Research Guides: Open Science: Open Code and Software

Useful Guides

Research Data Management
by Wasila Dahdul Last Updated Apr 22, 2024 1308 views this year
Software for Data Analysis
by Danielle Kane Last Updated Feb 15, 2024 15051 views this year
Scholarly Communication & Related Issues
by Mitchell Brown Last Updated Apr 4, 2024 338 views this year

Open Code & Software

Data and code are at the core of much research and scholarship. Making your data and code open can lead to increased research impact, improve reproducibility, and allow new discoveries and research through reuse.

The Open Definition defines Open Data as data that "can be freely used, modified, and shared by anyone for any purpose."

Some forms of research funding expect data resulting from a project to be shared. For example, the National Science Foundation's policy on the Dissemination and Sharing of Research Results states that investigators are expected to share primary data, samples, and other supporting materials. Other US Federal agencies have or are adopting similar policies.

Sharing Data, Code or Both?

Sometimes data can be shared alone, but there are times when there are scripts or research code that are critical to being able to understand the context and use of the data. In these cases it's crucial to share not only the data, but also any relevant code. Some data repositories allow data and code to be shared together, while others only accept data. Another approach is the one taken by Zenodo, which is a domain-general data repository that allows researcher to link directly to their code in Github. However the data and code are made available, it's important to document how they go together.

Conversely, you may have research code that could apply to all kinds of other data and would like to share that code openly. There are number of good options for sharing code, as well as some additional considerations (see below).

Sharing versus Publishing

You can share your data in a number of ways, and it can be tempting to simply store it on a platform like DropBox or Google and share a link to it, or to otherwise share it informally. However, sharing your data by publishing it in a data repository has a number of important advantages:

Citable: Get a unique, persistent, citable link like a DOI to make it easier for others to give you credit for your work
Re-usable: Some repositories offer professional data curation services to help ensure your data is re-usable
Lasting: Long-term preservation practices means your data will still be available in the years to come

Tools and Resources

NIH-Supported Data Sharing Resources
To help researchers locate an appropriate repository for sharing or accessing data, BMIC maintains lists of data sharing repositories. Domain-specific repositories are typically limited to data of a certain type or related to a certain discipline.
Open Data Commons
Open Data Commons is the home of a set of legal tools and licenses to help you publish, provide and use open data.
Open Data Handbook
This guide discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to open up data. It discusses why to go open, what open is, and the how to 'open' data.
OSI Approved Licenses
Open source licenses are licenses that comply with the Open Source Definition – in brief, they allow software to be freely used, modified, and shared. To be approved by the Open Source Initiative (also known as the OSI) a license must go through the Open Source Initiative’s license review process.
The Turing Way
Welcome to The Turing Way handbook to reproducible, ethical and collaborative data science. The Turing Way project is open source, open collaboration, and community-driven. We involve and support a diverse community of contributors to make data science accessible, comprehensible and effective for everyone.