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--- |
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license: mit |
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language: |
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- en |
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tags: |
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- gis |
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- geospatial |
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pretty_name: govgis_nov2023-slim-spatial |
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size_categories: |
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- 100K<n<1M |
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--- |
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# govgis_nov2023-slim-spatial |
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🤖 This README was written by [`HuggingFaceH4/zephyr-7b-beta`](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta). 🤖 |
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Introducing the govgis_nov2023-slim-spatial dataset, a carefully curated and georeferenced subset of the extensive [govgis_nov2023](https://huggingface.co/datasets/joshuasundance/govgis_nov2023) collection. This dataset stands out for its focus on geospatial data analysis, enriched with vector embeddings. While we have only explored a portion of this vast collection, the variety and richness of the content encountered have been remarkable, making it challenging to fully capture the dataset's breadth in a brief overview. |
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## Overview |
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The govgis_nov2023-slim-spatial dataset condenses key elements from the larger govgis_nov2023 collection into a more manageable format. It offers a glimpse into an extensive range of geospatial data types, all augmented with vector embeddings using [`BAAI/bge-large-en-v1.5`](https://huggingface.co/BAAI/bge-large-en-v1.5). Our exploration has revealed a staggering variety in the data, suggesting vast potential applications. |
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Key Features: |
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- **Diverse Geospatial Data Types:** The dataset includes samples of data like ecological data, census data, administrative boundaries, transportation networks, and land use maps, representing just a fraction of what's available. |
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- **Advanced Vector Search Capabilities:** Augmented with vector embeddings using [`BAAI/bge-large-en-v1.5`](https://huggingface.co/BAAI/bge-large-en-v1.5) for sophisticated content discovery. |
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## Dataset Files |
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The dataset comprises two distinct files: |
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1. **`govgis_nov2023_slim_spatial.geoparquet`** This file offers core georeferenced spatial data, suitable for a broad range of analysis needs. |
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2. **`govgis_nov2023_slim_spatial_embs.geoparquet`:** A more comprehensive file with detailed vector embeddings, catering to more in-depth analytical demands. |
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This two-tiered approach allows users to tailor their engagement with the dataset based on their specific requirements. |
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## Benefits: |
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- **Selective Accessibility:** The dataset provides an accessible entry point to a seemingly endless variety of spatial data. |
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- **Efficient yet Comprehensive:** It distills a vast array of data into a more practical format without losing the essence of its diversity. |
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- **Untapped Application Potential:** The examples we provide are merely starting points; the dataset's true scope is far more extensive and varied. |
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- **Enhanced Analytical Depth:** Vector embeddings from [`BAAI/bge-large-en-v1.5`](https://huggingface.co/BAAI/bge-large-en-v1.5) offer advanced data analysis capabilities. |
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## Use Cases: |
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Given the sheer variety of data we've glimpsed, the dataset is poised to serve a myriad of applications, far beyond the few examples we can confidently cite. It's designed to be adaptable to diverse analytical pursuits across different fields. |
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# Conclusion: |
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The govgis_nov2023-slim-spatial dataset is a thoughtfully distilled, georeferenced, and vector-embedded version of its more extensive counterpart. Our limited exploration has revealed an astonishing variety of data, hinting at a much broader scope of potential applications than we can definitively describe. This dual-file dataset is crafted to meet a wide spectrum of spatial data analysis needs, from the straightforward to the highly specialized, accommodating the extensive possibilities that lie within the realm of geospatial data. |
