pyOpenSci: Open and reproducible research, powered by Python

By

Trizna, Michael
Wasser, Leah
Nicholson, David

Type

Article

Date of Publication

2021-9-27

Original Publication

Metabarcoding and metagenomics

Volume

5

Pages

1--2

Subjects

Apis , data extraction , data retrieval , Open Source , reproducibility , software development

Contributed by

Pensoft Publishers

Language

English

Published by

Bulgaria Pensoft Publishers 2017-

Identifiers

DOI: https://doi.org/10.3897/biss.5.75688

 

Abstract

pyOpenSci (short for Python Open Science), funded by the Alfred P. Sloan Foundation, is building a diverse community that supports well documented, open source Python software that enables open reproducible science. pyOpenSci will work with the community to openly develop best practice guidelines and open standards for scientific Python software, which will be reinforced through a community-led peer review process and training. Packages that complete the peer review process become a part of the pyOpenSci ecosystem, where maintenance can be shared to ensure longevity and stability in code. pyOpenSci packages are also eligible for a “fast tracked” acceptance to JOSS (Journal of Open Source Software). In addition, we provide review for open science tools that would be of interest to TDWG members but are not within scope for JOSS, such as API (Application Programming Interface) wrappers. pyOpenSci is built on top of the successful model of rOpenSci, founded in 2011, which has fostered the development of several useful biodiversity informatics R packages. The pyOpenSci team looks to following the lessons learned by rOpenSci, to create a similarly successful community. We invite TDWG members developing open source software tools in Python to become part of the pyOpenSci community.