PLOS Author Contributions

All PLOS papers (currently about 80,000) include author contributions in a format similar to this:

Conceived and designed the experiments: HQ JKC AR NH. 
Performed the experiments: HQ JKC AR MP. 
Analyzed the data: HQ JKC AR MP NH. 
Contributed reagents/materials/analysis tools: CH. 
Wrote the paper: HQ JKC AR NH.

I want to use the PLOS Search API to do a systematic analysis of these author contributions, e.g. how many times the first author was involved in writing the paper, or how often we have co-authors who appear only in the "contributed reagents/materials/analysis tools" section.

This idea is also an exercise in searching the PLOS CC-BY content for machine-readable information, and in using R for data analysis and visualization. I would be happy to introduce people to R and the rplos package created by rOpenSci that makes working with the PLOS Search API much easier. We will do some nice visualizations with the results, and will write a report in markdown (using the R knitr package) that can be posted to the hack4ac website.

2. Martin Fenner, technical lead of the PLOS article-level metrics project
3. Experience in R, Ruby, Javascript, PHP
4. People who can help with asking good questions, data analysis and writing. People with skills in R or interested in learning R, or experience in Solr query syntax a bonus.

Background

This project is part of the hack4ac event taking place in London July 6, 2013. The goals of the event are twofold:

• Demonstrate the value of the CC-BY licence within academia. We are interested in supporting innovations around and on top of the literature.
• Reach out to academics who are keen to learn or improve their programming skills to better their research. We’re especially interested in academics who have never coded before.

Requirements

• Register for an API key for the PLOS Search API here.
• Create a (free) Github account in case you haven't done so already.
• Install RStudio, a powerful IDE for R via this link.
• Add PLOS API key to your .Rprofile file in your home directory: options(PlosApiKey = [your key]). More info here.
• Install a number of required packages via the RStudio interface or the console: install.packages(c("knitr", "plyr", "rplos"))
• Import this git repository. Use any git tool or the git support in R.
• Open the R project file plos-author-contributions.Rproj in this repository.
• Open the file index.Rmd. This file is where we will do the bulk of our work.

Subprojects

Improve documentation of PLOS Search API

The current schema for the PLOS Solr search is here. Make sure all fields are also documented in the PLOS Search website. Also compare field list to PLOS Search web interface, and add more search examples, including some advanced Solr queries. This can also include a wish list of features you would like to see supported in the PLOS Search API. Write down docuentation in file documentation.md in this repo.

Extract author contributions out of PLOS papers

We will do this using R and the rplos package. We use knitr to document our code in markdown, and do this in the index.Rmd file in this repo. RStudio understands R Markdown files: R code embedded into markdown, using the file extension .Rmd. Although the author contributions field contains structured information, there are some differences between PLOS journals. We also need to strip leading and trailing whitespace and reformat the content so that we have one row per author and one column for each of five author roles:

• Conceived and designed the experiments
• Performed the experiments
• Analyzed the data
• Contributed reagents/materials/analysis tools
• Wrote the paper

Analyze author contributions

Some ideas include the following:

• Add ScoRo Scholarly Contributions and Roles, e.g. provides tools, equipment or facilities or authorship contribution.
• Find particular authorship patterns, e.g. number of papers where at least one author only contributed reagents/materials/analysis tools.
• Correlate authorship for performed the experiments with analyzed the data.
• Analyse Flesch readability score of abstracts and correlate with number of people who wrote the paper and geolocation.
• Visualize authorship patterns.
• Correlate authorship patterns with subject areas and/or geolocation information.

Write a report

We want to summarize our findings in a report, and we can use the R markdown file we generated earlier for that. The report is one of the main intended outcomes of this project.