big-sea-data

README.md

𓆟 Description

This is a web-based visualiser that scrapes data from the Ocean Networks Canada API. It uses the latitude, longitude, and depth of various underwater devices to move imagined deep sea creatures around an enivronment. It serves as a simulacrum of a marine ecology that is largely understudied.

𓆟 Directory

Within this repository you can find:

the web pages that host all tests, research, evaluations

𓆟 tests/
• Python files for graphs and web scrapers
• output CSV files from those scrapers
• JavaScript files I sent those outputs to

𓆟 img/
• code snippets and various visual outputs
• research reference images
• slides from my initial idea

𓆟 docs/
• individual test pages with screenshots, running sketches and evaluations

𓆟 addons/
• my JavaScript code
• p5 and JQuery requirements

𓆟 Installation & Use

The documentation, research, experiments, and final outcome are all currently hosted on the Creative Computing Institute Server [CCI], which I will update regularly. If you choose to download the project, you only need "underwater-scraper.py", "uw-positions.py" and "incorporated.js". You will have to go through both Python files and change the file paths to ones correct for your system.

𓆟 Future Features

Interactivity

Marine snow

3D camera view

𓆟 Credits

The quick start guide for developers on the NOAA API.

The documentation on the Oceans 3.0 Public API on Ocean Networks Canada.

John Burkardt, for henon_heiles_ode.py.

_tanya_sri_ for this GeeksForGeeks tutorial.

Daniel Shiffman, for his Lorenz attractor tutorial.

Kantel-Chaos-Team, for their Butterfly Curve python code.

𓆟 License

Olivia McCallum, deep sea crawler, 16.06.2023. Copyleft with a difference: This is a collective work, you are invited to copy, distribute, and modify it under the terms of the CC4r [https://constantvzw.org/wefts/cc4r.en.html].