IQSS / social_science_software_toolkit

IQSS best practices and resources for developing social science statistical software

IQSS Social Science Software Toolkit

UNDER DEVELOPMENT. Everything in this repository is under review and subject to change.

Aims

This repository contains IQSS best practices and points to resources for developing statistical software that is:

• robust,

• user-friendly,

• persistent,

• attributable,

• enables reproducible research.

Contributing

If you are interested in contributing to the IQSS Software Development Toolkit, please first read our Contributor Guidelines and Code of Conduct.

Contents

This repository has the following contents:

• IQSS Best Practices for Statistical Software Development

• Guidelines for contributing to the toolkit

• Resources for software testing

• Tools for software citations

• Documents for guiding contributions

• Resources for effective software documentation

• Suggestions for version controlling a statistical software project

• IQSS Report Card: schema for reporting to what extent a piece of statistical software minimally complies with the IQSS Best Practices.

• IQSSdevtools: an R package for initialising, checking, and publishing packages that complie with the IQSS Best Practices.

Maintainers

The following maintainers are responsible the point of contacts for the following components of this toolkit. Please contact them for queries in the relevant areas:

• Dataverse:

• R packages: Christopher Gandrud [e-mail].

• Python packages: