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Open Science & Reproducible Research

An overview and resources on Open Science/Reproducibility

Open science

The Turing Way Community, & Scriberia. (2022). Illustrations from The Turing Way: Shared under CC-BY 4.0 for reuse. Zenodo. https://doi.org/10.5281/zenodo.6821117.

What does "Open Science" mean?

In announcing 2023 as "the year of Open Science", the White House Office of Science and Technology Policy (OSTP), the OSTP set the definition of open science across the U.S. federal government to be "“The principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity.”

Open science has many facets, and practitioners may engage with open science across the spectrum or only in specific areas, such as Open Access publishing (OA) or creating Open Education Resources (OERs).

Areas of Open Science

One early conceptualization of Open Science uses four "instruments of Open Science" to organize different aspects of the movement (Kraker et al., 2011). Since then, the Open landscape has expanded and diversified.

"Open Access"

  • Open Access journal and book publishing
  • Open Educational Resources

"Open Data"

  • Public data sharing
  • Using open licenses for data

"Open Source"

  • Open Source software
  • Public research code sharing
  • Using open licenses for software

"Open Methodology"

  • Preregistration
  • Registered reports
  • Public workflow sharing
  • Sharing equipment setting or instrument calibration information

Open Science can also include Open Hardware and aspects of reproducibility/replicability.

 

Kraker, P., Leony, D., Reinhardt, W., & Beham, G. (2011). The case for an open science in technology enhanced learning. International Journal of Technology Enhanced Learning, 3(6), 643–654. https://doi.org/10.1504/IJTEL.2011.045454

Incremental Approach to Open Science

While making all aspects of your research workflows Open immediately is a laudable but likely unachievable task, small steps that incrementally move your work towards Openness can immediately add value. 

  • Okay practices: Transparency in Output Availability: 
    • Begin by clearly indicating the availability of your research outputs. This simple step promotes transparency and lays the foundation for open sharing.
    • For publications, this might involve stating whether a preprint or open access version exists and providing access links. 
    • For data or software, clearly specify how it can be accessed. 
  • Good practices: Repository Sharing with Basic Metadata: 
    • Progress by depositing your research outputs in appropriate repositories. 
    • For publications, this might include finding Open Access journals, or sharing manuscripts in institutional repositories or preprint servers. 
    • For data and software, utilize specialized repositories. Alongside your outputs, include essential metadata to provide context and facilitate basic understanding.
  • Best practices: Comprehensive Open Sharing with Detailed Metadata:
    • Aim towards sharing your research outputs in repositories with comprehensive metadata and clear licensing. This enables others to fully interpret, reuse, and build upon your work. This level of openness maximizes the impact of your research and fosters greater collaboration.
    • For publications, this involves open access publishing or self-archiving with appropriate licenses. 
    • For data and software, this involves detailed documentation and open source licensing. 
    • Utilize open file formats and infrastructure for the outputs shared

Adapted from Carnegie Mellon University Library's course "How to Open: A Starter Kit for Open Research" under a CC-BY license.

License and reuse

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