Hindawi Arabic Books Section-Level NLP Dataset
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Custom terms — see license terms
- Source / creator
- nomeda-lab/hindawi-arabic-sections
- Collection method
- The publisher scraped book content section-by-section from Hindawi.org, then applied a cleaning pipeline that removes English/Latin text and other non-Arabic artifacts, normalizes content, and segments by section. The result is a Parquet-formatted dataset ready for direct loading via the `datasets`, `pandas`, or `polars` libraries.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
The original Hindawi catalog skews toward classical and literary Arabic; modern dialectal Arabic is underrepresented. Cleaning rules (e.g., Latin-text removal) may strip useful code-switched content or bibliographic references. Source does not document full provenance per row; buyers should validate empirically for downstream tasks. License terms for individual Hindawi works should be verified per-book if used commercially. The source describes free-access books and research/educational use of this derivative, but does not provide an unambiguous redistribution license.
Sample structure score: 92.9 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 42.9 / 50 | 60 of 70 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 60 of 60 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| text | 0 / 10 | string | 0 / 10 |
| book_title | 0 / 10 | string | 0 / 10 |
| author | 0 / 10 | string | 0 / 10 |
| category | 0 / 10 | string | 0 / 10 |
| section_title | 0 / 10 | string | 0 / 10 |
| chars | 0 / 10 | number | 0 / 10 |
| book_id | 10 / 10 | unknown | 0 / 0 |
About this data
Cleaned, section-level Arabic text from Hindawi.org books spanning literature, philosophy, history, and science, prepared for Arabic NLP training and research.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py d724d298-8c40-4151-ba15-463f60d56c46 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| text | VARCHAR | Cleaned Arabic text content of a book section |
| book_title | VARCHAR | Title of the source book |
| author | VARCHAR | Name of the book's author |
| category | VARCHAR | Topical category (literature, philosophy, history, science, psychology, etc.) |
| section_title | VARCHAR | Section heading or identifier within the book |
| chars | BIGINT | Character count of the section text |
| book_id | VARCHAR | Unique identifier for the source book |
Sample Data
Preview a sample of the data before downloading.
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Hindawi Arabic Books Section-L" })
// Found: d724d298-8c40-4151-ba15-463f60d56c46
get_download_url({ dataset_id: "d724d298-8c40-4151-ba15-463f60d56c46" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/d724d298-8c40-4151-ba15-463f60d56c46/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"