Building tools and community for open and reproducible research

Scott Chamberlain (@ropensci)

UC Berkeley / rOpenSci

This talk on the web:

recology.info/talks/sfustats

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These data are hard to get

Cultural barriers

Lack of incentives (carrots)

Lack of pressure (sticks)

Getting scooped ()

Takes too much time! ()

Instructions for preparation of the Biographical Sketch have been revised to rename the "Publications" section to "Products" and amend terminology and instructions accordingly. This change makes clear that products may include, but are not limited to, publications, data sets, software, patents, and copyrights.

Issuance of a new NSF Proposal & Award Policies and Procedures Guide (October 4th)

the Data Policy states the ‘minimal dataset’ consists “of the dataset used to reach the conclusions drawn in the manuscript with related metadata and methods, and any additional data required to replicate the reported study findings in their entirety. This does not mean that authors must submit all data collected as part of the research, but that they must provide the data that are relevant to the specific analysis presented in the paper.

PLOS Editorial and Publishing Policies

 Why Open?

To increase the pace of science

Openness facilitates reproducibility

For yourself!

To avoid mistakes

Data is increasingly on the web

API: Application Programming Interface

Reproducibly plug data from the web into research workflows

How rOpenSci got started

formed from ad-hoc conversation over Twitter. Now a worldwide community of researchers

http://ropensci.org/community

R has a lot of packages
(mostly data manip./viz & statistics)

rOpenSci packages

ropensci.org/packages

rOpenSci packages

ropensci.org/packages

Some numbers for amount of the data

Code demos

The diversity of projects

How easy it is

Imagine these examples at scale

 Biology

rentrez - an R client for ENTREZ

David Winter

Post-doc at Arizona State University

taxize
all things taxonomy

and many more...

Unified species occurrence data - spocc

 Literature

 Publishing

EML

EML provides a common structure for data, to better enable ecologists to document, share, and interpret ecological data

EML standard enables data integration at the machine level (with little or no human intervention).

Publishing outlets

• Figshare

• Zenodo

• Dataone

• Various journals

• More...

 History

History - mostly by
Lincoln Mullen at George Mason University

 Archeology

 Altmetrics

article-level metrics

There are a lot of altmetrics out there

altmetrics data often open

Docker

Software robustness through time

Other reasons

Training

Software quality

The rOpenSci Community

Community stats

• 71 contributors

• 148 Github repositories

• > 9,000 commits over ~3 years

• a few pkgs with ~900 commits

• ~66 R packages

Domains

• Ecology/Biology

  
  
  

• Altmetrics

• History

• Archeology

• More...

Training

rOpenSci Ambassador Program

Give talks

Code demos

rOpenSci brings to the table:

Bridge btw scientists & data providers

Visibility

Consistency

Quality

Conversation/community

Stability

github.com/ropengov

github.com/ropenhealth

In closing...

This is all about improving research

rOpenSci is just one vehicle with which to help

rOpenSci on the web: ropensci.org

This talk on the web: recology.info/talks/sfustats

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