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title: CCMcr19 ReproHack slides
tags: ReproHack, introduction, slides
description: View the slide with "Slide Mode".
slideOptions:
theme: white
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# Welcome to our ReproHack!

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### Event Repository: bit.ly/CCMcr19-ReproHack

Contains all event information and links to materials

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# Introductions

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## Who am I?

### Dr Anna Krystalli (@annakrystalli)

- Research Software Engineer _University of Sheffield_
- Software Peer Review Editor _rOpenSci_
- Co-organiser _Sheffield R Users Group_

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## Why am I here?

I believe there's lots to learn about Reproducibility from working with real published projects.

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## Who is my favorite animated character?

Stitch!


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<!-- Open it up to participants -->

## Who are you?

## Why are you here?

## Who is your favorite animated character?

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# Plan of Action

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### Reproduce paper / Hack the ReproHack

1. **Project review and team formation**

2. **Select and register your project**

3. **Work on your project!**

4. **Re-group part-way through.**

6. Feedback at the end (group & authors)

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## Your Work Might be Publishable!

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### [ReScience C](http://rescience.github.io/)

> **ReScience C** is an open-access peer-reviewed journal that targets computational research and encourages the **explicit replication** of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible.

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### What is **Replication:**
- Repeating a published protocol
- Respecting its spirit and intentions
- **Varying the technical details**, e.g. using different software, initial conditions, etc.

***

#### Change something that everyone believes shouldn’t matter, and see if the scientific conclusions are affected

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### Replicate your paper

- Finished early? Consider attempting **replication**!
- Replications could be considered for publication in **ReScience C** Journal

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#### But! ReScience got in touch and **considering creating a new category!**

- **Reproducibility Report**:
+ were results reproduced?
+ how hard/easy was it to reproduce?
+ did architectures differ etc.
+ what else? _discussion topic_

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### Then https://scigen.report got in touch:


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# Feed back

# :speech_balloon:

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### Feed back

- **Regroup part way through** to discuss progress and troubleshoot any sticking points
- **Feedback to authors** using form by end of session
- **Feedback to group** at the end, contribute to discussions

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## Code of Conduct

Event governed by [**Carpentries Code of Conduct**](https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html)

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### Additional Considerations

- #### Reproducibility is hard!
- #### Submitting authors are incredibly brave!

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## Thank you Authors! :raised_hands:

- #### Without them there would be no ReproHack.
- #### Show gratitude and appreciation for their effort and bravery. :pray:
- #### Constructive criticism only please!

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# Let's go! :checkered_flag:

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### Paper / hack topic review

#### **papers**: bit.ly/CCMcr19-ReproHack-papers
#### **topics**: bit.ly/CCMcr19-ReproHack-topics

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### Team formation / project registration

+ Fine to work individually
+ Register your team and paper / topic by [**opening a new issue**](https://github.com/reprohack/reprohack-2019-06-27/issues/new/choose). bit.ly/CCMcr19-ReproHack
+ Add your details to the [**hackpad**](https://hackmd.io/@U2KSpBasRLqM0fN-YALVrw/r1LTia9RV/edit).

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### Mid-point regroup

- Briefly describe the approach to reproducibility the paper has taken.
- Anything in particular you like about the paper's approach?
- Anything you're having difficulty with?

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### Feedback to authors

- Please complete the feedback form for authors bit.ly/CCMcr19-ReproHack-feedback
- Feel free to take notes on the hackpad

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### Final regroup

- So, how did you get on?
- Final comments.
- If there's time, tackle some discussion topics (see hackpad).
- One thing you liked, one thing that can be improved (use post it's if you prefer)

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### Further Resources

- [**The Turing Way**](https://the-turing-way.netlify.com/introduction/introduction): a lightly opinionated guide to reproducible data science.
- [**Packaging data analytical work reproducibly using R (and friends)**](https://peerj.com/preprints/3192/): how researchers can improve the reproducibility of their work using research compendia based on R packages and related tools

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# THANK YOU ALL! :pray:

- ### Thank you PARTICIPANTS for coming!
- ### Thank you AUTHORS for submitting!

# :wave: