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This page has resources, links, and guides relating to the Mindat.org mineralogy database and its new application program interface (API). This API establishes many practical affordances to those working with mineralogical data. The context, improvements, and changes relating to Mindat and the API can be found in paper "OpenMindat" which is linked to in the first section below.
This is a community maintained repository and is not affiliated with any of the projects below. This GitHub repository does contain links to other resources and further resources, but this repository is not thoroughly cited yet.
Authors: Xiaogang Ma, Jolyon Ralph, Jiyin Zhang, Xiang Que, Anirudh Prabhu, Shaunna M. Morrison, Robert M. Hazen, Lesley Wyborn, Kerstin Lehnert
- Accessible at https://rmets.onlinelibrary.wiley.com/doi/10.1002/gdj3.204
- Open Access Paper; an inspiring research initiative!
- ⭐
Source: https://www.mindat.org/a/how_to_get_my_mindat_api_key
For those interested in using the API, there is an official tutorial on this webpage. As of April 10th 2024, the article has 3,125 views!
**A user may generate an API key from their Mindat user page or from their **
The specification for the API can be found at https://api.mindat.org/schema/redoc/ and is downloadable as a .YAML file. The Mindat API can be used with the R and Python packages as well as proprietary packages.
The Random Mineral and Random Locality search options run a PHP script that generates a pseudorandom query.
The current footprint of the total Mindat database is measurable in gigabytes. While it is lighter than having all of those geomaterials in a backback, there are still considerations of storage and data handling that must be undertaken.
The API for Mindat.org removes the need for web scraping. While you can use web-scraping methods on the Mindat.org website example of old web scraper, this method is now outdated.
It is important to make a distinction in the usage of the Mindat API: querying and downloading data from the Mindat website is not the same as data analytics and data science with the mineralogy data.
- Source: https://cran.r-project.org/web/packages/OpenMindat/index.html
- Author(s): Xiang Que [aut, cre], Xiaogang Ma [aut]
- "Allows access to the Mindat.org resources through the R programming language for data science activities."
- ⭐
- "This is a test version of the OpenMindat Python package, designed to facilitate querying and retrieving data on minerals and geomaterials from the Mindat API."
- An excellent resource with documentation.
- Author(s): Jiyin Zhang
- ⭐
🚧
The Julia Programming Language is capable of data science activities alongside or in parallel with Python and R.
There exists an R package that allows calls to the Julia lang from R (https://cran.r-project.org/web/packages/JuliaCall/readme/README.html).
There exists a Julia package that allows calls to Python package that may be interoperable with the Python Mindat package. The Julia package may be found at (https://juliahub.com/ui/Packages/General/PyCall).
🔡 There are many minerals and many mineral properties. Any large language model (LLM) to generate tokens in response to user text could, if connected to the internet, query the Mindat database for factual retrieval of geomaterial properties. If a user asks an LLM _"Is Sakuraiite a real mineral?"__, the LLM could call a simple function to the Mindat database to check. This kind of functionality could be built out through the Microsoft Semantic Kernel or Langchain.
🦀
🚧 Not all people interested in using the Mindat API are familar with programming languages. There are many great resources for folks to learn, however, the usecase of Mindat to .csv outputs is important. The fastest way right now to output .csv's is through R.
- Source: https://github.com/MisterSirCode/Mindat-Data-Collector
- Language: JavaScript
https://github.com/ChuBL/How-to-Use-Mindat-API
- Source: https://github.com/MisterSirCode/Mindat-Data-Collector
- Language: JavaScript
- "A simple python example for the (alpha) version of the API. Requires an API key "
- Source: https://github.com/jolyonralph/mindat_api_test
- Author(s): Jolyon Ralph
- Python Programming Language
- ""
- Source: https://github.com/MrHamel/mindat_api_test
- Author(s): Ryan Hamel
- Python Programming Language
- Unmaintained
- Source: https://github.com/MelorGloom/Crystal-Info-Scrapper
- PostgreSQL and Python
- https://www.earthdatascience.org/
- Free Earth Data Science Courses & Textbooks
- Learn scientific programming, reproducible open science workflows and data science today.
- Python and Earth Data Science
- Source: https://opengeology.org/
- An excellent collection of open source textbooks!
- Source(s): https://www.c82.net/mineralogy/
- "All 2,242 illustrations from James Sowerby’s compendium of knowledge about mineralogy in Great Britain and beyond, drawn 1802–1817 and arranged by color."
- Interactive website
Python is a programming language that is accessible and well-suited for data science. If you are new to computer programming, Python is an excellent choice.
- FreeCodeCamp.com has an interactive "Scientific Computing With Python" course.
- The 'Python IDLE' is a programming environment associated with the Python language.
Advancing into Analytics: From Excel to Python and R (O’Reilly) https://stringfestanalytics.com/book/
. Please create a pull request if you can correct, clairfy, or expand on the resources above. :)