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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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11 to 20 of 4,336 Results
Codebooktssq25_1_SUF_NL_v2.0.pdf
Codebooktssq25_1_SUF_NL_v2.0.pdf
Aug 28, 2026 - rEUsilience - Family Dynamics and Labour Market Risks (tssq25_1)
Adobe PDF - 264.7 KB - MD5: 934208dab49bf486ca3b81f6c34f44c6
Stata export of the dataset v 2.0
tssq25_1_SUF_v2.0_CSV.tab
Aug 28, 2026 - rEUsilience - Family Dynamics and Labour Market Risks (tssq25_1)
Tabular Data - 8.3 MB - 224 Variables, 2254 Observations - UNF:6:2wptholm/ZhVLRkyMklF/w==
CSV export of the dataset v 2.0
tssq25_1_SUF_v2.0_SPSS.tab
Aug 28, 2026 - rEUsilience - Family Dynamics and Labour Market Risks (tssq25_1)
Tabular Data - 1.6 MB - 224 Variables, 2254 Observations - UNF:6:qb1kur9VxUc6vdWn1vPtfw==
SPSS export of the dataset v 2.0
tssq25_1_SUF_v2.0_STATA.tab
Aug 28, 2026 - rEUsilience - Family Dynamics and Labour Market Risks (tssq25_1)
Tabular Data - 1.9 MB - 224 Variables, 2254 Observations - UNF:6:qb1kur9VxUc6vdWn1vPtfw==
Stata export of the dataset v 2.0
tssq25_1_UserGuide_v2.0.pdf
tssq25_1_UserGuide_v2.0.pdf
Aug 28, 2026 - rEUsilience - Family Dynamics and Labour Market Risks (tssq25_1)
Adobe PDF - 355.2 KB - MD5: 86278cc92a3598d82e6eb8b5586fc2d7
Data user guide v 2.0
Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal
Aug 25, 2026
Zuzana Černáková; Fien Messens; Tess Dejaeghere; Julie M. Birkholz, 2026, "Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal", https://doi.org/10.34934/DVN/HNA7QO, Social Sciences and Digital Humanities Archive – SODHA, V1, UNF:6:MemhfA5Fl4s1tvLWf4VR2A== [fileUNF]
This dataset accompanies the article From nineteenth-century letters to entities: A Named Entity Recognition pipeline for French correspondence and its methodological lessons. It contains the input data, preprocessing scripts, analysis notebooks, evaluation outputs, and experimen...
00_navez_gold_standard_preprocessing_json2df.ipynb
Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal
Jupyter Notebook - 465.1 KB - MD5: 6062b90f470e79ad4062aa678de087d3
Preprocessing notebook that converts Label Studio JSON exports into the structured gold-standard corpus used throughout the experiments. The workflow merges annotation projects, extracts entity annotations, aligns character offsets, generates IOB labels, removes unsupported neste...
01a_navez_NER_spacy_off_the_shelf_no_dk_ner_pipe_sm.ipynb
Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal
Jupyter Notebook - 201.0 KB - MD5: fafce906de349b467636197fa64a4d95
Implements Workflow 1 described in the article by evaluating the off-the-shelf spaCy fr_core_news_sm model using only the isolated Named Entity Recognition (NER) component. The notebook evaluates the model on the held-out test set without additional domain-specific training.
01b_navez_NER_spacy_off_the_shelf_no_dk_ner_pipe_lg.ipynb
Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal
Jupyter Notebook - 248.3 KB - MD5: 4d33ecdf3831757bac0319676a57bb2a
Implements Workflow 1 using the larger fr_core_news_lg model. The notebook evaluates the isolated NER component on the historical correspondence corpus and compares its performance with the smaller spaCy model.
02a_navez_NER_spacy_off_the_shelf_no_dk_nlp_pipe_sm.ipynb
Aug 25, 2026 - Replication Data for: From nineteenth-century letters to entities: "a NER pipeline for French correspondence and its methodological lessons" - Article for Digital Humanities Benelux Journal
Jupyter Notebook - 200.0 KB - MD5: 2998c19d3448da4d9ed7a7776de6e9dc
Implements Workflow 2 by using the complete spaCy fr_core_news_sm pipeline, including all NLP components. The notebook assesses whether embedding the NER component within the full pipeline influences recognition performance.
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