Standardize Electric Sheep Africa dataset card

README.md

@@ -1,66 +1,145 @@
 ---
 license: cc-by-4.0
-task_categories:
-- tabular-classification
 language:
 - en
-tags:
-- laboratory
-- LIS
-- information-systems
-- digital-health
-- data-quality
-- synthetic
-- sub-saharan-africa
-pretty_name: Laboratory Information Systems
+task_categories:
+- tabular-classification
+- tabular-regression
+multilinguality: monolingual
 size_categories:
 - 10K<n<100K
-configs:
-- config_name: lis_implemented
-  data_files: data/lis_lis_implemented.csv
-- config_name: partial_lis
-  data_files: data/lis_partial_lis.csv
-  default: true
-- config_name: no_lis
-  data_files: data/lis_no_lis.csv
-data_type: synthetic
+tags:
+- "africa"
+- "electric-sheep-africa"
+- "open-data"
+- "metadata-backed"
+- "technology-digital"
+- "csv"
+- "tabular"
+- "text"
+- "laboratory"
+- "lis"
+- "information-systems"
+- "digital-health"
+- "data-quality"
+- "synthetic"
+- "sub-saharan-africa"
+- "digital"
+- "internet"
+pretty_name: "Laboratory Information Systems | Africa (Electric Sheep Africa metadata inventory)"
 ---
 
-> ⚠️ **Synthetic dataset** — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.
+# Laboratory Information Systems | Africa (Electric Sheep Africa metadata inventory)
+
+**Size category:** `10K<n<100K` - **Formats:** `csv` - **Sector:** technology_digital - *Engineered by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica)*
+
+![size](https://img.shields.io/badge/size-10K%3Cn%3C100K-blue)
+![sector](https://img.shields.io/badge/sector-technology_digital-green)
+![downloads](https://img.shields.io/badge/HF_downloads-143-orange)
+![license](https://img.shields.io/badge/license-cc--by--4.0-lightgrey)
 
-# Laboratory Information Systems
+## TL;DR
 
-## Abstract
+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.
 
-Synthetic dataset modeling laboratory information system adoption across three SSA scenarios. Captures LIS availability, type (OpenELIS/BLIS/commercial), infrastructure (power/internet), functionality (barcode/auto-entry/SMS), data quality, DHIS2 reporting, security, and workforce training. Parameterized from SSA LIS implementation research.
+## What This Dataset Covers
 
-## Parameterization Evidence
+Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
 
-| Parameter | Value | Source | Year |
-| --- | --- | --- | --- |
-| LIS adoption SSA | <15% of labs | Nguyen et al. BMC Med Inform | 2018 |
-| Paper-based systems | >80% of SSA labs | Nguyen et al. | 2018 |
-| Internet connectivity | <30% health facilities | Were et al. JAMIA | 2015 |
-| Paper record incomplete | 30-50% | Sarkinfada et al. Afr J Lab Med | 2012 |
+Dataset context from the existing Hugging Face card: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. Laboratory Information Systems Abstract Synthetic dataset modeling laboratory information system adoption across three SSA scenarios. Captures LIS availability, type (OpenELIS/BLIS/commercial), infrastructure (power/internet), functionality (barcode/auto-entry/SMS), data quality, DHIS2 reporting, security, and workforce… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all.
 
-## Validation
+## Dataset Profile
 
-![Validation Report](validation_report.png)
+| Field | Value |
+|---|---|
+| Hugging Face repo | [`electricsheepafrica/africa-synth-laboratory-information-systems-all`](https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all) |
+| Sector | technology_digital |
+| Topic tags | laboratory, LIS, information-systems, digital-health, data-quality, synthetic, sub-saharan-africa |
+| Modalities | `tabular`, `text` |
+| Formats | `csv` |
+| Size category | `10K<n<100K` |
+| Countries | Africa-wide or source-defined African coverage |
+| ISO3 coverage | `not declared` |
+| Last modified on HF | `2026-04-14 22:43:02+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/laboratory-information-systems", name="partial_lis")
-df = ds['train'].to_pandas()
+
+ds = load_dataset("electricsheepafrica/africa-synth-laboratory-information-systems-all")
+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())
 ```
 
-## References
+## 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: country, upstream_publisher.
+- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
+
+## Source And Provenance
 
-1. Nguyen TT et al. (2018). LIS low-resource. *BMC Med Inform Decis Mak*. DOI: 10.1186/s12911-018-0693-x
-2. Were MC et al. (2015). EHR in SSA. *JAMIA*. DOI: 10.1093/jamia/ocu023
-3. Sarkinfada F et al. (2012). Lab informatics Nigeria. *Afr J Lab Med*. DOI: 10.4102/ajlm.v1i1.18
+- **Source context:** Electric Sheep Africa metadata inventory
+- **Publisher/source attribution:** Public dataset metadata
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Hugging Face URL:** [https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all](https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all)
+- **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_synth_laboratory_information_systems_all_2026,
+  title        = {Laboratory Information Systems | Africa (Electric Sheep Africa metadata inventory)},
+  author       = {Public dataset metadata},
+  year         = {2026},
+  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all},
+  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
+  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-laboratory-information-systems-all}}
+}
+```
 
 ## License
 
-CC-BY-4.0
+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`.