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--- |
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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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license: mit |
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size_categories: |
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- 100K<n<1M |
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--- |
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# govgis_nov2023 |
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🤖 This README was written by GPT-4. 🤖 |
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`govgis_nov2023` is an extensive compilation of metadata, documenting geospatial data from known government servers as of November 15 2023. This should provide a rich resource for GIS analysis, research, and application development. |
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These datasets contain data from various Federal, State, County, and City ArcGIS Servers listed by Joseph Elfelt of [Mapping Support](https://mappingsupport.com). It serves as a unique snapshot capturing the state of these servers in November 2023. |
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This repo contains the [very messy] notebooks with the code used to compile the data and save it in parquet format. |
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## Overview |
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- Content: Includes three primary files: servers.parquet, services.parquet, and layers.parquet, offering detailed insights into numerous GIS servers and layers. |
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- Size and Scope: The dataset covers data from 1684 servers, detailing almost a million individual layers with extensive metadata including field information for feature layers, cell size for raster layers, etc. |
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- Format: Data is stored in Parquet format, facilitating efficient storage and quick access. |
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- Status: This is a static snapshot and not actively maintained like Joseph Elfelt’s ongoing listings. However, this foundation may evolve into a maintained index. |
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## Data Collection |
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- Tools & Libraries Used: Data was collected using the [`restgdf`](https://github.com/joshuasundance-swca/restgdf) library, designed for efficient and asynchronous interaction with ArcGIS servers. |
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- Process: The dataset was created by scraping information from a wide range of ArcGIS servers, focusing on capturing a comprehensive and detailed snapshot as of November 2023. |
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- Verification: While data integrity was a focus, the dataset was not subjected to extensive cleaning, preserving the raw and detailed nature of the information. |
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## Data Processing |
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- Data Cleaning: Minimal cleaning was conducted to maintain the dataset's comprehensive and raw nature, allowing users to filter and process data as needed. |
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- Data Transformation: Collected data was standardized and converted into Parquet format for ease of use and accessibility. |
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## Use Cases |
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The `govgis_nov2023` dataset can be utilized for: |
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- Educational and Research Purposes: A valuable resource for GIS students, educators, and researchers. |
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- Geospatial Data Analysis: Ideal for analysts and data scientists for conducting extensive geospatial analyses. |
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- GIS Application Development: Useful for developers in building or enhancing GIS-related applications. |
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- Language Model Integration: The dataset can be used to train or evaluate language models for generating descriptions or summaries of GIS data. |
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## Conclusion |
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- Creation: This dataset was created using the restgdf library, emphasizing the potential of open-source contributions in the GIS field. |
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- Data Source: The dataset comprises data from publicly accessible ArcGIS servers. The dataset creator has no affiliation with Joseph Elfelt, MappingSupport.com, or the servers' respective owners. |
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