Merge pull request #20 from oceanhackweek/eeholmes-book

Delete book/presentations directory

Author: eeholmes

book/logistics.md

@@ -1,59 +1,31 @@
-# What to Expect 
-
-The {{ hackweek }} will focus on applied, hands-on learning, with participants engaging in
-extended periods of small-group work. Our tutorials are designed to offer a broad
-snapshot of data science tools to support your applied investigations. Due to the
-relatively short duration of our events, we are not able to provide comprehensive,
-in-depth training in fundamental tools. Rather, our goal is to inform you about
-the types of tools we think are best suited to working with PACE datasets, with a focus
-on the Pangeo ecosystem of Python tools for big data geoscience.
-The details of implementation will be what you work out via peer-learning (helping each other) in
-your project group.
-
-## Typical Workflows and Tools
-
-Here are a few specific scenarios of how hackweek participants will engage
-with data science tools:
-
-* Connecting to a [Jupyter Notebook](https://jupyter.org/) environment and
-  accessing content for tutorial training.
-* Accessing cloud-hosted remote sensing data using earthaccess and plotting it
- using matplotlib.
-* Exploring multi-dimensional remote sensing data using xarray.
-* Opening CSV tabular data in Pandas and run tools to conduct satellite matchups.
-* Modifying code, committing it to Git and pushing changes to GitHub, for
-  others on your team to view and edit.
-* Exploring methods for high performance computing such as using Dask and parallelization
-* Preparing datasets for machine learning tools, including PyTorch and TensorFlow for neural networks
-
-These are examples of the types of activities we will do at the Fish-PACE hackweek in a
-collaborative setting. Be aware that most of the project work will be within self-organized project
-teams. Much of the hackweek will be spent running code (via notebooks),
-writing code and talking about code. The mentors and organizers will provide links to tutorials and 
-help trouble-shoot code, but much of the learning comes from working on a project together.
-
-All tutorials will be in Python using the Pangeo ecosystem of tools for computing in the earth sciences.
-For participants wishing to brush up on their skills before
-the event, we recommend viewing the resources as described on the 
-[Pythia Foundations](https://foundations.projectpythia.org/landing-page.html) website. Teams are 
-welcome to do their project in R and our compute platform fully supports R for 
-earth science computation. The HackWeek mentors/helpers are experienced in Python, R and Matlab.
-
-## HackWeek Projects
-
-A good hackweek project is a concrete idea that a team can flesh out in a week together. Not everyone needs to code. There is background research to do, data to find, and lots and lots of data wangling. A big part of the fun of hackweek is working together with a group with a diverse set of interests and skills. "I'll find some data." "I make some maps of our study area." "I'll figure out how to do a boosted regression tree." "I'll use that tutorial we were shown and get xyz PACE data for our region." etc, etc. It is messy, but through this process you'll learn new skills and also get to know your project team mates.
-
-The project work is a combination of 
-
-* fleshing out a science idea that is small enough on Monday brainstorming.
-* dividing up into tasks so that everyone can participate.
-* coding and data wrangling on Tuesday through Thursday.
-* and then Friday, frantically putting a presentation on your project and results.
-
-Checkout projects from other hackweeks to get an idea of projects done in earth science hackweeks
-
-* [PACE Hackweek 2024 projects](https://pacehackweek.github.io/pace-2024/projects/list_of_projects.html)
-* [OceanHackWeek projects](https://oceanhackweek.org/ohw24_proj_catalog_us/OHW_project_table.html)
-* [Geosmart HackWeek 2024 projects](https://geosmart-2024.hackweek.io/projects/index.html#list-of-projects)
-* [OceanHackWeek 2025 projects](https://oceanhackweek.org/ohw25/projects/projects_thisyear.html)
+# Checklist
+## Required setup
+
+### EarthData Login
+
+If you do not already have an Earthdata login, then navigate to the Earthdata login [page](https://urs.earthdata.nasa.gov/),
+register, and record username and password somewhere for use during the hackweek. 
+
+### GitHub Account
+
+If you do not already have a GitHub account, then navigate to [GitHub](https://github.com/), enter your email address and click on the green ‘Sign up for GitHub’ button. Keep  your username and password handy.
+
+### JupyterHub
+
+The JupyterHub is a pre-provisioned compute environment which can be accessed via a web browser. You will not need to install anything.
+Please follow these instructions which will guide you through gaining access to the JupyterHub. 
+
+1. [Watch this video](https://youtu.be/uZ2Uy376Az8) to get an orientation on our JupyterHub.
+
+2. Sign in by navigating to the [JupyterHub](https://nmfs-openscapes.2i2c.cloud/). Instructions to sign in are in our Slack channel [here](https://fish-pace.slack.com/files/U09FQF586KU/F09FRKRN5PC/hub.md).
+
+3. You will see server options. To start, you can stay with the default image and RAM. It can take several minutes for new servers to launch on the cloud. Once things are spun up, you will see your very own instance of a JupyterLab environment. 
+
+![server_options](../img/server_options.png)
+
+You will have access to your own virtual drive space under the `/home/jovyan` directory. No other users will be able to see or access your data files. You can add/remove/edit files in your virtual drive space. You will also have access to the  *`shared-public`* folder (read and write access). These are shared spaces so please make sure not to delete files from here unless they are yours.
+
+4. *To save our community money, when you are finished working for the day it is helpful for you to explicitly stop your server before logging out of your JupyterHub session.* To shut your server down immediately when you’re exiting your session please select “File -> Hub Control Panel -> Stop my Server” then you can click the “Log Out” button. We ask this because when you keep a session active it uses up AWS resources and these resources cost money per hour of use. If you forget this step, though, the server will shut down automatically after 90 min of no use.
+Logging out will **NOT** cause any files under your home directory to be deleted. It is equivalent to turning off your desktop computer at the end of the day.
+