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Improve dataset title for discoverability

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  1. README.md +9 -5
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@@ -19,9 +19,10 @@ libraries:
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  - datasets
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  size_categories:
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  - 10K<n<100K
 
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  ---
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- # Road Damage — 2023,2024,2025
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  This dataset contains geolocated observations selected for the semantic query “Road Damage.” The records were retrieved because their source text, visual context, or metadata matched the query; this is a discovery-oriented collection rather than a complete administrative inventory. It is useful for exploratory mapping, visual search evaluation, geospatial research, and building retrieval or monitoring workflows around road damage. The release contains 25,473 records from 2023, 2024, 2025; matched-observation details are preserved in `properties`, with associated media available through `media_url` when supplied. Prepared and distributed by EmbedEarth from Mapillary and iNaturalist.
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@@ -56,11 +57,14 @@ The `properties` column is a JSON-encoded object containing semantic retrieval a
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  | `owner / publisher` | Source owner or publisher when supplied. |
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  | `year / month / season / time_of_day` | Temporal context derived from the observation when supplied. |
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- ## Files
 
 
 
 
 
 
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- - [Parquet](https://huggingface.co/datasets/embedearth/road-damage/resolve/main/data.parquet)
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- - [GeoJSON](https://huggingface.co/datasets/embedearth/road-damage/resolve/main/data.geojson)
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- - [CSV](https://huggingface.co/datasets/embedearth/road-damage/resolve/main/data.csv)
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  ## Data source and attribution
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  Prepared and distributed by [EmbedEarth](https://embed.earth).
 
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  - datasets
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  size_categories:
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  - 10K<n<100K
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+ pretty_name: "Road Damage Dataset - Global Road Condition Observations - EmbedEarth"
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  ---
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+ # Road Damage Dataset - Global Road Condition Observations - EmbedEarth
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  This dataset contains geolocated observations selected for the semantic query “Road Damage.” The records were retrieved because their source text, visual context, or metadata matched the query; this is a discovery-oriented collection rather than a complete administrative inventory. It is useful for exploratory mapping, visual search evaluation, geospatial research, and building retrieval or monitoring workflows around road damage. The release contains 25,473 records from 2023, 2024, 2025; matched-observation details are preserved in `properties`, with associated media available through `media_url` when supplied. Prepared and distributed by EmbedEarth from Mapillary and iNaturalist.
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  | `owner / publisher` | Source owner or publisher when supplied. |
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  | `year / month / season / time_of_day` | Temporal context derived from the observation when supplied. |
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+ ## Downloads
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+
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+ - [Parquet](https://s3.us-east-005.backblazeb2.com/open-datasets/road-damage/2023,2024,2025/79ef0a0f-de2b-4454-a2fc-139ebbad222a/data.parquet)
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+ - [GeoJSON](https://s3.us-east-005.backblazeb2.com/open-datasets/road-damage/2023,2024,2025/79ef0a0f-de2b-4454-a2fc-139ebbad222a/data.geojson)
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+ - [CSV](https://s3.us-east-005.backblazeb2.com/open-datasets/road-damage/2023,2024,2025/79ef0a0f-de2b-4454-a2fc-139ebbad222a/data.csv)
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+ - [Manifest](https://s3.us-east-005.backblazeb2.com/open-datasets/road-damage/2023,2024,2025/79ef0a0f-de2b-4454-a2fc-139ebbad222a/manifest.json)
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+ - [Image archive](https://s3.us-east-005.backblazeb2.com/open-datasets/road-damage/2023,2024,2025/79ef0a0f-de2b-4454-a2fc-139ebbad222a/images.zip)
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  ## Data source and attribution
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  Prepared and distributed by [EmbedEarth](https://embed.earth).