The Birder’s Guide to rOpenSci

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# The Birder’s Guide to rOpenSci
## Maëlle Salmon <a href="https://twitter.com/ma_salmon"></a> ma_salmon <a href="https://github.com/maelle"></a> maelle <a href="https://masalmon.eu"></a> masalmon.eu
### 2018/09/12

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# My goals today
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* **Inspiring** you to try out rOpenSci packages.

* **Motivating** you to get involved with rOpenSci.

* **Sharing**  a few tips from my experience.

Slidedeck up at https://tiny.cc/animove
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#     Short intro to me 😉

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# My science credentials

* BSc in Biology, MSc in (Theoretical) Ecology

* Master of Public Health

* PhD in Statistics

Nowadays, more of a *research software engineer*.

Part-time software engineer at rOpenSci & at Locke Data.

Not an actual birder. 🙀

All pics by my dad. 📷

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# My place in the R community

* R-Ladies Global social master

* R Weekly team member (and blogger myself!)

* Volunteer editor for rOpenSci onboarding

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#     What is rOpenSci?

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# What's rOpenSci?

* Community of researchers and software developers

* R packages for open and reproducible science

* Community and staff contributions

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# https://ropensci.org/packages/

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# rOpenSci onboarding!

How to ensure quality in the whole suite?

Open software reviews.

* drive adoption of best practices and standards

* build a community of practice

* partnerships with the Journal of Open Source Software and Methods in Ecology and Evolution

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# What to review for?
--

```r
magick::image_read("https://raw.github.com/jtleek/rpackages/master/documentation.png")
```

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# Review criteria

* Open-source initiative (OSI) compatible license

* Complete docs

* High test coverage

* Readable code

* Usability

[ropensci.github.io/dev_guide/](https://ropensci.github.io/dev_guide/)

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# Side-note: your R 📦
--

Bye bye `source("myfunctions.R")`, hello `library("mypkg")`!
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* At least for future you!

* Automatic tools make it easier

List of resources: https://masalmon.eu/2017/12/11/goodrpackages/

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# How to review?
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* Open & non-adversarial

* No rejections

* Makes the process constructive for everyone involved

* Technically, using GitHub infrastructure

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# rOpenSci onboarding

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# The issues tracker

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# Submitting a package

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# Submitting a package

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# Submitting a package

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# Rejection

No rejections... but out-of-scope packages not onboarded.

https://ropensci.github.io/dev_guide/policies.html#aims-and-scope

* fit in our categories: data retrieval, data extraction, database access, data munging, data deposition, reproducibility, geospatial data, text analysis.

* application in _science_

* better than similar packages

When in doubt, pre-submission enquiry!

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# Pre-submission enquiry?

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# Pre-submission enquiry?

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# The review process

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# The review process: editor checks

<img src="index_files/figure-html/onboarding-editor-1.png" width="350" style="display: block; margin: auto;" />
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# The review process: reviews

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# The review process: reviews

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# The review process

Ongoing discussion until acceptance and transfer

Often a blog post https://ropensci.org/tags/review/

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#     An exploration from Radolfzell

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# An exploration from Radolfzell

5 use cases. Not all detailed in the talk! 😌
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All details in blog posts https://ropensci.org/tags/birder/

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# An exploration from Radolfzell
 
Leveraging rOpenSci packages and also:

* the `magrittr` pipe `%>%` to pass output from one function to the following function

* `tidyverse` (`ggplot2`, `dplyr`, `purrr`)

* `sf`

* `R Markdown`

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# Case study 1

Where to go birding near Radolfzell?

[Code&output](https://maelle.github.io/animove/demo/2018-08-14-where-to-bird.html)

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# Case study 1

* Open geographical data (💚 OpenStreetMap)

* `opencage`
    
    * `osmdata`
    
    * `osmplotr`

https://ropensci.org/blog/2018/08/14/where-to-bird/ (co-written with [Mark Padgham](https://github.com/mpadge))

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# Case study 2

What birds are observed in the county?

eBird occurrence data

* `rebird`, API, latest 30 days

* `auk`, access request needed, whole dataset

[Code&output](https://maelle.github.io/animove/demo/2018-08-21-birds-radolfzell.html)

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# Case study 2

Occurrence data

* `rebird` and `auk`

* more data sources via `spocc`

* `mapr`, `scrubr`, `CoordinateCleaner`

https://ropensci.org/blog/2018/08/21/birds-radolfzell/

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# Case study 3

Taxonomy and traits data of these birds

```r
ids <- taxize::get_uid(unique(ebd$scientific_name))
classif <- taxize::classification(ids)
tree <- taxize::class2tree(classif)
```

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# Case study 3

```r
library("ggplot2")
ggtree::ggtree(tree$phylo) +
    ggtree::geom_tiplab(aes(), size = 2, vjust=0.25) +
  xlim(0, 150)
```

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# Case study 3

![Messy tree](2018-09-04-birds-taxo-traits_files/figure-markdown_github/firsttree-1.png)

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# Case study 3

`rphylopic` + `phylobase` + ugly code

![animated tree](2018-09-04-birds-taxo-traits_files/figure-markdown_github/taxo.gif)

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# Case study 3

Taxonomy: `taxize`

Traits: `traits`

https://ropensci.org/blog/2018/09/04/birds-taxo-traits/

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# Case study 4

What were these species studied for?

[Code&output](https://maelle.github.io/animove/demo/2018-09-11-birds-science.html)

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# Case study 4

https://ropensci.org/blog/2018/09/11/birds-science/

Literature: `fulltext` & more!

Open scientific data: `dataone` (not rOpenSci), `rfigshare`

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#     Bonus: Old drawings

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# Natural history drawings

[Code&output](https://maelle.github.io/animove/demo/2018-08-28-birds-ocr.html)

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# Natural history drawings

https://ropensci.org/blog/2018/08/28/birds-ocr/

* `magick` for image manipulation

* `tesseract` for optical character recognition (OCR)

* `cld2` and `cld3` for language recognition

* `taxize::gnr_resolve` for taxonomic name resolution

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#     Conclusion

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# An impressive package suite

Missing from this overview: workflow packages such as `drake`, `gistr`, `git2r`.

https://ropensci.org/packages/

https://ropensci.org/tags/birder/

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#     A few tips

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# How to keep up-to-date with R &rOpenSci

* Twitter \#rstats hashtag

* [R Weekly](https://rweekly.org/), [rOpenSci biweekly newsletter](https://news.ropensci.org/)

* Conference programs & videos

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# How to not be overwhelmed

* Fine not to know everything!

* Learn asking for help and advice

* when you need
    
    * where you should https://masalmon.eu/2018/07/22/wheretogethelp/
    
* Make R friends

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# How to learn new R skills?

By doing!

* Try out stuff for yourself

* Blog! `blogdown`

* Danielle Navarro's 100 days of code https://djnavarro.net/#posts
    
    * My own blog https://masalmon.eu/2018/07/16/soapbox/

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#     Get involved with rOpenSci

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# Get involved

* Use our packages and tell us!

https://discuss.ropensci.org/

* Get involved with onboarding (submit, review)

https://github.com/ropensci/onboarding

* More ways to get involved

https://ropensci.org/community/

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# Thank you! https://tiny.cc/animove

[](https://twitter.com/ma_salmon) ma_salmon, [](https://github.com/maelle) maelle , [](https://masalmon.eu) masalmon.eu

[](https://twitter.com/rOpenSci) rOpenSci, [](https://github.com/ropensci) ropensci , [](https://ropensci.org) ropensci.org