elections of June 2024. Stemtest/Test Electoral was commissioned by VRT, RTBF, Mediahuis and IPM. In t...
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