Authors: Zhian N. Kamvar and Sydney E. Everhart
This poster is to be presented at the International Congress of Plant Pathology in the summer of 2018.
Open and reproducible research is quickly becoming an important topic in plant pathology where research output can directly influence management decisions that affect global food supply. Moreover, data sharing among plant pathologists has the potential to reduce cost and increase collaboration overall. While there is a need for plant pathologists to become familiar with concepts and tools of open and reproducible research, few examples specific to our field exist. We recently assessed the population genetic structure of the white mold pathogen, Sclerotinia sclerotiorum from research plots and commercial fields across the United States. Due to the vast amount of work that went into collecting all the data and measurements, we deliberately designed our data analysis such that it was i) auditable ii) reproducible and iii) open and accessible by anyone. We present here this case study of reproducible research in plant pathology as a proof-of-concept standard of open research for data sets of any size, attainable by anyone. In a non-technical manner, we provide a clear overview of the concepts and mechanisms used to produce a full-fledged publication starting from raw data in the R programming language. By providing recommendations for open research practices in plant pathology, we hope to foster a zeitgeist that will enable scientists in our discipline to reproduce their research with confidence, creating more efficient sharing and evaluation of data and materials.
The entire poster was created on MacOS 10.13.3 with Inkscape 0.92.2 (5c3e80d, 2017-08-06) built from homebrew. The color palette used was the "Echo Icon Theme" palette with some modifications for luminance.
The main font used in this poster is Lato. All monospace fonts are Noto Mono. Both of these font families are free to download.
All of the icons and emoji were found in the Xaviju/inkscape-open-symbols repository.
- Docker: Docker Media Kit
- Dryad: Dryad wiki
- Figshare: Wikipedia commons
- Zenodo: Zenodo About Page
- Open Science Framework: WUSTL Library
- PeerJ: PeerJ press room
- BioRxiv: Wikipedia
- Binder: GitHub
