Update README.md

README.md

@@ -1,8 +1,8 @@
-````markdown
 ---
 language:
 - en
 pretty_name: Global Fire Hydrants Dataset
+license: cc-by-4.0
 tags:
 - geospatial
 - computer-vision
@@ -12,27 +12,35 @@ tags:
 - fire-hydrants
 - open-data
 - world-models
-license: cc-by-4.0
+- mapillary
 task_categories:
 - image-classification
 - object-detection
 size_categories:
 - 10K<n<100K
+annotations_creators:
+- machine-generated
+language_creators:
+- other
+multilinguality:
+- monolingual
+source_datasets:
+- original
 ---
 
 # Global Fire Hydrants Dataset
 
-A geotagged dataset of **14.2K fire hydrants** from around the world, released by **Outerview**, a research lab focused on building world models.
+The **Global Fire Hydrants Dataset** is a geotagged dataset of **14.2K fire hydrants** from around the world, released by **Outerview**, a research lab focused on building world models.
 
-At Outerview, our mission is to **organize the world’s physical information and make it accessible and usable**. This dataset is part of that effort: transforming real-world infrastructure into structured, machine-readable data that can support research, modeling, and physical-world intelligence.
+At Outerview, our mission is to **organize the world’s physical information and make it accessible and usable**. This dataset is part of that effort: transforming physical-world infrastructure into structured, machine-readable data for research, modeling, and real-world intelligence.
 
-## Overview
+## Dataset Description
 
-The **Global Fire Hydrants Dataset** contains **14,200 examples** of fire hydrants with associated geographic and image metadata.
+This dataset contains **14,200 examples** of fire hydrants with geographic and image metadata.
 
 Each entry is centered on a single real-world physical feature: a **fire hydrant**.
 
-This dataset is designed for work in:
+It is designed for:
 
 - computer vision
 - geospatial machine learning
@@ -41,23 +49,21 @@ This dataset is designed for work in:
 - multimodal retrieval
 - physical-world search and indexing
 
-It is a focused, single-feature dataset built for researchers, developers, and teams working on systems that need to understand the physical world.
-
-## Data sources and processing
+## Data Source and Processing
 
 The underlying imagery in this dataset is sourced from **Mapillary**.
 
-Dataset computation, extraction, and structuring were performed using the **Outerview API**, which is designed to help index and organize physical-world information at scale.
+The dataset was computed, extracted, and structured using the **Outerview API**, which is designed to help index and organize physical-world information at scale.
 
-## Why this dataset exists
+## Why This Dataset Exists
 
 Most of the world’s physical infrastructure is still difficult for machines to access and reason about.
 
-Fire hydrants are a useful example: they are common, spatially distributed, visually diverse, and operationally important, yet high-quality open datasets for them remain limited.
+Fire hydrants are a strong example of this problem: they are common, geographically distributed, visually diverse, and operationally important, yet clean open datasets for them remain limited.
 
 We created this dataset to help make physical infrastructure more searchable, more usable, and easier to work with in machine learning and geospatial systems.
 
-## What’s included
+## What’s Included
 
 This release contains **14.2K fire hydrant records** with metadata fields such as:
 
@@ -71,7 +77,7 @@ This release contains **14.2K fire hydrant records** with metadata fields such a
 
 Images are included as part of the dataset release assets.
 
-## Dataset structure
+## Dataset Structure
 
 Typical columns include:
 
@@ -83,68 +89,52 @@ Typical columns include:
 - `region`
 - `filename`
 
-Example:
-
-```json
-{
-  "id": "8d1c2b7a",
-  "latitude": 40.7128,
-  "longitude": -74.0060,
-  "source": "Mapillary",
-  "name": "Fire Hydrant",
-  "region": "New York, United States",
-  "filename": "fire_hydrant_00001.jpg"
-}
-````
-
-Update this section if your final schema differs slightly from the release.
-
-## Use cases
+## Uses
 
 This dataset can be used for:
 
-* fire hydrant classification
-* object detection and localization
-* infrastructure mapping
-* geospatial indexing
-* physical-world retrieval systems
-* training and evaluating world models
-* civic infrastructure research
-* real-world AI prototypes
+- fire hydrant classification
+- object detection and localization
+- infrastructure mapping
+- geospatial indexing
+- physical-world retrieval systems
+- training and evaluating world models
+- civic infrastructure research
+- real-world AI prototypes
 
 ## Coverage
 
-* **Feature type:** Fire hydrants
-* **Count:** 14.2K
-* **Scope:** Global
-* **Modality:** Street-level imagery + geospatial metadata
+- **Feature type:** Fire hydrants
+- **Count:** 14.2K
+- **Scope:** Global
+- **Modality:** Street-level imagery with geospatial metadata
 
-Coverage is not uniform across all countries or regions. The dataset should be understood as a research and development resource rather than a complete inventory of all fire hydrants worldwide.
+Coverage is not uniform across all countries or regions. This dataset should be treated as a research and development resource rather than a complete inventory of all fire hydrants worldwide.
 
 ## Limitations
 
-* Geographic coverage is uneven
-* Image quality and capture conditions vary
-* Some hydrants may be partially occluded, distant, blurred, or difficult to identify
-* The dataset reflects available imagery and collection coverage, not complete ground truth
-* Presence in the dataset does not imply full regional completeness
+- Geographic coverage is uneven
+- Image quality and capture conditions vary
+- Some hydrants may be partially occluded, distant, blurred, or difficult to identify
+- The dataset reflects available imagery and collection coverage, not complete ground truth
+- Presence in the dataset does not imply full regional completeness
 
-## Recommended uses
+## Recommended Uses
 
-Recommended uses:
+Recommended for:
 
-* research
-* model training
-* evaluation
-* geospatial analysis
-* infrastructure discovery
-* real-world retrieval and indexing workflows
+- research
+- model training
+- evaluation
+- geospatial analysis
+- infrastructure discovery
+- retrieval and indexing workflows
 
 Not recommended for:
 
-* safety-critical decisions without independent verification
-* emergency response use without validation against authoritative sources
-* claims of complete hydrant coverage for any city or country
+- safety-critical decisions without independent verification
+- emergency response use without validation against authoritative sources
+- claims of complete hydrant coverage for any city or country
 
 ## About Outerview
 
@@ -158,14 +148,12 @@ We believe the physical world should be as searchable and understandable as the
 
 If you use this dataset, please cite:
 
-```bibtex
 @dataset{outerview_global_fire_hydrants,
   title={Global Fire Hydrants Dataset},
   author={Outerview},
   year={2026},
   publisher={Hugging Face}
 }
-```
 
 ## License
 
@@ -175,11 +163,8 @@ This dataset is released under the **CC-BY-4.0** license.
 
 For larger datasets, research collaborations, or access to broader physical-world data infrastructure, visit **Outerview**.
 
-## Future releases
+## Future Releases
 
 This dataset is part of a broader effort by Outerview to publish structured datasets of physical-world features, infrastructure, and objects for training and evaluating world models.
 
-Future releases will expand into additional categories, geographies, and scales.
-
-```
-```
+Future releases will expand into additional categories, geographies, and scales.