Sharing analysis code & software

No Action (Qual.)

Analytic code, workflows, or project files are not shared. Analyses are conducted using undocumented or inaccessible methods, with little transparency about coding processes, software use, or interpretive decisions.

Moving from No Action to Emerging in Sharing Analysis Code/Software (Qual.)

1. To progress from No Action to Emerging, begin developing habits that make your analytic process clearer, more transparent, and easier to revisit or share responsibly. These steps will help you organise your work and prepare for future ethical sharing.
2. Annotate Your Workflows or Coding Files. Add short notes or comments within your analytic software (for example, NVivo, ATLAS.ti, or RQDA) explaining the purpose of each coding stage or script. Use consistent naming conventions for codes, memos, and files so that others--and your future self--can follow the logic of your analysis.
3. Record Your Software Environment. Note the software, version number, and any custom settings or plug-ins used in your analysis. This helps others understand your technical setup and supports reproducibility within qualitative frameworks.
4. Create Basic Documentation
   Write a simple README file that explains:
   • The purpose of the analysis
   • The research context and type of data analysed
   • The structure of your folders or files
   • How the analysis was conducted (for example, coding, memo writing, or text analysis)
   • Any dependencies or tools required to open the project
5. Choose a Platform for Sharing. Create an account on a trusted repository such as the Open Science Framework (OSF), Zenodo, or your institutional repository. Begin experimenting with uploading non-sensitive materials, such as templates, codebooks, or synthetic data, even privately at first.
6. Review Ethical and Confidentiality Considerations. Check your institutional and funder policies on data sharing, anonymisation, and participant consent. Consider whether any of your analytic materials could reveal identifiable information. When uncertain, consult your ethics board or data protection officer before sharing.

Emerging (Qual.)

Some qualitative analysis files or workflows are shared upon request, but sharing is informal and inconsistent. Documentation and contextual information are limited, making it difficult for others to understand the analytic process or reuse the materials responsibly.

Moving from Emerging to Evolving in Sharing Analysis Code/Software (Qual.)

1. To progress from Emerging to Evolving, focus on organising and documenting your qualitative analysis materials so others can understand your analytic process and reuse your workflows responsibly.
2. Add a README File. Create a clear README file to accompany your qualitative materials. Describe:
   • The purpose of the project and type of data analysed
   • The structure of your files and folders
   • The software or tools required to open and view them
   • The analytic stages or steps represented (for example, coding, theme development, or memo writing)
   • The outputs provided (for example, codebooks, thematic maps, or anonymised excerpts). A well-written README helps others navigate your materials and understand your analytic logic.
3. Record Your Software Environment. Document the software, version, and file types used (for example, NVivo 14, ATLAS.ti 23, RQDA, or .qpf/.nvp/.xlsx files). Note any scripts, macros, or plug-ins that shaped your analysis. This information supports transparency and helps others replicate or adapt your workflow.
4. Upload to a Trusted Platform. Choose a suitable repository for storing your qualitative materials:
   • Open Science Framework (OSF) for codebooks, analytic frameworks, and project organisation
   • Zenodo for permanent archiving and DOI generation
   • Qualitative Data Repository (QDR) for qualitative data, documentation, and contextual materials
     Even if you cannot share raw transcripts, you can upload codebooks, analytic templates, methodological notes, or anonymised excerpts to make your approach transparent.
5. Address Ethical and Confidentiality Considerations. Review your materials to ensure they do not contain identifiable or sensitive information. Remove or mask participant details where possible, and consider using synthetic or redacted examples. When uncertain, seek advice from your ethics board or research governance office.

Evolving (Qual.)

Qualitative analysis files or workflows are shared in trusted public repositories with basic documentation, contextual notes, and an open licence. Efforts are made to make the analytic process understandable and the materials reusable by others in a responsible manner.

Moving from Evolving to Sustained in Sharing Analysis Code/Software (Qual.)

1. To move from Evolving to Sustained, focus on enhancing the transparency, ethical integrity, and reusability of your qualitative analysis materials.
2. Refine Documentation and Contextual Clarity. Ensure your materials—such as codebooks, analytic memos, thematic frameworks, or software project files (for example, NVivo, MAXQDA, or ATLAS.ti)—are well organised and accompanied by a detailed README file. The README should explain the purpose of each item, the analytic steps taken, how themes or codes were developed, and any dependencies or software versions required.
3. Implement Version Control and Traceability. Keep track of changes to your analytic materials using version control systems such as Git or by saving dated versions within your repository. Record the software and version used, along with any plug-ins, scripts, or templates that shaped your analysis. This documentation supports transparency and helps others trace how interpretations evolved.
4. Share Through Trusted Repositories. Deposit your qualitative materials and documentation in secure and sustainable repositories such as the Open Science Framework (OSF), Zenodo, or the Qualitative Data Repository (QDR). These platforms allow for detailed metadata, version tracking, and the assignment of a Digital Object Identifier (DOI) to make your materials permanently citable.
5. Clarify Licensing and Ethical Practices. Apply a clear open licence such as CC BY 4.0 to specify reuse permissions. Ensure that all shared materials comply with ethical and confidentiality standards by anonymising or redacting identifiable content. Where full data cannot be shared, provide synthetic datasets, exemplar excerpts, or redacted samples to illustrate your analytic approach.
6. Promote Reuse and Mentorship. Reference your shared materials and DOIs in publications, teaching, and presentations to model good open research practice. Encourage responsible reuse by providing reflexive notes and guidance on how the materials should be interpreted and cited. Track engagement through repository metrics to monitor impact and improve your sharing practices over time.

Sustained (Qual.)

Qualitative analysis materials, including codebooks, analytic memos, and project files, are consistently shared through trusted repositories such as the Open Science Framework (OSF) or the Qualitative Data Repository (QDR). Materials include detailed documentation, contextual and reflexive information, version control, and clear open licensing to ensure ethical integrity, transparency, and meaningful reuse.

Guidance for Sustained Level in Sharing Analysis Code/Software (Qual.)

Congratulations. You are operating beyond good practice and contributing as a field leader in open and ethically grounded qualitative research.

At this stage, qualitative analysis materials are consistently shared through trusted, openly accessible repositories such as the Open Science Framework (OSF), Zenodo, or the Qualitative Data Repository (QDR). All materials are well structured, version-controlled, and accompanied by comprehensive documentation that includes. To maintain and further improve at this level, consider the following:

• README: A clear overview of the project’s purpose, analytic focus, and structure, explaining how files relate to different stages of the analysis (for example, coding, theme development, or memo writing).
• Context and Reflexivity: Notes detailing the research context, researcher positionality, and interpretive decisions made during the analytic process.
• Annotations: Embedded comments within codebooks, analytic memos, or software projects that explain how codes were developed, refined, and linked to broader themes or theoretical insights.
• Software Environment: Details of the tools used (for example, NVivo, MAXQDA, or ATLAS.ti), including software versions, file types, and any plug-ins or scripts that support replication of the workflow.
• Licence: A clear open licence, such as CC BY 4.0, that specifies reuse permissions while protecting ethical boundaries.
• Version History: A changelog or dated project versions that document the evolution of the analysis and allow others to trace interpretive development.
• Ethics and Confidentiality: Sensitive or identifying content removed or redacted, with transparent guidance on what has been withheld and why. Synthetic examples, anonymised excerpts, or exemplar codebooks may be provided where appropriate.