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Datasets:
nidhipandya
/
boundarybench

Tasks:
Tabular Classification
Modalities:
Tabular
Text
Geospatial
Formats:
parquet
Languages:
English
Size:
1K - 10K
Tags:
geospatial
gis
benchmark
boundaries
coordinates
uncertainty
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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metadata
license: cc-by-4.0
task_categories:
  - tabular-classification
language:
  - en
tags:
  - geospatial
  - gis
  - benchmark
  - boundaries
  - coordinates
  - uncertainty
  - spatial-analysis
  - llm-evaluation
pretty_name: BoundaryBench v1
size_categories:
  - 10K<n<100K

BoundaryBench

A National Benchmark for Geographic Boundary Resolution with Calibrated Uncertainty

DOI

DOI: 10.5281/zenodo.18090588

Dataset Summary

BoundaryBench is a benchmark dataset of 13,000 synthetic coordinate queries across 50 U.S. states plus D.C., designed to evaluate geographic boundary resolution systems. Points are stratified by distance-to-boundary difficulty tiers and complex polygon geometries.

  • Points: 13,000
  • Layers: county, ZCTA, tract
  • Difficulties: easy, medium, hard, boundary, edge
  • Version: v1.0.0
  • License: CC-BY-4.0
  • DOI: 10.5281/zenodo.18090588

Independent research; not endorsed by any organization.

How to Load 

from datasets import load_dataset

# Load the dataset
ds = load_dataset("nidhipandya/boundarybench")

# Or load parquet files directly
import pandas as pd
df = pd.read_parquet("hf://datasets/nidhipandya/boundarybench/data/boundarybench_v1.parquet")

print(f"Total points: {len(df)}")
print(df.head())

Data Fields

Field Type Description
lat float Latitude (EPSG:4269 / NAD83)
lon float Longitude (EPSG:4269 / NAD83)
layer string Administrative layer: county, zcta, or tract
label_id string Ground-truth region identifier
difficulty string One of: easy, medium, hard, boundary, edge
dist_to_boundary_m float Distance to nearest boundary in meters
state_fips string State FIPS code
split string Dataset split: train, dev, or test

Difficulty Stratification

Difficulty Distance Range Count
easy ≥500m 4,550
medium 100-500m 3,250
hard 10-100m 3,250
boundary 0-10m 1,300
edge 10-100m 650

Versioning

Citation 

@dataset{pandya2025boundarybench,
  title={BoundaryBench: Evaluating Geographic Boundary Resolution with Calibrated Uncertainty},
  author={Pandya, Nidhi},
  year={2025},
  doi={10.5281/zenodo.18090588},
  url={https://doi.org/10.5281/zenodo.18090588},
  license={CC-BY-4.0}
}

License

CC-BY-4.0

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