Welcome to the CamHD Compute Engine (CCE). The CCE is a computational platform that allows users to investigate, process, and visualize data from the OOI CamHD camera system. CamHD is currently located in the ASHES hydrothermal vent field on Axial Seamount, and collects approximately 100 gigabytes of data per day during normal operations. The official CamHD Raw Data Archive currently houses over 80 terabytes of data, making it difficult to download these data for analysis. The CCE allows users to work on a large subset of the CamHD data remotely without downloading raw data.
Currently the main component of the CCE is a JupyterHub server with a large subset of the CamHD data on local storage. The current CamHD dataset includes all of the data from the first camera deployment, from November 2015 to July 2016, and is about 25 TB in size. The JupyterHub server currently has several kernels available, including Python 3.6, Python 2.7, Google Go, and a custom PyCamHD kernel for working with the PyCamHD module. Users also have the option of installing custom kernels.
To obtain an account on the system, first make sure you have a GitHub account, which is how users authenticate. Next, send an email to email@example.com with your GitHub user name to have it whitelisted. Finally, go to the CamHD JupyterHub to log in. If you are new to Jupyter, you may want to explore this introduction to the platform.
Several example notebooks are available on GitHub. You can clone the example repository into your home directory using the Jupyter terminal window to get a working copy of the examples and adapt them for your research. See the instructions in the examples repository for more information.