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Description
A dataset for the NariSafe ML project, a prototype for women's safety risk-awareness. It combines city-level crime statistics with OpenStreetMap-derived urban infrastructure and engineered contextual features to classify locations into low, medium, or high risk. The dataset was created by avnisinghal001 and last updated on June 12, 2026.
Use Cases
Train risk classification models based on combined crime statistics and urban features.
Analyze correlations between urban infrastructure and perceived safety levels.
Develop location-based safety applications using latitude and longitude coordinates.
Benchmark geospatial feature engineering techniques for public safety datasets.
Strengths
Integrates multiple data sources: crime statistics, OpenStreetMap infrastructure, and engineered contextual features.
Includes explicit geospatial location columns: city, latitude, and longitude.
Provides a clear classification target with three risk levels: low, medium, high.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count, file size, and license information are unknown, which may limit suitability assessment.
Freshness should be verified as the last update timestamp is in the future (2026-06-12).
Provenance
Source
huggingface user avnisinghal001
Collection Method
Combines public crime statistics and OpenStreetMap-derived features.
Freshness
Last updated 2026-06-12 07:51:58
Geography
City-level, specific cities unknown.
License is unknown; terms of use must be verified before application.