Skip to content

Latest commit

 

History

History
65 lines (39 loc) · 3.76 KB

README.md

File metadata and controls

65 lines (39 loc) · 3.76 KB
Raw

A paper about Versioned Data Delivery and the datastorr package

This repository contains code needed to reproduce the article:

Falster DS, FitzJohn RG, Pennell MW, Cornwell WK (2019) Datastorr: a workflow and package for delivering successive versions of 'evolving data' directly into R. GigaScience 8: 1–8. doi: 10.1093/gigascience/giz035

and/or the preprint:

Falster DS, FitzJohn RG, Pennell MW, Cornwell WK (2017) Versioned data: why it is needed and how it can be achieved (easily and cheaply). doi 10.7287/peerj.preprints.3401v1

We think delivering versioned data to users in a simple and easy way will help science a lot.

Running the code

All analyses were done in R, and the paper is written in LaTeX. All code needed to reproduce the submitted products is included in this repository. To reproduce this paper, run the code contained in the analysis.R file. The paper will be produced in the directory ms.

If you are reproducing this manuscript on your own machine, first download the code and then install the tinytex package.

You can access an interactive RStudio session with the required software pre-installed by opening a container hosted by Binder:

Launch Rstudio Binder

To ensure long-term computational reproducibility of this work, we have created a Docker image to enable others to reproduce these results on their local machines using the same software and versions we used to conduct the original analysis. Instructions for reproducing this work using the docker image are available at the bottom of the page.

Material included in the repository include:

  • ms/: directory containing manuscript in LaTeX and accompanying style files
  • figures/: directory containing figures for the manuscript
  • DESCRIPTION: A machine-readable compendium file containing key metadata and dependencies
  • LICENSE: License for the materials
  • Dockerfile & .binder/Dockerfile: files used to generate docker containers for long-term reproducibility

Running via Docker

If you have Docker installed, you can recreate the computing environment as follows in the terminal.

From the directory you'd like this repo saved in, clone the repository:

git clone https://github.com/traitecoevo/data_versioning.git

Then fetch the container:

docker pull traitecoevo/data_versioning

Navigate to the downloaded repo, then launch the container using the following code (it will map your current working directory inside the docker container):

docker run --user root -v $(pwd):/home/rstudio/ -p 8787:8787 -e DISABLE_AUTH=true traitecoevo/data_versioning

The code above initialises a docker container, which runs an RStudio session accessed by pointing your browser to localhost:8787. For more instructions on running docker, see the info from rocker.

NOTE: Building the docker image

For posterity, the docker image was built off rocker/verse:3.6.1 container via the following command, in a terminal contained within the downloaded repo:

docker build -t traitecoevo/data_versioning .

and was then pushed to dockerhub. The image used by binder builds off this container, adding extra features needed by binder, as described in rocker/binder.