In today's rapidly evolving AI technology, we are constantly exploring ways to make AI process various types of data more efficiently. Currently, JSON is the most mainstream data format, but its redundancy leads to high token consumption when interacting with AI. To address this issue, a new data format called TOON has been designed to replace JSON in interactions with LLMs, reducing token consumption.
TOON GitHub: https://github.com/toon-format/toon
Demo Website: https://toonformat.dev/
A few days ago, while working on a GIS dashboard development, I encountered a highly peculiar issue: the map worked perfectly in the development environment but failed to display in the production environment. After a thorough investigation, I finally discovered that the GeoJSON data in the production environment was problematic. The data team might have manually edited and accidentally deleted some content during the GeoJSON export process, resulting in incomplete data. Since no comprehensive validation was performed beforehand, this caused the map to fail to load.
After identifying the problem, I decided to create a validation tool to prevent similar issues in the future. I tested several methods available online and have summarized a few reliable ones to share with you. The core idea is: Attempt to convert each GeoJSON file into an ArcGIS format (such as a feature class). If the conversion is successful, the file is considered valid; if it fails, capture the error and log it.
This method leverages the error handling mechanism of geoprocessing tools but requires manual setup.
First, place all the GeoJSON files you need to check in the same folder. Then, open the Geoprocessing pane (Analysis > Tools), search for and find the JSON To Features tool. This official tool for converting GeoJSON is strict with format requirements, making it very suitable for checking validity. In the tool interface, click the folder icon next to the Input JSON parameter. Locate the GeoJSON folder and select multiple files (hold Ctrl or Shift keys). Finally, set an output location and click Run.
Building upon our previous sharing of district/county-level administrative division data, we now provide the 2024 updated version sourced from China's official platform. This dataset addresses limitations in earlier versions (e.g., data gaps, insufficient detail) while maintaining cartographic compliance.
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