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DOI

metarepo

metarepo is short for meta-repository, a GitHub repository that contains instructions to reproduce results in a published work. This repo is a template for creating your own metarepo.

Purpose

A meta-repository creates a single point of access for someone to find all of the components that were used to create a published work for the purpose of reproducibility. This repository should contain references to all minted data and software as well as any ancillary code used to transform the source data, create figures for your publication, conduct the experiment, and / or execute the contributing software.

lastname-etal_year_journal

your Paper Title here (once published, include a link to the text)

First Last1*, First Last1, and First Last1, 2

1 Pacific Northwest National Laboratory, Richland, WA, USA.

2 Institute for Energy Analysis, Oak Ridge Associated Universities, Washington, DC, USA

* corresponding author: [email protected]

Abstract

your abstract here

Journal reference

your journal reference

Code reference

References for each minted software release for all code involved.

These are generated by Zenodo automatically when conducting a release when Zenodo has been linked to your GitHub repository. The Zenodo references are built by setting the author order in order of contribution to the code using the author's GitHub username. This citation can, and likely should, be edited without altering the DOI.

If you have modified a codebase that is outside of a formal release, and the modifications are not planned on being merged back into a version, fork the parent repository and add a .<shortname> to the version number of the parent and construct your own name. For example, v1.2.5.hydro.

your software reference here

Data reference

Input data

Reference for each minted data source for your input data. For example:

Human, I.M. (2021). My input dataset name [Data set]. DataHub. https://doi.org/some-doi-number

your input data references here

Output data

Reference for each minted data source for your output data. For example:

Human, I.M. (2021). My output dataset name [Data set]. DataHub. https://doi.org/some-doi-number

your output data references here

Contributing modeling software

Model Version Repository Link DOI
model 1 version link to code repository link to DOI dataset
model 2 version link to code repository link to DOI dataset
component 1 version link to code repository link to DOI dataset

Reproduce my experiment

Fill in detailed info here or link to other documentation to thoroughly walkthrough how to use the contents of this repository to reproduce your experiment. Below is an example.

  1. Install the software components required to conduct the experiment from contributing modeling software
  2. Download and install the supporting input data required to conduct the experiment
  3. Run the following scripts in the workflow directory to re-create this experiment:
Script Name Description How to Run
step_one.py Script to run the first part of my experiment python3 step_one.py -f /path/to/inputdata/file_one.csv
step_two.py Script to run the second part of my experiment python3 step_two.py -o /path/to/my/outputdir
  1. Download and unzip the output data from my experiment
  2. Run the following scripts in the workflow directory to compare my outputs to those from the publication
Script Name Description How to Run
compare.py Script to compare my outputs to the original python3 compare.py --orig /path/to/original/data.csv --new /path/to/new/data.csv

Reproduce my figures

Use the scripts found in the figures directory to reproduce the figures used in this publication.

Figure Number(s) Script Name Description How to Run
1, 2 generate_plot.py Description of figure, ie. "Plots the difference between our two scenarios" python3 generate_plot.py -input /path/to/inputs -output /path/to/outuptdir
3 generate_figure.py Description of figure, ie. "Shows how the mean and peak differences are calculated" python3 generate_figure.py -input /path/to/inputs -output /path/to/outuptdir