Islam West Africa Collection (IWAC)
Read-only access to the Islam West Africa Collection via Hugging Face datasets.
| Endpoint | https://islam.zmo.de/mcp/ (streamable-http) |
|---|---|
| Registry version | 5.0.0 |
| Now | 39 tools · grade D (58) · pin ts_5d9186f54d06fbf6b84ed2be14681a5e · protocol 2025-06-18 |
| First / last listed | 2026-10-31 03:02 UTC / 2026-10-31 03:02 UTC |
| Grade over time | 2026-10-31: D (58), 39 tools |
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Tools: search fetch explore_corpus search_articles get_article semantic_search_articles search_by_sentiment get_sentiment_distribution search_index get_index_entry list_subjects list_locations list_persons get_collection_stats get_newspaper_stats get_country_comparison get_temporal_distribution get_topic_distribution get_field_distribution get_cooccurrence get_place_distribution get_semantic_map get_similar_items get_lexical_metrics search_publications list_periodicals get_publication_fulltext semantic_search_publications search_references get_reference semantic_search_references search_documents get_document search_audiovisual list_audiovisual get_audiovisual search_images get_image semantic_search_images
search | Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every params: query*, limit |
fetch | Retrieve the full text and metadata of one IWAC item by an id returned from `search` (format '<category>:<number>', e.g. 'articles:28576'). Returns {id, title, text, url, metadata}: `text` is the item's OCR / abstract / transcription / description, `url` is the canonical islam.zmo.de link to cite, and `metadata` holds the remaining fields (author, date, country, newspaper, AI sentiment, …). Catego params: id* |
explore_corpus | Selection workbench: items, concordance, coverage, compare (requires comparison), attention, aliases, or paginated manifest/CSL-JSON/BibTeX exports. Exact filters intersect. limit/offset also page compare/coverage/attention cells. Coverage measures archive availability. Exports identify this page and dataset snapshot; compare snapshot IDs across pages. Schema discovery: iwac://datasets/{subset}. params: mode, subset, selection, comparison, offset, limit, link |
search_articles | Search IWAC newspaper articles by keyword (title + OCR + AI abstracts, French and English), country, newspaper, subject, and date range. Use French concept keywords regardless of the user's report language. Matching is accent- and case-insensitive. params: keyword_mode, keyword_aliases, exact, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, with_description, limit, offset |
get_article | Get one article (by id): full metadata, the AI abstract (description_ai), AI sentiment, and OCR text, in 25k-char parts (follow `next_offset`). Pass a `keyword` to get ~2000-char excerpts around each match instead. params: article_id*, keyword, context_chars, max_excerpts, offset |
semantic_search_articles | Semantic search over article title + full text, including articles whose OCR is not public. Query in any language. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query. params: query*, country, newspaper, date_from, date_to, limit |
search_by_sentiment | Filter articles by gpt-5-6-luna sentiment labels (accent/case-insensitive exact match). One model's reading, not a consensus — 4 other models scored the same articles and often disagree; get_sentiment_distribution with model:"all" shows by how much. `subjectivity` is much the weakest of the three scales, so treat a set selected on it as a lead to read rather than as a finding. params: polarity, centrality, subjectivity, country, subject, disputed, limit, offset |
get_sentiment_distribution | Aggregate AI labels over a shared selection. model:"all" compares independent annotators and their coverage; model:"consensus" reads the stored panel majority. Choose compare_models and agreement_field for pairwise Cohen's kappa and quadratic weighted kappa, with explicit denominators. Labels are interpretations, not ground truth; subjectivity is weak evidence and its caveat must accompany finding params: keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, model, compare_models, agreement_field |
search_index | Search the IWAC authority index (persons, places, organisations, events, subjects) by name. Accent/case-insensitive. params: keyword*, index_type, limit, offset |
get_index_entry | Get full details of an index entry by id (raw dataset columns, French names — Titre, Prénom, Coordonnées…). params: entry_id* |
list_subjects | List sujets from the IWAC index, sorted by frequency (most-referenced first). params: limit, offset |
list_locations | List lieux from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria reaches only the few entries its references mention (index frequency counts articles, publications and refer params: limit, offset, country |
list_persons | List personnes from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria reaches only the few entries its references mention (index frequency counts articles, publications and r params: limit, offset, country |
get_collection_stats | Overall statistics for every IWAC subset, including `fulltext_coverage` — how many items in each subset actually carry searchable full text in this dataset. Read that before treating any keyword count as a full-text census. params: none |
get_newspaper_stats | Per-newspaper article counts and date ranges. params: country |
get_country_comparison | Compare article counts, newspaper counts, date ranges, and gpt-5-6-luna polarity across countries. params: none |
get_temporal_distribution | Counts by Gregorian or Hijri year/month, or pooled lunar month. Group by country/newspaper. Partial dates and missing lunar dates are disclosed. normalize_by returns numerator counts and per-bucket denominators in the same country/outlet/date scope, removing thematic filters. Shares describe IWAC holdings. params: keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, normalize_by, subset, granularity, calendar, group_by |
get_topic_distribution | Counts of offline LDA topic assignments, optionally over time. Topic labels are interpretive model outputs; exact topic_id filters select assignments rather than keyword matches. Reports unclassified coverage. params: subset, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, min_prob, over_time, top_n |
get_field_distribution | Rank exact metadata values, splitting pipe-separated tags. Reports missing metadata and optional coverage over time. Choose spatial for mentioned places, country for stored country tags, or subject/author/language. params: field*, subset, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, top_n, over_time |
get_cooccurrence | Count pairs of metadata values co-tagged on the same items. Matrix/network views show descriptive associations, not causal links. Filters apply before pair counting; top_n caps the vocabulary. params: field, subset, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, top_n |
get_place_distribution | Place tags joined to authority coordinates. Separates publication countries from mentioned places; missing geocodes are counted explicitly. params: subset, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, top_n |
get_semantic_map | Stable-hash sample of matching stored embeddings, projected with PCA. Reports eligible, invalid, missing and capped counts, seed and explained variance. Group counts describe the sample. Coordinates are chart-only; this is not the published UMAP landscape. Needs no API key. params: subset, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, color_by, limit |
get_similar_items | Nearest stored embeddings by cosine similarity. Articles and documents lead with the dataset's published top 10. Scores run high (unrelated ~0.7) and rank reading candidates; >= 0.97 suggests a near-duplicate, but no threshold proves a reprint. Returns source IDs and dates. Corpus-wide candidate generation belongs offline. params: id*, subset, limit, min_score |
get_lexical_metrics | Text length, lexical richness and readability by country/newspaper/year. Metrics are precomputed; readability is French-specific and excludes other languages. Missing values are disclosed. Compare distributions as descriptive evidence. params: group_by, keyword, country, newspaper, subject, date_from, date_to, hijri_month, hijri_year, keyword_mode, keyword_aliases, exact, top_n |
search_publications | Search Islamic publications (periodical issues, books). `keyword` matches title, subject, table of contents, and full OCR text (TOC hits come back as matching_toc_entries); use French concept keywords regardless of the user's report language. Filter by newspaper/series, subject, country and year. Use list_periodicals to discover series titles, and get_publication_fulltext for keyword excerpts from params: keyword_mode, keyword_aliases, exact, keyword, newspaper, subject, country, date_from, date_to, hijri_month, hijri_year, limit, offset |
list_periodicals | List the Islamic periodical/series titles in the publications subset, with issue counts and year ranges. Use the returned newspaper value as the `newspaper` filter on search_publications. params: country |
get_publication_fulltext | Full OCR text of a publication in 25k-char parts (follow `next_offset`), or ~2000-char excerpts around keyword matches (accent-insensitive; capped: see match_count vs excerpts_returned). params: publication_id*, keyword, context_chars, max_excerpts, offset |
semantic_search_publications | Semantic search over publication tables of contents, present for ~40% of issues (none for An-Nasr Vendredi, 130 of 695 Islam Info issues): use search_publications for the rest. Rows show the first 600 characters of each table. Query in any language. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query. params: query*, country, limit |
search_references | Search academic references (journal articles, book chapters, theses, books, reports) by keyword and metadata. `keyword` requires every word in the title + abstract ("quote" a phrase). References are multilingual: try French and English title/abstract keywords when relevant; metadata/filter values such as `reference_type` and `language` use French labels. Results include a short abstract snippet — params: keyword, author, reference_type, subject, country, language, date_from, date_to, limit, offset |
get_reference | Full bibliographic record for one academic reference (by id), including the complete abstract (present for ~51% of references), subjects, DOI/URL, and host-work details (book, volume, issue, pages). params: reference_id* |
semantic_search_references | Semantic search over academic references by title + abstract, across languages. Only references with an abstract (about half) are covered; use search_references for the rest. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query. params: query*, reference_type, country, language, date_from, date_to, limit |
search_documents | Search the small archival-documents subset (~26 items: Islamic association reports, flyers, project documents — mostly Burkina Faso). Use French concept keywords regardless of the user's report language. Most have OCR text and an AI description. Call with no arguments to list all. params: keyword, country, limit, offset |
get_document | Get one archival document (by id): full metadata, AI description, and OCR text, in 25k-char parts (follow `next_offset`). Pass a `keyword` to get ~2000-char excerpts around each match instead, useful for long documents. params: document_id*, keyword, context_chars, max_excerpts, offset |
search_audiovisual | Search audiovisual materials by keyword and metadata: francophone web video from Burkina Faso, Togo and Benin (TV reports, association and campus recordings), plus deposited Nigerian Hausa/Arabic recordings. Keyword matches title, creator, publisher, subject, spatial, language, source, the item's own description (the richest text most of these items have) and its transcription where one exists. Ea params: keyword, country, language, medium, publisher, source_type, subject, limit, offset |
list_audiovisual | List audiovisual materials, newest first (francophone web video from Burkina Faso, Togo and Benin; deposited Nigerian Hausa/Arabic recordings). Filter by country, publishing channel or `source_type`. params: country, publisher, source_type, limit, offset |
get_audiovisual | Get one audiovisual record by id: full description and transcription (where one exists), creator/publishing channel, duration, medium, subjects, places, language, rights, source, and three distinct links: `url` (the IWAC page, the one to cite), `external_url` (where a harvested video plays) and `media_url` (a deposited file). `source_type` says which to expect. A long transcription comes in 25k-ch params: audiovisual_id*, keyword, offset |
search_images | Search the IWAC photographs (30 items: mosques, radio stations, schools, signage and street scenes documented during fieldwork). Keyword matches title, creator, subject, place and the rare caption. Each result carries `image_url` (the full-resolution file), `coordinates` ('lat, lng' where known) and the canonical IWAC page. Call with no arguments to list all. Captions are almost never present, so params: keyword, country, subject, spatial, creator, date_from, date_to, limit, offset |
get_image | Get one photograph by id: title, photographer, capture date, place and coordinates, subjects, rights, the IIIF manifest, and the full-resolution `image_url`. The server returns URLs, not image bytes. params: image_id* |
semantic_search_images | Find photographs by describing what they SHOW, in any language ('mosquée en construction', 'street signage in Arabic'). This is cross-modal: the ranking runs against a multimodal embedding of the photograph itself, not against a caption, so it works even though only 2 of the 30 images have one. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similari params: query*, country, limit |
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