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4 changes: 4 additions & 0 deletions .buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 6382536223a54ae3e9decb43895c5ccc
tags: 645f666f9bcd5a90fca523b33c5a78b7
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18 changes: 18 additions & 0 deletions _sources/breakouts1.md
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# Breakout session 1

- Use-cases for open-source data and metadata standards:
- Where has the use of open-source standards benefitted your research?
- How has a lack of open standards impacted your research?
- What are examples of community influenced development of standards in your field?
- How do you create open standards in your experience?

- Cross-sector interaction:
- What are examples of cross-sector collaboration that have had an impact in your field?
- What are the challenges related to developing standards when instrumentation is developed commercially? Discuss specific examples.
- Who is responsible for sustaining standards (i.e., federal funders, research communities, industry, …), and should it be centralized?
- How could the research community guide and influence industry standards to ensure they meet the needs of researchers?

- Failure modes:
- What are points of failure that have you seen in the development and use of open standards?
- What are some lessons that have been learned from failures that you’ve encountered?
- How do you know when it’s time to scrap the old and start a new standard?
17 changes: 17 additions & 0 deletions _sources/breakouts2.md
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# Breakout session 2

- Interactions with open-source software:
- How should open-source maintenance be sustained?
- What are some strategies for taming the complexity of open standards?
- How has standards-compliant software contributed to the development of a standard? And where/how has it been a hindrance?

- Promoting adoption:
- What are strategies for accelerating adoption that have worked in the past?
- How do we train for use of open standards? How do we fit this into a busy curriculum?
- What are some of the arguments/resistance that you encounter against the adoption of standards?
- How does a standard become the standard (in your experience)?

- Bringing data standards to the cloud:
- What are some benefits/challenges of bringing existing data standards to the cloud?
- What is driving movement to the cloud? Is it driven by industry or by the community?
- What are examples of top-down standards that have been defined by cloud providers?
8 changes: 8 additions & 0 deletions _sources/debates.md
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# Debates

This session will be held in debate style, where we will formulates
arguments pro/con the following statements:

1. "Bottom-up deveelopment of standards is better"
2. "Adherence with open standars should be a requirement for federal funding"
3. ""
12 changes: 12 additions & 0 deletions _sources/intro.md
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# Towards an open source model for data and metadata standards

**April 8th-9th, 2024, National Science Foundation, Alexandria Virginia**

Recent progress in machine learning and artificial intelligence promises to advance research and understanding across a wide range of fields and activities. In tandem, an increased awareness of the importance of open data for reproducibility and scientific transparency is making inroads in fields that have not traditionally produced large publicly available datasets. Data sharing requirements from publishers and funders, as well as from other stakeholders, have also created pressure to make datasets with research and/or public interest value available through digital repositories. However, to make the best use of existing data, and facilitate the creation of useful future datasets, robust, interoperable and usable standards need to evolve and adapt over time. The open-source development model provides significant potential benefits to the process of standard creation and adaptation. In particular, development and adaptation of standards can use long-standing socio-technical processes that have been key to managing the development of software, and allow incorporating broad community input into the formulation of these standards. By adhering to open-source standards to formal descriptions (e.g., by implementing schemata for standard specification, and/or by implementing automated standard validation), processes such as automated testing and continuous integration, which have been important in the development of open-source software, can be adopted in defining data and metadata standards as well. Similarly, open-source governance provides a range of stakeholders a voice in the development of standards, potentially enabling use-cases and concerns that would not be taken into account in a top-down model of standards development. On the other hand, open-source models carry unique risks that need to be incorporated into the process. The goal of this workshop is to discuss specific examples where an open-source model for standards development has had significant impact on the practice within a field and other cases where this model has not worked in the past, and/or cases where this model is not a good fit.

The workshop will convene attendees from a broad range of research disciplines and from various sectors (e.g., academic, government and industry) to a two-day workshop that will be held at the NSF headquarters. The meeting will include a mix of activities: plenary talks from experts in the field who can share their experience developing open-source data and metadata standards; breakout discussions on a variety of sub-topics (e.g., governance of data and metadata standards, strategies for evolving and adapting data and metadata standards, etc.); brainstorming sessions; and networking sessions. One of the goals of the workshop is to synthesize the discussions into a white paper that will summarize the state of the art and make concrete recommendations for the future evolution of robust, transparent and useful standards.

```{tableofcontents}
```

#### Funded through [grant \#2334483]() from the NSF [Pathways to Enable Open-Source Ecosystems (POSE) program](https://new.nsf.gov/funding/opportunities/pathways-enable-open-source-ecosystems-pose).
53 changes: 53 additions & 0 deletions _sources/markdown-notebooks.md
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---
jupytext:
formats: md:myst
text_representation:
extension: .md
format_name: myst
format_version: 0.13
jupytext_version: 1.11.5
kernelspec:
display_name: Python 3
language: python
name: python3
---

# Notebooks with MyST Markdown

Jupyter Book also lets you write text-based notebooks using MyST Markdown.
See [the Notebooks with MyST Markdown documentation](https://jupyterbook.org/file-types/myst-notebooks.html) for more detailed instructions.
This page shows off a notebook written in MyST Markdown.

## An example cell

With MyST Markdown, you can define code cells with a directive like so:

```{code-cell}
print(2 + 2)
```

When your book is built, the contents of any `{code-cell}` blocks will be
executed with your default Jupyter kernel, and their outputs will be displayed
in-line with the rest of your content.

```{seealso}
Jupyter Book uses [Jupytext](https://jupytext.readthedocs.io/en/latest/) to convert text-based files to notebooks, and can support [many other text-based notebook files](https://jupyterbook.org/file-types/jupytext.html).
```

## Create a notebook with MyST Markdown

MyST Markdown notebooks are defined by two things:

1. YAML metadata that is needed to understand if / how it should convert text files to notebooks (including information about the kernel needed).
See the YAML at the top of this page for example.
2. The presence of `{code-cell}` directives, which will be executed with your book.

That's all that is needed to get started!

## Quickly add YAML metadata for MyST Notebooks

If you have a markdown file and you'd like to quickly add YAML metadata to it, so that Jupyter Book will treat it as a MyST Markdown Notebook, run the following command:

```
jupyter-book myst init path/to/markdownfile.md
```
55 changes: 55 additions & 0 deletions _sources/markdown.md
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# Markdown Files

Whether you write your book's content in Jupyter Notebooks (`.ipynb`) or
in regular markdown files (`.md`), you'll write in the same flavor of markdown
called **MyST Markdown**.
This is a simple file to help you get started and show off some syntax.

## What is MyST?

MyST stands for "Markedly Structured Text". It
is a slight variation on a flavor of markdown called "CommonMark" markdown,
with small syntax extensions to allow you to write **roles** and **directives**
in the Sphinx ecosystem.

For more about MyST, see [the MyST Markdown Overview](https://jupyterbook.org/content/myst.html).

## Sample Roles and Directives

Roles and directives are two of the most powerful tools in Jupyter Book. They
are like functions, but written in a markup language. They both
serve a similar purpose, but **roles are written in one line**, whereas
**directives span many lines**. They both accept different kinds of inputs,
and what they do with those inputs depends on the specific role or directive
that is being called.

Here is a "note" directive:

```{note}
Here is a note
```

It will be rendered in a special box when you build your book.

Here is an inline directive to refer to a document: {doc}`markdown-notebooks`.


## Citations

You can also cite references that are stored in a `bibtex` file. For example,
the following syntax: `` {cite}`holdgraf_evidence_2014` `` will render like
this: {cite}`holdgraf_evidence_2014`.

Moreover, you can insert a bibliography into your page with this syntax:
The `{bibliography}` directive must be used for all the `{cite}` roles to
render properly.
For example, if the references for your book are stored in `references.bib`,
then the bibliography is inserted with:

```{bibliography}
```

## Learn more

This is just a simple starter to get you started.
You can learn a lot more at [jupyterbook.org](https://jupyterbook.org).
122 changes: 122 additions & 0 deletions _sources/notebooks.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Content with notebooks\n",
"\n",
"You can also create content with Jupyter Notebooks. This means that you can include\n",
"code blocks and their outputs in your book.\n",
"\n",
"## Markdown + notebooks\n",
"\n",
"As it is markdown, you can embed images, HTML, etc into your posts!\n",
"\n",
"![](https://myst-parser.readthedocs.io/en/latest/_static/logo-wide.svg)\n",
"\n",
"You can also $add_{math}$ and\n",
"\n",
"$$\n",
"math^{blocks}\n",
"$$\n",
"\n",
"or\n",
"\n",
"$$\n",
"\\begin{aligned}\n",
"\\mbox{mean} la_{tex} \\\\ \\\\\n",
"math blocks\n",
"\\end{aligned}\n",
"$$\n",
"\n",
"But make sure you \\$Escape \\$your \\$dollar signs \\$you want to keep!\n",
"\n",
"## MyST markdown\n",
"\n",
"MyST markdown works in Jupyter Notebooks as well. For more information about MyST markdown, check\n",
"out [the MyST guide in Jupyter Book](https://jupyterbook.org/content/myst.html),\n",
"or see [the MyST markdown documentation](https://myst-parser.readthedocs.io/en/latest/).\n",
"\n",
"## Code blocks and outputs\n",
"\n",
"Jupyter Book will also embed your code blocks and output in your book.\n",
"For example, here's some sample Matplotlib code:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from matplotlib import rcParams, cycler\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"plt.ion()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Fixing random state for reproducibility\n",
"np.random.seed(19680801)\n",
"\n",
"N = 10\n",
"data = [np.logspace(0, 1, 100) + np.random.randn(100) + ii for ii in range(N)]\n",
"data = np.array(data).T\n",
"cmap = plt.cm.coolwarm\n",
"rcParams['axes.prop_cycle'] = cycler(color=cmap(np.linspace(0, 1, N)))\n",
"\n",
"\n",
"from matplotlib.lines import Line2D\n",
"custom_lines = [Line2D([0], [0], color=cmap(0.), lw=4),\n",
" Line2D([0], [0], color=cmap(.5), lw=4),\n",
" Line2D([0], [0], color=cmap(1.), lw=4)]\n",
"\n",
"fig, ax = plt.subplots(figsize=(10, 5))\n",
"lines = ax.plot(data)\n",
"ax.legend(custom_lines, ['Cold', 'Medium', 'Hot']);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There is a lot more that you can do with outputs (such as including interactive outputs)\n",
"with your book. For more information about this, see [the Jupyter Book documentation](https://jupyterbook.org)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.0"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}
44 changes: 44 additions & 0 deletions _sources/organizers.md
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# Organizer team

```{image} images/andy.png
---
height: 150px
---
```

[Andy Connolly (Department of Astronomy, University of Washington)](https://astro.washington.edu/people/andy-connolly)


```{image} images/nicoleta.png
---
height: 150px
---
```

[Nicoleta Cristea (Freshwater Initiative and Department of Civil and Environmental Engineering, University of Washington)](http://nchydro.weebly.com/)


```{image} images/vani.png
---
height: 150px
---
```

[Vani Mandava (Scientific Software Engineering Center, University of Washington)](https://escience.washington.edu/member/vani-mandava/)


```{image} images/arokem.png
---
height: 150px
---
```

[Ariel Rokem (Department of Psychology, University of Washington)](https://arokem.org)

```{image} images/anshul.png
---
height: 150px
---
```

[Anshul Tambay (Scientific Software Engineering Center, University of Washington)](https://escience.washington.edu/member/anshul-tambay/)
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