diff --git a/_site.yml b/_site.yml index fa13bb8..3b77526 100644 --- a/_site.yml +++ b/_site.yml @@ -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 diff --git a/docs/index.html b/docs/index.html index e4e898a..de4f07e 100644 --- a/docs/index.html +++ b/docs/index.html @@ -11,7 +11,7 @@ -Practical Workflows for Scientists June-July 2023 +Practical Workflows for NMFS Scientists 2023 @@ -257,7 +257,7 @@ @@ -266,16 +266,17 @@ - Week 1 Intro to Docker + Intro to Docker - - - - - - - +
  • + + + + Intro to JupyterHubs with R + +
  • +
  • @@ -310,8 +311,8 @@ -

    Practical Workflows for Scientists -June-July 2023

    +

    Practical Workflows for NMFS Scientists +2023

    @@ -334,49 +335,83 @@

    Practical Workflows for Scientists


    -

    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).

    -

    Target audience: This year I am assuming that you -have an understanding of using Git and GitHub. See the RWorflow -Workshops 2022 if not. All sessions (except last) were recorded.

    +

    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.

    About the instructor Eli Holmes: 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. website

    +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: NASA +EarthData Cloud hackweek, ICESat-2 hackweek, SnowEx hackweek (assistant), +OceanHackWeek +(project lead), ITCOocean +Hack2Week (lead organizer).


    -
    -

    2023 Topics

    +
    +

    Dec 6 - Intro to JupyterHubs

    +

    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 ADD +CALENDAR event.

    +

    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.

    +

    JupyterHub: https://dhub.opensci.live/hub/login

    +

    If you want to get on the JupyterHub during the intro session, I will +need your GitHub username. Provide that with this form: https://forms.gle/RQdnw4HsbSd3zC9b8

    +
    +
    +

    Dec 19 - Geospatial Data in R HackDay Dec 19th

    +

    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. ADD +CALENDAR event.

    +

    Schedule

      -
    • June 27 -Introduction to Docker for R users I will introduce you -to using Docker to run R and RStudio in containers. Lecture notes
    • -
    • 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.
    • -
    • July 14 Part 1. Intro to remote sensing data -with R
    • -
    • July 21 Part 2. Intro to remote sensing data -with R
    • -
    • July 28 Part 1. Intro to marine SDMs with -R
    • -
    • August 4 Part 2. Intro to marine SDMs with -R
    • +
    • 8-8:30 Welcome and orientation to the JupyterHub
    • +
    • 8:30-10am Geospatial tutorials in R on accessing NASA Earth +Data
    • +
    • 10-11am Explore data and come up with a project
    • +
    • 11-12pm Break and lunch
    • +
    • 12-12:30pm Pitch a project!
    • +
    • 12:30-2:30pm Hack and co-work on the project
    • +
    • 2:30-3pm Report out!
    - +

    GitHub username required to participate as we will use it provide +access to the JupyterHub. Provide with this form: https://forms.gle/RQdnw4HsbSd3zC9b8.

    +

    Coding skills needed 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.

    +

    NWFSC Math Bio Program, NOAA Fisheries diff --git a/docs/jupyterhub-R.html b/docs/jupyterhub-R.html new file mode 100644 index 0000000..8172264 --- /dev/null +++ b/docs/jupyterhub-R.html @@ -0,0 +1,487 @@ + + + + + + + + + + + + + +Intro to JupyterHubs with RStudio + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    + + + +
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    + +
    + + + + + + + + + +
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    Intro to JupyterHubs

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    + +
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    + NWFSC Math Bio Program, NOAA Fisheries +
    + + +
    +
    + +
    + + + + + + + + + + + + + + + + diff --git a/docs/links.html b/docs/links.html index e241da4..5ee3ab6 100644 --- a/docs/links.html +++ b/docs/links.html @@ -257,7 +257,7 @@ @@ -266,16 +266,17 @@ - Week 1 Intro to Docker + Intro to Docker

  • - - - - - - - +
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    Resolving merge conflicts with GitHub Desktop

  • Now try to Pull. It’ll tell you that you have conflicts and give you options for what to do.
  • -
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    GitHub Desktop merge conflict alert

    +
    + +
    GitHub Desktop merge conflict alert
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  • - - - - - - - +
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    Resolving merge conflicts with GitHub Desktop

  • Now try to Pull. It’ll tell you that you have conflicts and give you options for what to do.
  • -
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    GitHub Desktop merge conflict alert

    +
    + +
    GitHub Desktop merge conflict alert
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  • diff --git a/index.Rmd b/index.Rmd index 739b65a..d7fcd64 100644 --- a/index.Rmd +++ b/index.Rmd @@ -1,5 +1,5 @@ --- -title: "Practical Workflows for Scientists June-July 2023" +title: "Practical Workflows for NMFS Scientists 2023" --- @@ -16,25 +16,48 @@ title: "Practical Workflows for Scientists June-July 2023" -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). +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. -**Target audience**: This year I am assuming that you have an understanding of using Git and GitHub. See the [RWorflow Workshops 2022](https://rverse-tutorials.github.io/RWorkflow-NWFSC-2022/) if not. All sessions (except last) were recorded. - -**About the instructor Eli Holmes**: 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. [website](http://eeholmes.github.io/) +**About the instructor Eli Holmes**: I am a 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: [NASA EarthData Cloud hackweek](https://nasa-openscapes.github.io/2021-Cloud-Hackathon/), [ICESat-2 hackweek](https://icesat-2-2022.hackweek.io/), [SnowEx hackweek](https://snowex-2022.hackweek.io/) (assistant), [OceanHackWeek](https://oceanhackweek.org/ohw23/index.html) (project lead), [ITCOocean Hack2Week](https://hackweek-itcoocean.github.io/2023-Hackbook/) (lead organizer).
    -### 2023 Topics +## Dec 6 - Intro to JupyterHubs +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 [ADD CALENDAR](https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MjJ0OGo5bGJsZ2xrdmc3NWtpMnNtY244OXVfMjAyMzEyMDZUMjEwMDAwWiBjXzkxNmI2OTQ4ZWYyZWU4YjdkNDljMjg2NjFlZmMwNzk4MzAzYzI3NDJiZTM5OWM5MjkwZmEwMmQ5MzIwYzc2OWVAZw&tmsrc=c_916b6948ef2ee8b7d49c28661efc0798303c2742be399c9290fa02d9320c769e%40group.calendar.google.com) event. -* [June 27](week1-introtodocker-cs.html) **Introduction to Docker for R users** I will introduce you to using Docker to run R and RStudio in containers. [Lecture notes](week1-introtodocker-cs.html) -* [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. -* [July 14]() **Part 1. Intro to remote sensing data with R** -* [July 21]() **Part 2. Intro to remote sensing data with R** +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. + +JupyterHub: [https://dhub.opensci.live/hub/login](https://dhub.opensci.live/hub/login) + +If you want to get on the JupyterHub during the intro session, I will need your GitHub username. Provide that with this form: [https://forms.gle/RQdnw4HsbSd3zC9b8](https://forms.gle/RQdnw4HsbSd3zC9b8) + +## Dec 19 - Geospatial Data in R HackDay Dec 19th + +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. [ADD CALENDAR](https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=MHM4MWtvNDFvamRrcWNnOHBoMHZvb2VqYWkgY185MTZiNjk0OGVmMmVlOGI3ZDQ5YzI4NjYxZWZjMDc5ODMwM2MyNzQyYmUzOTljOTI5MGZhMDJkOTMyMGM3NjllQGc&tmsrc=c_916b6948ef2ee8b7d49c28661efc0798303c2742be399c9290fa02d9320c769e%40group.calendar.google.com) event. + +**Schedule** + +* 8-8:30 Welcome and orientation to the JupyterHub +* 8:30-10am Geospatial tutorials in R on accessing NASA Earth Data +* 10-11am Explore data and come up with a project +* 11-12pm Break and lunch +* 12-12:30pm Pitch a project! +* 12:30-2:30pm Hack and co-work on the project +* 2:30-3pm Report out! + +GitHub username required to participate as we will use it provide access to the JupyterHub. Provide with this form: [https://forms.gle/RQdnw4HsbSd3zC9b8](https://forms.gle/RQdnw4HsbSd3zC9b8). + +*Coding skills needed* 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. + + + +[Lecture video](https://youtu.be/M1sOC4046PQ) - [Q&A](week1.html) -->
    diff --git a/jupyterhub-R.Rmd b/jupyterhub-R.Rmd new file mode 100644 index 0000000..d4fe856 --- /dev/null +++ b/jupyterhub-R.Rmd @@ -0,0 +1,11 @@ +--- +title: "Intro to JupyterHubs with RStudio" +output: + html_document: + toc: true + include: + after_body: footer.html +--- + +## Intro to JupyterHubs +