## Welcome to the AIMOS Mini-ReproHack!
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<br>
### Event Page:
### https://reprohack.org/event/13/
Contains all event information and links to materials
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# Introductions
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go around the room and introduce themselves too. If online, consider using break-out rooms of 5-6 people -->
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## Who am I?
### Dr Anna Krystalli (@annakrystalli)
- Research Software Engineer _University of Sheffield_
- 2019 Fellow _Software Sustainability Institute_
- Software Peer Review Editor _rOpenSci_
- _ReproHack_ Core Team member
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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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# Your turn
- ## Who are you?
- ## Why are you here?
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# Welcome Back
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## ReproHack Objectives
1. **Practical Experience in Reproducibility**
3. **Feedback to Authors**
5. **Think more broadly about opportunities and challenges**
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# Plan of Action
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### Reproduce paper
1. **Paper review and team formation**
2. **Select and register your paper on hackpad**
3. **Work on your paper!**
6. **Feedback at the end (group & authors)**
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# Tips for reviewing
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## Code of Conduct
Event governed by [**ReproHack Code of Conduct**](https://reprohack.org/code-of-conduct)
<br>
### 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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# Reproduce and Review
# :mag:
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## Selecting Papers
- **Author comments:** paper descroption and why you should choose to reproduce.
- **Tags:** Tools, languages & domains
- **No. attempts:** No. times reproduction has been attempted
- **Mean Repro Score:** Mean reproducibility score (out of 10)
- lower == harder!
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## Review as an auditor :bookmark_tabs:
### Looking for FAIR principles
- Findable
- Accessible
- Interoperable
- Reusable
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## Access
- How easy was it to gain access to the materials?
## Installation
- How easy / automated was installation?
- Did you have any problems?
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## Data
- Were data clearly separated from code and other items?
- Were large data files deposited in a trustworthy data repository and referred to using a persistent identifier?
- Were data documented ...somehow...
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## Documentation
Was there adequate documentation describing:
- how to install necessary software including non-standard dependencies?
- how to use materials to reproduce the paper?
- how to cite the materials, ideally in a form that can be copy and pasted?
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## Analysis
- Were you able to fully reproduce the paper? :white_check_mark:
- How automated was the process of reproducing the paper?
- How easy was it to link analysis code to:
- the plots it generates
- sections in the manuscript in which it is described
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## Analysis
### If the analysis was not fully reproducible :no_entry_sign:
- Did results (e.g. model outputs, tables, figures) differ to those published? By how much?
- Were missing dependencies?
- Was the computational environment not adequately described / captured?
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## Review as a user :video_game:
<br>
#### What did you find easy / intuitive?
#### What did you find confusing / difficult
#### What did you enjoy?
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# Feed back
# :speech_balloon:
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## Feedback as a community member
<br>
#### Acknowledge author effort
#### Give feedback in good faith
#### Focus on community benefits and system level solutions
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# Let's go! :checkered_flag:
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## 1. Paper review / Team formation
+ Have a look at the papers available for reproduction
+ Add your details to the **hackpad**.
+ Fine to work individually or tackle a papers as group
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## 2. Project registration
+ Register your team and paper on the **hackpad**
+ Register for an account on the Hub.
+ Feel free to work here or in break-out rooms.
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## 3. Reproduce Paper
- Inspect the review form.
- Try to reproduce the paper using the materials provided.
- Record your responses to review questions according to your experiences.
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## 4. Feedback to authors
- **Please complete the feedback form for authors**
- Feel free to record general findings the hackpad
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## 5. Final regroup
- So, how did you get on?
- Final comments.
- On hackpad: One thing you liked, one thing that can be improved.
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# Get involved!
### Visit ReproHack Hub <https://reprohack.org>
- [**Submit a paper for review**](https://reprohack.org/paper/new/)
- [**Organise your own event**](https://reprohack.org/event/new/)
_Check out our [Resources](https://reprohack.org/resources) for more details_
### Chat to us:
[![Slack](https://img.shields.io/badge/slack-join%20us-orange?style=for-the-badge&logo=slack)](https://reprohack-autoinvite.herokuapp.com/)
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## THANK YOU ALL! :pray:
- ### Thank you PARTICIPANTS for coming!
- ### Thank you AUTHORS for submitting!
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# Resources
- [**Example Compendium**](https://github.com/annakrystalli/rrcompendiumDTB): Demo Research compendium
- [**The Turing Way**](https://the-turing-way.netlify.com/introduction/introduction): a lightly opinionated guide to reproducible data science.
- [**Statistical Analyses and Reproducible Research**](): Gentleman and Temple Lang's introduction of the concept of Research Compendia
- [**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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# :wave:
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