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# Encouraging code and data sharing: a primer in open science and reproducible research

<br>

```
Stephen J Eglen                  Cambridge Computational Biology Institute
https://sje30.github.io          University of Cambridge
sje30@cam.ac.uk                  @StephenEglen
```

Slides: http://bit.ly/eglen-3rs  (CC-BY license)

<br>

#### Acknowledgements

Paul Charlseworth, Ellese Cotterill, Catherine Cutts, Tom Edinburgh,
Gerrit Hilgen, Ole Paulsen, Evelyne Sernagor, Rachel Wong.

BBSRC, EPSRC, Wellcome Trust, Software Sustainability Institute.

---
# Confusing terms in usage today

### Data science

### Open science

### Reproducible research

---
class: center, middle

# Personal Activities to promote 3Rs

---
# Curate data repositories

MEA recordings of spontaneous activity in developing retina

---
# Files in waverepo

---
#  Evaluate analytical techniques

---
#  "realistic" synthetic data / 1

---
# "realistic" synthetic data / 2

---
#  "realistic" synthetic data / 2

---
# Inverse problems are hard

.pull-left[
<br>
<table>
 <thead>
  <tr>
   <th style="text-align:left;"> Mark </th>
   <th style="text-align:left;"> grade </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 70-100 </td>
   <td style="text-align:left;"> A </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 60-69 </td>
   <td style="text-align:left;"> B </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 50-59 </td>
   <td style="text-align:left;"> C </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 40-49 </td>
   <td style="text-align:left;"> D </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 0-39 </td>
   <td style="text-align:left;"> F </td>
  </tr>
</tbody>
</table>
]
.pull-right[
### Forward problem

I scored 68, what was my grade?

### Inverse problem

I got a B, what was my score?
]

---
# Research sharing: the inverse problem

<br>

---
# Where is the scholarship?

> An article about computational science in a scientific publication
> is not the scholarship itself, it is merely advertising of the
> scholarship. The actual scholarship is the complete software
> development environment and that complete set of instructions that
> generated the figures.

[Buckheit and Donoho 1995, after Claerbout]

---
# Moral or selfish approach?

<br>

<div style="font-size: 60%; position: absolute; right: 15%;   width: fit-content; height: fit-content; top:95%; z-index:10"><a href="http://dx.doi.org/10.1186/s13059-015-0850-7">10.1186/s13059-015-0850-7</a></div>
---
# Selfish reasons to share

Why not align what is good for science with what is good for
scientists?

1. Funding mandates (REF + enforcement from Wellcome Trust)
2. Credit through data papers
3. Fixes data bugs / errors in analysis
4. Prevent data loss [(Vines et al 2014)](http://www.ncbi.nlm.nih.gov/pubmed/24361065). e.g. students have a habit of leaving...
5. Your future self is probably one of the main beneficiaries of
   sharing.
6. *Now* is a very good time to be an open scientist.
7. Leads to further collaborations
8. Reviewers can do more work...

---
# meaRtools: Tools for MEA analysis

<div style="font-size: 60%; position: absolute; right: 15%;   width: fit-content; height: fit-content; top:95%; z-index:10"><a href="http://dx.doi.org/10.1101/242065">10.1101/242065</a></div>
---
# Reviewers doing your work

I would use an ordinate log scale for this bottom right panel (as
    done in Fig.  3). But since the authors gave me everything, I can
    do it! by redefining fourplot as follows:

![](eglen-3rs_files/figure-html/unnamed-chunk-4-1.png)
#

---
# Code review pilot

---
# Specific recommendations

1. Include enough code to reproduce key figure/result from your paper
   ("modeldb").
2. Provide toy examples if your project is too intensive to expect
   others to run in a few hours.
3. Version control (github)
4. Licence (MIT)
5. Provide data
6. Provide tests
7. Use standards 
8. Use permanent URLs (Zenodo/figshare)

---
# Simple example of reproducible research

Eglen SJ (2016) Bivariate spatial point patterns in the retina: a
reproducible review. Journal de la Société Française de Statistique
157:33–48.

See

[paper](https://doi.org/10.1101/029348)
or [code](http://github.com/sje30/eglen2015).

---
# New tools

1. **Docker** Can bundle entire open-source evironment for others to share.
2. Jupyter notebooks
3. binder = Docker + jupyter + cloud compute

[https://github.com/sofroniewn/2pRAM-paper](https://github.com/sofroniewn/2pRAM-paper)

---
# Find a code buddy

* We ask our students to submit a .Rnw file rather than a pdf.  You get
a zero if I can't compile the pdf.
* So, ask someone else if they can run your code.
* Talk to some of the Software Sustainability Institute
  [Fellows](https://software.ac.uk/fellows/) at Oxford.
* Learn R, python, git...

---
# Summary

* Find the selfish reasons to make your research reproducible.
* Adopt good practices to help you on your way.
* Writing code in groups can be very motivating.
* Use new tech if you want, but old tech works too.