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reproducibility-value-in-practice.Rmd
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reproducibility-value-in-practice.Rmd
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---
title: "Reproducibility"
subtitle: "the value in the practice"
author: "_Anna Krystalli `r anicon::faa('twitter', animate='float', rtext='@annakrystalli')`_ "
date: "2019-11-30 <br> <small> Leiden ReproHack! </small>"
output:
xaringan::moon_reader:
lib_dir: libs
css: [assets/css/reproducibility-in-practice-xaringan-themer.css, assets/css/reproducibility-in-practice_custom.css]
nature:
beforeInit: "https://platform.twitter.com/widgets.js"
dev: svg
highlightStyle: github
highlightLines: true
countIncrementalSlides: false
---
```{r xaringan-themer, include = FALSE}
library(xaringanthemer)
duo_accent(
primary_color = "#77DDBC", secondary_color = "#75a3a3",
title_slide_text_color = "#334d4d", text_bold_color = "white" ,
text_color = "#e6e6e6", link_color = "#75a3a3",
inverse_text_color = "#334d4d", inverse_header_color = "#77DDBC",
header_font_google = google_font("Calistoga", "400"),
text_font_google = google_font("Lato", "700", "700i"),
code_font_google = google_font("Source Code Pro"),
background_color = "#334d4d",
title_slide_background_image = "../backgrounds/reprohack-slide.png",
#background_image = "../backgrounds/reprohack-slide.png",
background_size = "cover", outfile = "assets/css/ç-xaringan-themer.css"
)
```
# `r emo::ji("wave")` Hello
### me: **Dr Anna Krystalli**
- **Research Software Engineer**, _University of Sheffield_
+ twitter **@annakrystalli**
+ github **@annakrystalli**
+ email **a.krystalli[at]sheffield.ac.uk**
- **Editor [rOpenSci](http://onboarding.ropensci.org/)**
- **Co-organiser:** [Sheffield R Users group](https://www.meetup.com/SheffieldR-Sheffield-R-Users-Group/)
<br>
### slides: **bit.ly/repro-value-in-practice**
---
## Welcome to the 4th ReproHack! `r emo::ji("tada")`
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">This thing is really happening! <a href="https://t.co/d2xnHNo9z2">pic.twitter.com/d2xnHNo9z2</a></p>— ReproHack NL ♻️ (@ReproHackNL) <a href="https://twitter.com/ReproHackNL/status/1174998682879631360?ref_src=twsrc%5Etfw">September 20, 2019</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
---
## Welcome to the 4th ReproHack! `r emo::ji("tada")`
### Thanks to the Leiden Repro Ladies `r emo::ji("pray")`
---
## Welcome to the 4th ReproHack! `r emo::ji("tada")`
### Thanks to the Software Sustainability Institute
---
class: inverse, center, middle
# Background
---
background-image: url(assets/boats.png)
background-size: cover
.box[
## Marine Biology
]
---
background-image: url(assets/maps.png)
background-size: cover
.box[
## Marine Biology
]
---
background-image: url(https://www.reactiongifs.com/r/O_o.gif)
background-size: cover
class: inverse
.box[
## Quality Assurance
> #### _QA Auditor for a Contract Research Organisation subject to GLP regulation_
]
---
background-image: url(assets/ruchindra-gunasekara-GK8x_XCcDZg-unsplash.jpg)
background-size: cover
.box[
## Ultrasport
> #### _Brand coordinator for an extreme sports equipment distributing_
]
---
class: inverse, center, middle
# Back to science:
---
.pull-left[
### Ooops, that's embarassing!
<br>
]
.pull-right[
]
---
# The paper is the advertisement
> “an article about computational result is advertising, not scholarship. The **actual scholarship is the full software environment, code and data, that produced the result.**”
*John Claerbout paraphrased in [Buckheit and Donoho (1995)](https://statweb.stanford.edu/~wavelab/Wavelab_850/wavelab.pdf)*
--
### Why is our whole system geared towards **reviewing, publishing, distributing, archiving** the adverstisement?
---
## Progress: calls for reproducibility as minimum standard
> #### **Reproducibility** has the potential to serve as a **minimum standard for judging scientific claims** when full independent replication of a study is not possible.
<br>
.center[
<img src="assets/repro-spectrum.jpg" width="650px" />
]
.img-attr[Reproducible Research in Computational Science
_ROGER D. PENG, SCIENCE 02 DEC 2011 : 1226-1227_
]
<br>
---
class: inverse, center, middle
.box[
## Benefit #1
]
## transparency as a means of verification
---
background-image: url("https://media1.giphy.com/media/BWTZOE4vnj3gs/giphy.gif?cid=790b761105c665c045cf431bde7e8419e02f3f6314ac0d32&rid=giphy.gif")
background-size: cover
.box[
### there is a hidden superpower
]
---
background-image: url("assets/repository-fork.png")
--
.pull-left[
<br>
<br>
<br>
<br>
<br>
<br>
.box[
## **Woah, It's evolution...**
]
]
.pull-right[
<br>
<br>
<br>
<br>
<br>
<br>
]
---
> #### [**_Macroecological and macroevolutionary patterns emerge in the universe of GNU/Linux operating systems_**](https://doi.org/10.1111/ecog.03424)
> doi:10.1111/ecog.03424
.pull-left[
]
--
.pull-right[
<img src="assets/ecography_gnu_fig4.jpg" height=430px>
]
---
> #### [_Macroecological and macroevolutionary patterns emerge in the universe of GNU/Linux operating systems_](https://doi.org/10.1111/ecog.03424)
> doi:10.1111/ecog.03424
.center[
<img src="assets/ecography_gnu_fig5.jpg" height=470px>
]
---
background-image: url("assets/hanslibdata.png")
background-size: cover
## Example: **gapminder.org: 2006**
### [liberating stories from data](https://youtu.be/hVimVzgtD6w?t=15m3s)
---
## Gapminder today
```{r, fig.show = "animate", message=FALSE, warning=FALSE}
library(ggplot2)
p <- ggplot(gapminder::gapminder, aes(gdpPercap, lifeExp, size = pop, color = continent, frame = year)) +
geom_point() + scale_x_log10() + theme_bw()
```
```{r, message=FALSE, warning=FALSE, fig.height=4}
plotly::ggplotly(p)
```
---
class: inverse, center, middle
.box[
## Benefit #2
]
## transparency as a means of supercharging research cycle
---
class: inverse, center, middle
# Reproducible Research Compendia
---
### The concept of a Research Compendium
>“
...We introduce the **concept of a compendium**
as both a **container for the different elements**
that make up the document and its computations (i.e. text, code, data, ...), and as a **means for distributing, managing and updating the
collection**."
[_Gentleman and Temple Lang, 2004_](https://biostats.bepress.com/bioconductor/paper2/)
---
## Principles
.img-attr[slides: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
---
## Components
.img-attr[slides: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
---
### Research compendia in R
**Ben Marwick, Carl Boettiger & Lincoln Mullen (2018)** [_Packaging Data Analytical Work Reproducibly Using R (and Friends)_](https://peerj.com/preprints/3192/)
.pull-left[
.img-attr[slides: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
]
.pull-right[
]
---
## Example compendium
.pull-left[
**Paper**:
##### Boettiger, C. (2018) *From noise to knowledge: how randomness generates novel phenomena and reveals information*. <https://doi.org/10.1111/ele.13085>
<img src="assets/Boettiger-2018.png" heigth="250px" width="400px">
]
.pull-right[
**Compendium**
##### *cboettig/noise-phenomena: Supplement to: "From noise to knowledge: how randomness generates novel phenomena and reveals information"* http://doi.org/10.5281/zenodo.1219780
<img src="assets/boettiger_compendium.png" heigth="250px" width="400px">
]
---
# `rrtools`: Creating Compendia in R
### "The goal of rrtools is to provide **instructions, templates, and functions** for making a **basic compendium** suitable for writing **reproducible research with R**."
<br>
### Install [`rrtools`](https://github.com/benmarwick/rrtools) from GitHub
```{r, eval=FALSE}
# install.packages("devtools")
devtools::install_github("benmarwick/rrtools")
```
---
# Create compendium
```{r, eval=FALSE}
rrtools::create_compendium("~/Documents/workflows/rrcompendium")
```
```
✔ Setting active project to '/Users/Anna/Documents/workflows/rrcompendium'
✔ Creating 'R/'
✔ Creating 'man/'
✔ Writing 'DESCRIPTION'
✔ Writing 'NAMESPACE'
✔ Writing 'rrcompendium.Rproj'
✔ Adding '.Rproj.user' to '.gitignore'
✔ Adding '^rrcompendium\\.Rproj$', '^\\.Rproj\\.user$' to '.Rbuildignore'
✔ Opening new project 'rrcompendium' in RStudio
✔ The package rrcompendium has been created
✔ Opening the new compendium in a new RStudio session...
Next, you need to: ↓ ↓ ↓
● Edit the DESCRIPTION file
● Use other 'rrtools' functions to add components to the compendium
```
---
## `DESCRIPTION` file
#### Package metadata
```yaml
Package: rrcompendiumDTB
Title: Partial Reproduction of Boettiger Ecology Letters 2018;21:1255–1267 with rrtools
Version: 0.0.0.9000
Authors@R:
person(given = "Anna",
family = "Krystalli",
role = c("aut", "cre"),
email = "annakrystalli@googlemail.com")
Description: This repository contains the research compendium of the partial
reproduction of Boettiger Ecology Letters 2018;21:1255–1267. The compendium
contains all data, code, and text associated with this sub-section of the
analysis.
```
---
# Prepare for sharing
```{r, eval=FALSE}
rrtools::use_readme_rmd()
```
.pull-left[
```
✔ Creating 'README.Rmd' from template.
✔ Adding 'README.Rmd' to `.Rbuildignore`.
● Modify 'README.Rmd'
✔ Rendering README.Rmd to README.md for GitHub.
✔ Adding code of conduct.
✔ Creating 'CONDUCT.md' from template.
✔ Adding 'CONDUCT.md' to `.Rbuildignore`.
✔ Adding instructions to contributors.
✔ Creating 'CONTRIBUTING.md' from template.
✔ Adding 'CONTRIBUTING.md' to `.Rbuildignore`.
```
]
.pull-right[
]
---
# Create analysis folder
```{r, eval=FALSE}
rrtools::use_analysis()
```
```
✔ Adding bookdown to Imports
✔ Creating 'analysis' directory and contents
✔ Creating 'analysis'
✔ Creating 'analysis/paper'
✔ Creating 'analysis/figures'
✔ Creating 'analysis/templates'
✔ Creating 'analysis/data'
✔ Creating 'analysis/data/raw_data'
✔ Creating 'analysis/data/derived_data'
✔ Creating 'references.bib' from template.
✔ Creating 'paper.Rmd' from template.
Next, you need to: ↓ ↓ ↓ ↓
● Write your article/report/thesis, start at the paper.Rmd file
● Add the citation style library file (csl) to replace the default provided here, see https://github.com/citation-style-language/
● Add bibliographic details of cited items to the 'references.bib' file
● For adding captions & cross-referencing in an Rmd, see https://bookdown.org/yihui/bookdown/
● For adding citations & reference lists in an Rmd, see http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html
```
---
# `paper.Rmd` to `paper.pdf`
.pull-left[
**Rmd**
<img src="assets/paper_rmd.png" >
]
.pull-right[
**pdf**
<img src="assets/paper_pdf.png" >
]
---
# Capturing dependencies
```{r, eval=FALSE}
rrtools::add_dependencies_to_description()
```
```
Imports:
bookdown,
ggplot2 (>= 3.0.0),
ggthemes (>= 3.5.0),
here (>= 0.1),
knitr (>= 1.20),
rticles (>= 0.6)
```
---
# Further Helpers
## `r emo::ji("package")` `rticles`
Contains a **suite of custom R Markdown templates for popular journals**, simplifying the creation of documents that conform to research paper submission standards.
---
# `r emo::ji("package")` `citr`
RStudio Add-in to **Insert Markdown Citations**
<img src="assets/citr-insert.png" width="700px">
---
class: inverse, center, middle
# Reproducible Computational Environments
---
## Why isn't sharing code enough?
### Case Study: Sharing a Geospatial Analysis in R
***
#### On a computer without System Library `GDAL` `r emo::ji("x")`
.pull-left[
```r
package ‘rgdal’ successfully unpacked
and MD5 sums checked
configure: gdal-config: gdal-config
checking gdal-config usability... ./configure:
line 1353: gdal-config: command not found
no
*Error: gdal-config not found
...
*ERROR: configuration failed for
package ‘rgdal’
```
]
.pull-right[
<br>
<br>
.img-attr[slide: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
]
---
## What are Docker containers?
### standardized units of software
**package up everything needed to run an application:** _code, runtime, system tools, system libraries_ and settings in a lightweight, standalone, executable package
--
- #### **Dockerfile**: Text file containing recipe for setting up computation environment.
- #### **Docker Image**: Executable **built** from the **Dockerfile** with all required dependencies installed. Can have many images from the same `Dockerfile`.
- #### **Docker Container**: **Docker Images** become containers at **runtime**
.center[
<img src="assets/docker_workflow.png" height=180px>
]
---
# Rocker on DockerHub
#### using the `rocker/geospatial` Docker Image `r emo::ji("white_check_mark")`
***
.pull-left[
]
.pull-right[
<br>
<br>
.img-attr[slide: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
]
---
# Create Dockerfile w/ `rrtools`
```{r, eval=FALSE}
rrtools::use_dockerfile()
```
```r
✔ Creating 'Dockerfile' from template.
✔ Adding 'Dockerfile' to `.Rbuildignore`.
● Modify
Next:
* Edit the dockerfile with your name & email
* Edit the dockerfile to include system dependencies, such as linux libraries that are needed by the R packages you're using
* Check the last line of the dockerfile to specify which Rmd should be rendered in the Docker container, edit if necessary
```
---
# `Dockerfile`
```{bash, eval= FALSE}
# get the base image, the rocker/verse has R, RStudio and pandoc
FROM rocker/verse:3.6.0
# required
*MAINTAINER Anna Krystalli <annakrystallil@googlemail.com>
COPY . /rrcompendiumDTB
# go into the repo directory
RUN . /etc/environment \
# Install linux depedendencies here
# e.g. need this for ggforce::geom_sina
&& sudo apt-get update \
&& sudo apt-get install libudunits2-dev -y \
# build this compendium package
&& R -e "devtools::install('/rrcompendiumDTB', dep=TRUE)" \
# render the manuscript into a docx, you'll need to edit this if you've
# customised the location and name of your main Rmd file
* && R -e "rmarkdown::render('/rrcompendiumDTB/analysis/paper/paper.Rmd')"
```
---
# Docker + Travis
## Create `.travis.yml`
```{r, eval=FALSE}
rrtools::use_travis()
```
```r
✔ Creating '.travis.yml' from template.
✔ Adding '.travis.yml' to `.Rbuildignore`.
Next:
* Add a travis shield to your README.Rmd:
[](https://travis-ci.org/annakrystalli/rrcompendiumDTB)
* Turn on travis for your repo at https://travis-ci.org/annakrystalli/rrcompendiumDTB
** To connect Docker, go to https://travis-ci.org/, and add your environment
*variables: DOCKER_EMAIL, DOCKER_USER, DOCKER_PASS to enable pushing to the
*Docker Hub
```
---
# `.travis.yml`
```bash
env:
global:
- REPO=$DOCKER_USER/rrcompendiumdtb
sudo: required
warnings_are_errors: false
language: generic
services:
- docker
before_install:
* - docker build -t $REPO .
```
Create & build image using dockerfile
---
# `.travis.yml`
Push our custom docker image to docker hub
```bash
after_success:
* - docker login -u $DOCKER_USER -p $DOCKER_PASS
- export REPO=$DOCKER_USER/rrcompendiumdtb
- export TAG=`if [ "$TRAVIS_BRANCH" == "master" ]; then echo "latest"; else echo $TRAVIS_BRANCH ; fi`
- docker build -f Dockerfile -t $REPO:$COMMIT .
- docker tag $REPO:$COMMIT $REPO:$TAG
- docker tag $REPO:$COMMIT $REPO:travis-$TRAVIS_BUILD_NUMBER
* - docker push $REPO
```
---
class: middle, inverse, center
# How to review a research compendium?
---
class: inverse, center, middle
# Review as an auditor
---
## Access
- How easy was it to gain access to the materials?
## Installation
- How easy / automated was installation?
- Did you have any problems?
## Data
- Data were clearly separated from code and other items?
- Large data files were deposited in a trustworthy data repository and referred to using a persistent identifier?
- Data are documented ...somehow...
---
## Documentation
Was there adequate documentation describing:
- the purpose and target audience of the compendium?
- how to cite the compendium in a form that can be copy and pasted?
- how to install necessary software including non-standard dependencies?
- how to use materials to reproduce the paper?
## Analysis
- Were all dependencies clearly specified?
- Was a full computational environment captured?
- How automated was the reproduction?
- How easy was it to link analysis code to:
- the plots it generates
- sections in the manuscript in which it is described
---
class: inverse, center, middle
## Review as a user
---
.pull-left[
]
--
.pull-right[
## User Testing
#### What did you find easy / intuitive?
#### What did you find confusing / difficult
#### What did you enjoy?
]
---
class: inverse, center, middle
## Feedback as a community member
---
### Acknowledge author effort
--
### Give feedback in good faith
--
### Focus on community benefits
- and system level solutions
---
class: inverse, center, middle
# td:lr
## Reproducbility:
## the value in the practice
---
background-image: url('assets/1728_TURI_Book sprint_38 computer readable_040619.jpg')
background-size: contain
.box[
## Following conventions `r emo::ji("right_arrow")`
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]
.box[
#### This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence.
]
---
background-image: url('assets/reproducible-data-analysis_042.png')
background-size: contain
.box[
## Successful Reproducibility `r emo::ji("right_arrow")`
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.box[slide: [_Karthik Ram: rstudio::conf 2019 talk_](https://github.com/karthik/rstudio2019)]
]
---
background-image: url('assets/1728_TURI_Book sprint_36 data research cycle_040619.jpg')
background-size: contain
.box[
## Enhanced Research Cycle `r emo::ji("arrows_counterclockwise")`
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#### This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence.
]
]
---
background-image: url('assets/1728_TURI_Book sprint_26 culture shift_040619.jpg')
background-size: contain
.box[
## Reproducibility as standard `r emo::ji("+1")`
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.box[
#### This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence.
]
]
---
class: inverse, center, middle
# Further Resources
---
# The Turing Way
.pull-left[
### Book
#### a lightly opinionated guide to reproducible data science
<https://the-turing-way.netlify.com>
<img src="assets/1728_TURI_Book sprint_12 chapter_040619.jpg"
height="150px">
]
.pull-right[
### workshops
- **Boost Your Research Reproducibility with Binder** [materials](https://github.com/alan-turing-institute/the-turing-way/tree/master/workshops/boost-research-reproducibility-binder)
- **Build a binderhub** [materials](https://github.com/alan-turing-institute/the-turing-way/tree/master/workshops/build-a-binderhub)
]
### <https://github.com/alan-turing-institute/the-turing-way>
---
## Reviewing resources