---
language:
- en
tags:
- gis
- geospatial
license: mit
size_categories:
- 100K<n<1M
---
# govgis_nov2023

🤖 This README was written by GPT-4. 🤖

`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.

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.

This repo contains the [very messy] notebooks with the code used to compile the data and save it in parquet format.

## Overview

- Content: Includes three primary files: servers.parquet, services.parquet, and layers.parquet, offering detailed insights into numerous GIS servers and layers.
- 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.
- Format: Data is stored in Parquet format, facilitating efficient storage and quick access.
- 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.

## Data Collection

- 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.
- 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.
- Verification: While data integrity was a focus, the dataset was not subjected to extensive cleaning, preserving the raw and detailed nature of the information.

## Data Processing
- Data Cleaning: Minimal cleaning was conducted to maintain the dataset's comprehensive and raw nature, allowing users to filter and process data as needed.
- Data Transformation: Collected data was standardized and converted into Parquet format for ease of use and accessibility.

## Use Cases
The `govgis_nov2023` dataset can be utilized for:

- Educational and Research Purposes: A valuable resource for GIS students, educators, and researchers.
- Geospatial Data Analysis: Ideal for analysts and data scientists for conducting extensive geospatial analyses.
- GIS Application Development: Useful for developers in building or enhancing GIS-related applications.
- Language Model Integration: The dataset can be used to train or evaluate language models for generating descriptions or summaries of GIS data.

## Conclusion

- Creation: This dataset was created using the restgdf library, emphasizing the potential of open-source contributions in the GIS field.
- 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.