Datasets:

electricsheepafrica
/

africa-unep-wdpca-bfa

@@ -1,185 +1,142 @@
 ---
-annotations_creators:
-- no-annotation
-language_creators:
-- found
 language:
 - en
-license: cc-by-4.0
-multilinguality:
-- monolingual
-size_categories:
-- n<1K
-source_datasets:
-- original
 task_categories:
 - tabular-regression
-task_ids: []
 tags:
-- africa
-- humanitarian
-- hdx
-- electric-sheep-africa
-- environment
-- geodata
-- bfa
-pretty_name: "Protected and Conserved Areas (WDPCA) in Burkina Faso"
-dataset_info:
-  splits:
-    - name: train
-      num_examples: 1
-    - name: test
-      num_examples: 0
----
-# Protected and Conserved Areas (WDPCA) in Burkina Faso
-**Publisher:** The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) · **Source:** [HDX](https://data.humdata.org/dataset/unep_wdpca_bfa) · **License:** `cc-by-igo` · **Updated:** 2026-03-19
 ---
-## Abstract
-The World Database on Protected and Conserved Areas (WDPCA) combines the formerly separate World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM). The WDPCA is the most comprehensive global database of marine and terrestrial protected areas and other effective area-based conservation measures, updated on a monthly basis, and is one of the key global biodiversity datasets being widely used by scientists, businesses, governments, international secretariats, and others to inform planning, policy decisions, and management.
-The WDPCA is part of the Protected Planet Initiative, a joint product of the UN Environment Programme and the International Union for Conservation of Nature (IUCN). The compilation and management of the WDPCA is carried out by the UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), in collaboration with governments and other stakeholders. Data and information on the world's protected and conserved areas compiled in the WDPCA is used for reporting on progress towards reaching Target 3 of the Kunming-Montreal Global Biodiversity Framework, which calls for 30% of the world’s land and waters to be effectively conserved by 2030.
-Additionally, the WDPCA is used for reporting to the UN to track progress towards the 2030 Sustainable Development Goals, tracking of core indicators of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), and providing information for other international assessments and reports including the Global Biodiversity Outlook. UNEP-WCMC and IUCN periodically release the Protected Planet Report on the status of the world's protected and conserved areas.
-Many platforms are incorporating the WDPCA to provide integrated information to diverse users, including businesses and governments, in a range of sectors. For example, the WDPCA is included in the Integrated Biodiversity Assessment Tool (IBAT), an innovative decision support tool that gives commercial users easy access to up-to-date information that allows them to identify biodiversity risks and opportunities within a project boundary.
-The reach of the WDPCA is further enhanced by the UN Biodiversity Lab as well as services developed by other parties, such as the Global Forest Watch and the Digital Observatory for Protected Areas, which provide decision makers with access to monitoring and alert systems that allow whole landscapes to be managed better. Together, these applications of the WDPCA demonstrate the growing value and significance of the Protected Planet initiative.
-Each row in this dataset represents individual-level records. Data was last updated on HDX on 2026-03-19. Geographic scope: **BFA**.
-*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*
----
-## Dataset Characteristics
-| | |
 |---|---|
-| **Domain** | Water, sanitation and hygiene (wash) |
-| **Unit of observation** | Individual-level records |
-| **Rows (total)** | 2 |
-| **Columns** | 35 (8 numeric, 27 categorical, 0 datetime) |
-| **Train split** | 1 rows |
-| **Test split** | 0 rows |
-| **Geographic scope** | BFA |
-| **Publisher** | The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) |
-| **HDX last updated** | 2026-03-19 |
----
-## Variables
-**Geographic** — `site_type` (PA), `desig_type` (International), `status_yr` (range 1986.0–2002.0), `gov_type`, `own_type` and 4 others.
-**Identifier / Metadata** — `objectid` (range 225.0–4830.0), `site_id` (range 12471.0–900732.0), `site_pid` (range 12471.0–900732.0), `name_eng` (Forêt classée de la mare aux hippopotames, W Region), `name` (Forêt classée de la mare aux hippopotames, "W" Region (Burkina Faso)) and 3 others.
-**Other** — `desig` (UNESCO-MAB Biosphere Reserve), `desig_eng` (UNESCO-MAB Biosphere Reserve), `iucn_cat` (Not Applicable), `int_crit` (Not Applicable), `realm` (Terrestrial) and 13 others.
----
-## Quick Start
 ```python
 from datasets import load_dataset
-ds    = load_dataset("electricsheepafrica/africa-unep-wdpca-bfa")
-train = ds["train"].to_pandas()
-test  = ds["test"].to_pandas()
-print(train.shape)
-train.head()
 ```
----
-## Schema
-| Column | Type | Null % | Range / Sample Values |
-|---|---|---|---|
-| `objectid` | int64 | 0.0% | 225.0 – 4830.0 (mean 2527.5) |
-| `site_id` | int64 | 0.0% | 12471.0 – 900732.0 (mean 456601.5) |
-| `site_pid` | int64 | 0.0% | 12471.0 – 900732.0 (mean 456601.5) |
-| `site_type` | object | 0.0% | PA |
-| `name_eng` | object | 0.0% | Forêt classée de la mare aux hippopotames, W Region |
-| `name` | object | 0.0% | Forêt classée de la mare aux hippopotames, "W" Region (Burkina Faso) |
-| `desig` | object | 0.0% | UNESCO-MAB Biosphere Reserve |
-| `desig_eng` | object | 0.0% | UNESCO-MAB Biosphere Reserve |
-| `desig_type` | object | 0.0% | International |
-| `iucn_cat` | object | 0.0% | Not Applicable |
-| `int_crit` | object | 0.0% | Not Applicable |
-| `realm` | object | 0.0% | Terrestrial |
-| `rep_m_area` | float64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
-| `rep_area` | float64 | 0.0% | 1860.0 – 3460.0 (mean 2660.0) |
-| `no_take` | object | 0.0% | Not Applicable |
-| `no_tk_area` | float64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
-| `status` | object | 0.0% |  |
-| `status_yr` | int64 | 0.0% | 1986.0 – 2002.0 (mean 1994.0) |
-| `restrict` | object | 0.0% |  |
-| `gov_type` | object | 0.0% |  |
-| `own_type` | object | 0.0% |  |
-| `mang_auth` | object | 0.0% |  |
-| `mang_plan` | object | 0.0% |  |
-| `cons_obj` | object | 0.0% |  |
-| `supp_info` | object | 0.0% |  |
-| `verif` | object | 0.0% |  |
-| `inlnd_wtrs` | object | 0.0% |  |
-| `metadataid` | int64 | 0.0% | 988.0 – 988.0 (mean 988.0) |
-| `prnt_iso3` | object | 0.0% |  |
-| `iso3` | object | 0.0% |  |
-| `govsubtype` | object | 0.0% |  |
-| `ownsubtype` | object | 0.0% |  |
-| `oecm_asmt` | object | 0.0% |  |
-| `esa_source` | object | 0.0% |  |
-| `esa_processed` | object | 0.0% |  |
----
-## Numeric Summary
-| Column | Min | Max | Mean | Median |
-|---|---|---|---|---|
-| `objectid` | 225.0 | 4830.0 | 2527.5 | 2527.5 |
-| `site_id` | 12471.0 | 900732.0 | 456601.5 | 456601.5 |
-| `site_pid` | 12471.0 | 900732.0 | 456601.5 | 456601.5 |
-| `rep_m_area` | 0.0 | 0.0 | 0.0 | 0.0 |
-| `rep_area` | 1860.0 | 3460.0 | 2660.0 | 2660.0 |
-| `no_tk_area` | 0.0 | 0.0 | 0.0 | 0.0 |
-| `status_yr` | 1986.0 | 2002.0 | 1994.0 | 1994.0 |
-| `metadataid` | 988.0 | 988.0 | 988.0 | 988.0 |
----
-## Curation
-Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.
----
-## Limitations
-- Data originates from The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) and has not been independently validated by ESA.
-- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
-- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/unep_wdpca_bfa) for the publisher's own methodology notes and caveats.
----
 ## Citation
 ```bibtex
-@dataset{hdx_africa_unep_wdpca_bfa,
-  title     = {Protected and Conserved Areas (WDPCA) in Burkina Faso},
-  author    = {The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC)},
-  year      = {2026},
-  url       = {https://data.humdata.org/dataset/unep_wdpca_bfa},
-  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
 }
 ```
 ---
-*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*

 ---
+license: cc-by-4.0
 language:
 - en
 task_categories:
+- tabular-classification
 - tabular-regression
+multilinguality: monolingual
+size_categories:
+- n<1K
 tags:
+- "africa"
+- "electric-sheep-africa"
+- "open-data"
+- "metadata-backed"
+- "climate-environment"
+- "parquet"
+- "tabular"
+- "text"
+- "humanitarian"
+- "hdx"
+- "environment"
+- "geodata"
+- "bfa"
+- "conservation"
+pretty_name: "Protected and Conserved Areas (WDPCA) in Burkina Faso | Africa (original)"
 ---
+# Protected and Conserved Areas (WDPCA) in Burkina Faso | Africa (original)
+**Size category:** `n<1K` - **Formats:** `parquet` - **Sector:** climate_environment - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+![size](https://img.shields.io/badge/size-n%3C1K-blue)
+![sector](https://img.shields.io/badge/sector-climate_environment-green)
+![downloads](https://img.shields.io/badge/HF_downloads-47-orange)
+![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)
+## TL;DR
+This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
+## What This Dataset Covers
+Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
+Dataset context from the existing Hugging Face card: Protected and Conserved Areas (WDPCA) in Burkina Faso Publisher: The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) · Source: HDX · License: cc-by-igo · Updated: 2026-03-19 Abstract The World Database on Protected and Conserved Areas (WDPCA) combines the formerly separate World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM). The WDPCA is the most comprehensive global database… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa.
+## Dataset Profile
+| Field | Value |
 |---|---|
+| Hugging Face repo | [`electricsheepafrica/africa-unep-wdpca-bfa`](https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa) |
+| Sector | climate_environment |
+| Topic tags | humanitarian, hdx, electric-sheep-africa, environment, geodata, bfa |
+| Modalities | `tabular`, `text` |
+| Formats | `parquet` |
+| Size category | `n<1K` |
+| Countries | Burkina Faso |
+| ISO3 coverage | `BFA` |
+| Last modified on HF | `2026-04-04 15:13:39+00:00` |
+| Inventory snapshot | `2026-07-16T16:00:34Z` |
+## How To Read This Dataset
+- Start from the repository files and the dataset viewer when available.
+- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
+- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
+- Preserve missing values until you have a defensible imputation rule.
+## Usage
 ```python
 from datasets import load_dataset
+ds = load_dataset("electricsheepafrica/africa-unep-wdpca-bfa")
+print(ds)
+split_name = next(iter(ds))
+table = ds[split_name]
+print(table.features)
+print(table[:3])
 ```
+### Convert To Pandas When Tabular
+```python
+from datasets import Dataset
+first_split = ds[next(iter(ds))]
+if isinstance(first_split, Dataset):
+    df = first_split.to_pandas()
+    print(df.head())
+```
+## Data Quality Notes
+- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
+- Exact schema, row counts, and source files should be inspected in the repository data files.
+- Metadata gaps from the inventory: upstream_publisher.
+- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
+## Source And Provenance
+- **Source context:** original
+- **Publisher/source attribution:** original
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa](https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa)
+- **Inventory retrieved at:** `2026-07-16T16:00:34Z`
+## Suggested Analyses
+- Inspect schema and missingness before modeling.
+- Profile variables by geography, time, and subgroup columns where present.
+- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
+- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
 ## Citation
 ```bibtex
+@misc{electric_sheep_africa_africa_unep_wdpca_bfa_2026,
+  title        = {Protected and Conserved Areas (WDPCA) in Burkina Faso | Africa (original)},
+  author       = {original},
+  year         = {2026},
+  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-unep-wdpca-bfa}}
 }
 ```
+## License
+Released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
+## About Electric Sheep Africa
+Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
 ---
+Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: `catalog/esa_metadata_inventory/master_metadata.jsonl`.