Content from IPCC FAIR Background
Last updated on 2024-10-24 | Edit this page
Overview
Questions
- What are the fundamentals to produce a FAIR IPCC Assessemt Report`?
Objectives
- Learn the FAIR priniciples and motivations
- Learn about genereal Research Data and Software Management Practices
- Learn about story telling and visualisation
FAIR data principles at IPCC
motivation for archiving code, figures, input data and metadata FAIR guidance
The experience in AR6 and shortcomings
including some examples.
Fundamentals of Sustainable Research Software
Software Management Plans eScience
Fundamentals of Research Data Management
Models of interactive products:
Storytelling, layered storytelling, static vs dynamic, GIS-based models.
Content from AR7 Tutorial
Last updated on 2024-10-24 | Edit this page
Overview
Questions
- How do I generate digital outputs?
- How do I describe and curate digital outputs?
- How do I transfer to the TSU the digital outputs?
Objectives
- Produce data and figures (tooling/programming)
- Create and Manage a software repository
- Generate Metadata
- Obtain a DOI for data
- Obtain a DOI for software
The AR6 experience and lessons learnt
Author profiles
spreadsheet sam, notebook nancy, script sandy
Categories and governance of digital IPCC products
From figures to interactive applicatio
Content from Editing Tutorial - Markdown
Last updated on 2024-10-24 | Edit this page
Overview
Questions
- How do you write a lesson using Markdown and sandpaper?
Objectives
- Explain how to use markdown with The Carpentries Workbench
- Demonstrate how to include pieces of code, figures, and nested challenge blocks
Introduction
This is a lesson created via The Carpentries Workbench. It is written in Pandoc-flavored Markdown for static files and R Markdown for dynamic files that can render code into output. Please refer to the Introduction to The Carpentries Workbench for full documentation.
What you need to know is that there are three sections required for a valid Carpentries lesson:
-
questions
are displayed at the beginning of the episode to prime the learner for the content. -
objectives
are the learning objectives for an episode displayed with the questions. -
keypoints
are displayed at the end of the episode to reinforce the objectives.
Challenge 1: Can you do it?
What is the output of this command?
R
paste("This", "new", "lesson", "looks", "good")
OUTPUT
[1] "This new lesson looks good"
Challenge 2: how do you nest solutions within challenge blocks?
You can add a line with at least three colons and a
solution
tag.
Figures
You can use standard markdown for static figures with the following syntax:
{alt='alt text for accessibility purposes'}
Callout
Callout sections can highlight information.
They are sometimes used to emphasise particularly important points but are also used in some lessons to present “asides”: content that is not central to the narrative of the lesson, e.g. by providing the answer to a commonly-asked question.
Math
One of our episodes contains \(\LaTeX\) equations when describing how to create dynamic reports with {knitr}, so we now use mathjax to describe this:
$\alpha = \dfrac{1}{(1 - \beta)^2}$
becomes: \(\alpha = \dfrac{1}{(1 - \beta)^2}\)
Cool, right?
Key Points
- Use
.md
files for episodes when you want static content - Use
.Rmd
files for episodes when you need to generate output - Run
sandpaper::check_lesson()
to identify any issues with your lesson - Run
sandpaper::build_lesson()
to preview your lesson locally