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add the jupyterhub sessions
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eeholmes committed Dec 6, 2023
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21 changes: 6 additions & 15 deletions _site.yml
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Expand Up @@ -6,26 +6,17 @@ navbar:
- text: Set-up
icon: fa-clone
href: set-up.html
- text: Workshop Weekly Notes
- text: Workshop Sessions
icon: fa-calendar
menu:
- text: Week 1 Intro to Docker
- text: Intro to Docker
icon: fa-cogs
href: week1-introtodocker-cs.html
- text: Week 2 Creating Docker Images
- text: Intro to JupyterHubs with R
icon: fa-cogs
href: juyterhub-R.html
- text: HackDay Geospatial R
icon: fa-cogs
- text: Week 3 Remote-sensing Data in R
icon: fa-recycle
- text: Week 4 Remote sensing Data in R
icon: fa-recycle
- text: Week 5 Part 1. SDMs
icon: fa-box
- text: Week 6 Part 2. SDMs
icon: fa-box
- text: Week 7 Part 3. SDMs
icon: fa-file-code
- text: Week 8 Setting up a JupyterHub
icon: fab fa-github-alt
- text: RVerse
icon: fas fa-toolbox
href: https://rverse-tutorials.github.io
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137 changes: 86 additions & 51 deletions docs/index.html
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<title>Practical Workflows for Scientists June-July 2023</title>
<title>Practical Workflows for NMFS Scientists 2023</title>

<script src="site_libs/header-attrs-2.21/header-attrs.js"></script>
<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
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<a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" data-bs-toggle="dropdown" aria-expanded="false">
<span class="fa fa-calendar"></span>

Workshop Weekly Notes
Workshop Sessions

<span class="caret"></span>
</a>
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<a href="week1-introtodocker-cs.html">
<span class="fa fa-cogs"></span>

Week 1 Intro to Docker
Intro to Docker
</a>
</li>
<li class="dropdown-header">Week 2 Creating Docker Images</li>
<li class="dropdown-header">Week 3 Remote-sensing Data in R</li>
<li class="dropdown-header">Week 4 Remote sensing Data in R</li>
<li class="dropdown-header">Week 5 Part 1. SDMs</li>
<li class="dropdown-header">Week 6 Part 2. SDMs</li>
<li class="dropdown-header">Week 7 Part 3. SDMs</li>
<li class="dropdown-header">Week 8 Setting up a JupyterHub</li>
<li>
<a href="juyterhub-R.html">
<span class="fa fa-cogs"></span>

Intro to JupyterHubs with R
</a>
</li>
<li class="dropdown-header">HackDay Geospatial R</li>
</ul>
</li>
<li>
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<h1 class="title toc-ignore">Practical Workflows for Scientists
June-July 2023</h1>
<h1 class="title toc-ignore">Practical Workflows for NMFS Scientists
2023</h1>

</div>

Expand All @@ -334,49 +335,83 @@ <h1 class="title toc-ignore">Practical Workflows for Scientists
</table>
<p><br></p>
<p><img style="float: right;" src="images/tools-logo-transparent.png" width=30%></p>
<p>In 2023, I am focusing on Part 1) cloud computing platforms and Part
2) working with remote-sensing data in R. Why cloud computing? Well the
days of doing all your work on a computer with all your software
downloaded to that are numbered. It is not a very efficient way to work.
It is more efficient to have everyone working on a fully provisioned
platform so you can focus on the science and not the software
installation headaches. Part 2) is because I am preparing for a couple
oceanography hackweeks in late summer. The focus of these workshops is
practical skills and tools; they are intended to get you applying the
skill immediately in your own work. I will give you links to my and
other NOAA GitHub repositories that illustrate more complex examples
(that you can copy and build on).</p>
<p><strong>Target audience</strong>: This year I am assuming that you
have an understanding of using Git and GitHub. See the <a
href="https://rverse-tutorials.github.io/RWorkflow-NWFSC-2022/">RWorflow
Workshops 2022</a> if not. All sessions (except last) were recorded.</p>
<p>In 2023, I am focusing on cloud computing platforms and working with
remote-sensing data in R. Why cloud computing platforms? This allows
everyone to work in a fully provisioned platform so you can focus on the
science and not the software installation. See the ‘Workshop Sessions’
tab in top navigation for a link to 2023 sessions.</p>
<p><strong>About the instructor Eli Holmes</strong>: I am a
modeler/applied mathematician. I develop R packages for public use. I
teach time-series analysis at the University of Washington (using R) and
I teach workshops on R and reproducible research and am heavily involved
in efforts to support transition to Open Science workflows within NOAA
Fisheries. <a href="http://eeholmes.github.io/">website</a></p>
modeler/applied mathematician. I teach time-series analysis at the
University of Washington (using R) and I teach workshops on R and
reproducible research. Since 2021, I have been attending and helping
with hackweeks using JupyterHubs provisioned for geospatial analyses: <a
href="https://nasa-openscapes.github.io/2021-Cloud-Hackathon/">NASA
EarthData Cloud hackweek</a>, <a
href="https://icesat-2-2022.hackweek.io/">ICESat-2 hackweek</a>, <a
href="https://snowex-2022.hackweek.io/">SnowEx hackweek</a> (assistant),
<a href="https://oceanhackweek.org/ohw23/index.html">OceanHackWeek</a>
(project lead), <a
href="https://hackweek-itcoocean.github.io/2023-Hackbook/">ITCOocean
Hack2Week</a> (lead organizer).</p>
<hr>
<div id="topics" class="section level3">
<h3>2023 Topics</h3>
<div id="dec-6---intro-to-jupyterhubs" class="section level2">
<h2>Dec 6 - Intro to JupyterHubs</h2>
<p>On Dec 6th at 12:30PM PT, I am demo-ing a JupyterHub that I have set
up on a Kubernetes Cluster on the NOAA Azure account. If you want to
join <a
href="https://calendar.google.com/calendar/event?action=TEMPLATE&amp;tmeid=MjJ0OGo5bGJsZ2xrdmc3NWtpMnNtY244OXVfMjAyMzEyMDZUMjEwMDAwWiBjXzkxNmI2OTQ4ZWYyZWU4YjdkNDljMjg2NjFlZmMwNzk4MzAzYzI3NDJiZTM5OWM5MjkwZmEwMmQ5MzIwYzc2OWVAZw&amp;tmsrc=c_916b6948ef2ee8b7d49c28661efc0798303c2742be399c9290fa02d9320c769e%40group.calendar.google.com">ADD
CALENDAR</a> event.</p>
<p>In this session, you will get a brief introduction to JupyterHubs,
which is a popular platform for cloud computing. It is an open source,
provider agnostic (runs on AWS, GCP or Azure), computing platform used
across scientific communities for shared computing environments. You’ll
get to play around on a JupyterHub set up for geospatial analyses with R
or Python using either Jupyter notebooks or RStudio. I will discuss how
cloud computing platforms streamline and accelerate science innovation
by increasing reproducibility and removing the “set-up” phase of a
computing environment. This is especially important with big data
geospatial analysis as the ‘set-up’ phase can be tricky and
time-consuming.</p>
<p>JupyterHub: <a
href="https://dhub.opensci.live/hub/login">https://dhub.opensci.live/hub/login</a></p>
<p>If you want to get on the JupyterHub during the intro session, I will
need your GitHub username. Provide that with this form: <a
href="https://forms.gle/RQdnw4HsbSd3zC9b8">https://forms.gle/RQdnw4HsbSd3zC9b8</a></p>
</div>
<div id="dec-19---geospatial-data-in-r-hackday-dec-19th"
class="section level2">
<h2>Dec 19 - Geospatial Data in R HackDay Dec 19th</h2>
<p>On Dec 19th 8-3pm PT, I will run a mini NOAA hackday during which we
will use the JupyterHub to do a day of geospatial analysis with R and
work on projects pitched by the group. <a
href="https://calendar.google.com/calendar/event?action=TEMPLATE&amp;tmeid=MHM4MWtvNDFvamRrcWNnOHBoMHZvb2VqYWkgY185MTZiNjk0OGVmMmVlOGI3ZDQ5YzI4NjYxZWZjMDc5ODMwM2MyNzQyYmUzOTljOTI5MGZhMDJkOTMyMGM3NjllQGc&amp;tmsrc=c_916b6948ef2ee8b7d49c28661efc0798303c2742be399c9290fa02d9320c769e%40group.calendar.google.com">ADD
CALENDAR</a> event.</p>
<p><strong>Schedule</strong></p>
<ul>
<li><a href="week1-introtodocker-cs.html">June 27</a>
<strong>Introduction to Docker for R users</strong> I will introduce you
to using Docker to run R and RStudio in containers. <a
href="week1-introtodocker-cs.html">Lecture notes</a></li>
<li><a href="">July 7</a> <strong>Customizing Docker images</strong> We
will learn how to create customized Docker files and how to build your
own docker images that you’ll can store on Docker Hub.</li>
<li><a href="">July 14</a> <strong>Part 1. Intro to remote sensing data
with R</strong></li>
<li><a href="">July 21</a> <strong>Part 2. Intro to remote sensing data
with R</strong></li>
<li><a href="">July 28</a> <strong>Part 1. Intro to marine SDMs with
R</strong></li>
<li><a href="">August 4</a> <strong>Part 2. Intro to marine SDMs with
R</strong></li>
<li>8-8:30 Welcome and orientation to the JupyterHub</li>
<li>8:30-10am Geospatial tutorials in R on accessing NASA Earth
Data</li>
<li>10-11am Explore data and come up with a project</li>
<li>11-12pm Break and lunch</li>
<li>12-12:30pm Pitch a project!</li>
<li>12:30-2:30pm Hack and co-work on the project</li>
<li>2:30-3pm Report out!</li>
</ul>
<!-- - [Lecture video](https://youtu.be/M1sOC4046PQ) - [Q&A](week1.html) -->
<p>GitHub username required to participate as we will use it provide
access to the JupyterHub. Provide with this form: <a
href="https://forms.gle/RQdnw4HsbSd3zC9b8">https://forms.gle/RQdnw4HsbSd3zC9b8</a>.</p>
<p><em>Coding skills needed</em> For this session, I will only be
presenting content in R. However Python programmers are welcome to join
as a geospatial environment for Python is also on the hub. You will not
need Git/GitHub skills. The GitHub username is used for authentication
to the hub.</p>
<!--
* [July 28]() **Part 1. Intro to marine SDMs with R**
* [August 4]() **Part 2. Intro to marine SDMs with R**
* [July 7]() **Customizing Docker images** We will learn how to create customized Docker files and how to build your own docker images that you'll can store on Docker Hub.
[Lecture video](https://youtu.be/M1sOC4046PQ) - [Q&A](week1.html) -->
<hr>
<div style="text-align: center">
<p><i class="fas fa-cubes"></i> NWFSC Math Bio Program, NOAA Fisheries
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