electricsheepasia/asia-aviation-ourairports-oman
Airports in Oman Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-03-13 Abstract List of airports in Oman, with latitude and longitude. Unverified community data from http://ourairports.com/countries/OM/ Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-13. Geographic scope: OMN. Curated into ML-ready Parquet format by Electric Sheep Africa. Dataset… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-aviation-ourairports-oman.
Airports in Oman
Publisher: OurAirports · Source: HDX · License: Public Domain · Updated: 2026-03-13
Abstract
List of airports in Oman, with latitude and longitude. Unverified community data from http://ourairports.com/countries/OM/
Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-13. Geographic scope: OMN.
Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).
Dataset Characteristics
Variables
Geographic — type (smallairport, heliport, mediumairport), latitude_deg (range 16.7011–26.3678), longitude_deg (range 53.0979–59.7879), country_name (Oman, #country +name), iso_country (OM, #country +code +iso2) and 4 others.
Temporal — last_updated.
Outcome / Measurement — score (range 0.0–1275.0).
Identifier / Metadata — id (range 5225.0–605712.0), ident (#meta +code, OOMS, OOSA), name (#loc +airport +name, Muscat International Airport, Salalah International Airport), gps_code, iata_code and 2 others.
Other — elevation_ft (range 10.0–6500.0), continent (AS, #region +continent +code), scheduled_service (range 0.0–1.0), wikipedia_link.
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/asia-aviation-ourairports-oman")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()Schema
Numeric Summary
Curation
Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snakecase. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 4 column(s) with >80% missing values were removed: `icaocode, localcode`, `homelink, keywords`. 7 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). 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 OurAirports and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling:
gps_code,iata_code,wikipedia_link. - Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.
Citation
@dataset{hdx_asia_aviation_ourairports_oman,
title = {Airports in Oman},
author = {OurAirports},
year = {2026},
url = {https://data.humdata.org/dataset/ourairports-omn},
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.
