| ---
|
| license: cc-by-4.0
|
| pretty_name: "GAIA / GARDIAN-CIGI Agricultural Research Corpus"
|
| tags:
|
| - "science"
|
| - "agriculture"
|
| - "academic"
|
| - "rag"
|
| - "cgiar"
|
| - "multilingual"
|
| - "documents"
|
| - "research"
|
| - "food-security"
|
| - "climate-adaptation"
|
| - "sdg 1 - no poverty"
|
| - "nutrition"
|
| - "food security"
|
| - "africa south of sahara"
|
| - "carbon"
|
| - "climate change"
|
| - "latin america and the caribbean"
|
| - "nutrition, health and food security"
|
| - "poverty reduction, livelihoods and jobs"
|
| - "sdg 2 - zero hunger"
|
| - "sdg 8 - decent work and economic growth"
|
| - "systems transformation"
|
| - "decision making"
|
| - "health"
|
| - "africa"
|
| task_categories:
|
| - summarization
|
| - text-retrieval
|
| - question-answering
|
| - text-generation
|
| - feature-extraction
|
| size_categories:
|
| - n<1K
|
| configs:
|
| - config_name: full_text_en
|
| default: true
|
| data_files:
|
| - split: train
|
| path: "FULL_TEXT/EN/Parquet/*.parquet"
|
| - config_name: abstracts_only_en
|
| data_files:
|
| - split: train
|
| path: "ABSTRACTS_ONLY/EN/Parquet/*.parquet"
|
| - config_name: abstracts_only_es
|
| data_files:
|
| - split: train
|
| path: "ABSTRACTS_ONLY/ES/Parquet/*.parquet"
|
| - config_name: abstracts_only_fr
|
| data_files:
|
| - split: train
|
| path: "ABSTRACTS_ONLY/FR/Parquet/*.parquet"
|
| ---
|
|
|
| # GAIA / GARDIAN-CIGI Agricultural Research Corpus
|
|
|
| This dataset contains **20** agricultural research records from the GARDIAN repository, processed through the CIGI pipeline: **6** with full text and **14** with metadata and abstract only.
|
|
|
| ## Repository Layout
|
|
|
| ```
|
| FULL_TEXT/<LANG>/ documents with extracted full text
|
| ABSTRACTS_ONLY/<LANG>/ documents with metadata and abstract only
|
| JSON/ one JSON file per document (metadata + content)
|
| Markdown/ one Markdown file per document (metadata front matter + text)
|
| Parquet/ all documents of the folder in Parquet (part files)
|
| ```
|
|
|
| Each `FULL_TEXT`/`ABSTRACTS_ONLY` + language folder is available as a separate config in the dataset viewer, e.g. `load_dataset("sciosystems/test", "full_text_en")`.
|
|
|
| | Folder | Documents | Tokens | Files | Size |
|
| |---|---:|---:|---:|---:|
|
| | `ABSTRACTS_ONLY/EN` | 9 | 0 | 20 | 146.30 KB |
|
| | `ABSTRACTS_ONLY/ES` | 3 | 0 | 7 | 73.58 KB |
|
| | `ABSTRACTS_ONLY/FR` | 2 | 0 | 5 | 40.12 KB |
|
| | `FULL_TEXT/EN` | 6 | 29,954 | 13 | 468.00 KB |
|
|
|
| ## Dataset Overview
|
|
|
| | Property | Value |
|
| |----------|-------|
|
| | **Total Documents** | 20 |
|
| | **Full-Text Documents** | 6 |
|
| | **Abstract-Only Documents** | 14 |
|
| | **Total Size (all formats)** | 728.00 KB |
|
| | **Total Tokens (full text)** | 29,954 |
|
| | **Total Characters (full text)** | 188,904 |
|
| | **Avg. Tokens per Full-Text Document** | 4,992 |
|
| | **Total Pages (partly est.)** | 76 |
|
| | **Languages** | 3 |
|
| | **Countries** | 18 |
|
| | **Unique Keywords** | 211 |
|
| | **Resource Types** | 6 |
|
| | **Documents with Source URL** | 20 (100.0%) |
|
| | **Date Generated** | 2026-11-04 18:27:07 |
|
|
|
| Tokens are counted on the `content` field of full-text documents using the `o200k_base` tokenizer (tiktoken). 3 of 6 full-text documents have a real page count; the rest are estimated at 500 words per page.
|
|
|
| ## Language Distribution
|
|
|
| | Language | Count | Percentage |
|
| |----------|------:|-----------:|
|
| | English | 15 | 75.0% |
|
| | Spanish | 3 | 15.0% |
|
| | French | 2 | 10.0% |
|
|
|
| ## Resource Types
|
|
|
| | Type | Count | Percentage |
|
| |------|------:|-----------:|
|
| | Dataset / Tabular | 7 | 35.0% |
|
| | Scientific Publication | 6 | 30.0% |
|
| | Report | 2 | 10.0% |
|
| | Brief | 2 | 10.0% |
|
| | Training Material | 2 | 10.0% |
|
| | Dataset / Geospatial | 1 | 5.0% |
|
|
|
| ## Top Countries
|
|
|
| | Country | Count | Percentage |
|
| |---------|------:|-----------:|
|
| | Peru | 3 | 15.0% |
|
| | Viet Nam | 2 | 10.0% |
|
| | Indonesia | 2 | 10.0% |
|
| | Mali | 2 | 10.0% |
|
| | India | 1 | 5.0% |
|
| | Ethiopia | 1 | 5.0% |
|
| | Bangladesh | 1 | 5.0% |
|
| | Guyana | 1 | 5.0% |
|
| | Russia | 1 | 5.0% |
|
| | Colombia | 1 | 5.0% |
|
| | Democratic Republic of the Congo | 1 | 5.0% |
|
| | Malawi | 1 | 5.0% |
|
| | Uganda | 1 | 5.0% |
|
| | Honduras | 1 | 5.0% |
|
| | Guatemala | 1 | 5.0% |
|
| | Kenya | 1 | 5.0% |
|
| | Costa Rica | 1 | 5.0% |
|
| | Nigeria | 1 | 5.0% |
|
|
|
| ## Top Keywords
|
|
|
| sdg 1 - no poverty, nutrition, food security, africa south of sahara, carbon, climate change, latin america and the caribbean, nutrition, health and food security, poverty reduction, livelihoods and jobs, sdg 2 - zero hunger, sdg 8 - decent work and economic growth, systems transformation, decision making, health, africa, research, emission, models, tropical forests, biomass
|
|
|
| ## Publication Years
|
|
|
| 2026 (1), 2025 (3), 2024 (2), 2023 (1), 2022 (2), 2021 (1), 2020 (1), 2018 (2), 2017 (2), 2015 (3), 2014 (2)
|
|
|
| ## Rights
|
|
|
| Per-document licensing varies. Distribution of the `rights` field:
|
|
|
| | Rights | Docs | Share |
|
| |---|---:|---:|
|
| | CC-BY | 20 | 100.0% |
|
|
|
| > **Rights are heterogeneous.** The repo-level `cc-by-4.0` tag reflects the curation of the collection, **not** a uniform document license. **Always check the per-document `rights` field (and the source at `url`, where available) before redistributing or using individual documents commercially.**
|
|
|
| ## Document JSON Schema
|
|
|
| ```json
|
| {
|
| "gardian_id": "string",
|
| "source": "string",
|
| "url": "string",
|
| "description": "string",
|
| "id": "string",
|
| "title": "string",
|
| "language": "string",
|
| "resource_type": "string",
|
| "release_year": "string",
|
| "rights": "string",
|
| "dataNODE_id": "string",
|
| "keywords": "list[string]",
|
| "geography": {
|
| "regions": "list[string]",
|
| "countries": "list[string]"
|
| },
|
| "content": "string"
|
| }
|
| ```
|
|
|
| ## License
|
|
|
| This dataset is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/).
|
|
|
| ## Acknowledgements
|
|
|
| This dataset was developed for the [Generative AI for Agriculture (GAIA)](https://www.ifpri.org/project/generative-ai-for-agriculture-gaia/) project, funded by the Gates Foundation and UK International Development (FCDO), in collaboration between [CGIAR](https://www.cgiar.org/) and [SCiO](https://scio.systems/).
|
|
|
| ---
|
|
|
| *Generated automatically on 2026-11-04 18:27:07*
|
|
|
