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23 changes: 23 additions & 0 deletions .github/workflows/draft-pdf.yml
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on: [push]

jobs:
paper:
runs-on: ubuntu-latest
name: Paper Draft
steps:
- name: Checkout
uses: actions/checkout@v2
- name: Build draft PDF
uses: openjournals/openjournals-draft-action@master
with:
journal: joss
# This should be the path to the paper within your repo.
paper-path: paper/paper.md
- name: Upload
uses: actions/upload-artifact@v1
with:
name: paper
# This is the output path where Pandoc will write the compiled
# PDF. Note, this should be the same directory as the input
# paper.md
path: paper/paper.pdf
34 changes: 34 additions & 0 deletions paper/paper.bib
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@article{cwl,
Author = {Michael R. Crusoe and Sanne Abeln and Alexandru Iosup and Peter Amstutz and John Chilton and Nebojša Tijanić and Hervé Ménager and Stian Soiland-Reyes and Bogdan Gavrilovic and Carole Goble and The CWL Community},
Title = {Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language},
Year = {2021},
Eprint = {arXiv:2105.07028},
Doi = {10.1145/3486897},
}

@misc{wdl,
author = {WDL Community},
title = {Workflow Description Language (WDL)},
year = {2017},
publisher = {GitHub},
journal = {GitHub repository},
url = {https://github.com/openwdl/wdl}
}

@misc{miniwdl,
author = {miniwdl Community},
title = {miniwdl},
year = {2018},
publisher = {GitHub},
journal = {GitHub repository},
url = {https://github.com/chanzuckerberg/miniwdl/}
}

@misc{cwl_utils,
author = {CWL Community},
title = {cwl-utils},
year = {2019},
publisher = {GitHub},
journal = {GitHub repository},
url = {https://github.com/common-workflow-language/cwl-utils}
}
62 changes: 62 additions & 0 deletions paper/paper.md
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---
title: 'wdl2cwl: A Python tool for converting WDL workflow files to CWL workflows'
tags:
- Python
- workflow
- workflow description language
- common workflow language
- Language
authors:
- name: Dinithi Wickramaratne
- name: Dennis Chukwunta
- name: Michael R. Crusoe
orcid: 0000-0002-2961-9670
- name: Bruno P. Kinoshita
orcid: 0000-0001-8250-4074
- name: Peter Amstutz
orcid: 0000-0003-3566-7705
date: August 2022
bibliography: paper.bib
---

# Summary

Computational workflows are used in data analysis, enabling innovation and
decision-making in various fields of science. There are several competing workflow description languages,
WDL (Workflow description Language) and CWL (Common Workflow Languaage) are two examples
of popularly used systems. WDL is a way to specify data processiing workflows with
a human-readable and writeable syntax. WDL makes it straightforward to define
complex analysis tasks, chain them together in workflows, and parallelize their execution [@wdl].
CWL is a way to describe command line tools and connect
the together to create workflows. Because CWL is a specification and not a
specific piece of software, tools and workflows described using CWL are portable acroos
a variety of platforms that support the CWL standard [@cwl].

It can be hard learning and adapting to the various knowledge requirements and
specifications of a workflow language. This complication makes it hard for analysts and scientists
share their work and collaborate efficiently with others who are use to working with different language.

``wdl2cwl`` is a Python package for converting workflow files written in WDL to workflows in CWL. Python
allows flexibility and the ability to import other Python packages.
The ``wdl2cwl`` package uses the ``miniwdl`` package [@miniwdl], an open-source, Python package,
developer toolkit and local runner for running wdl files. The ``wdl2cwl`` package was
designed to provide a class-based and developer-friendly interface for extracting
the various sections of a wdl file, dynamically create the various objects
needed to create a valid cwl file ( this is done using the ``cwl.utils`` package [@cwl_utils],
an open-source, Python package for parsing cwl files) and performing error checking
for valid imports, input declarations, expressions etc.

``wdl2cwl`` was designed to be used by both cwl and wdl professionals and researchers, as well
students in courses on bioinformatics and data analytics. It has already been
used to convert a number of wdl workflows. This tool makes it easier
to translate your favourite WDL workflows into CWL. This could be because of platform
dependency issues (like trying to reproduce a WDL workflow on a platform that only allows CWL),
or it could be to eliminate the need for an anylyst who undersnd and writes CWL to learn WDL language
in other to quickly use a WDL workflow or it could be to create a more widely available workflow
that can be used by users of either languages and so much more.

# Acknowledgements

We acknowledge the work by the developers of miniwdl, CWL and WDL.

# References