Qualitative project
Before
Transcripts, consent files, notes, and drafts mixed together
After
Restricted Admin, Data/Raw, Data/Processed, Analysis, and Manuscript
Direct answer
Researchers need a project structure that separates literature management, immutable raw data, processing, analysis, outputs, manuscripts, and administration. Use specialist tools for citations and version control, and use local file organization to keep the broader project archive consistent.
Reviewed and updated 2026-06-14
A research project spans more than papers
Citation libraries solve only one part of the problem. Ethics approvals, consent forms, protocols, meeting notes, code, datasets, figures, and manuscripts each need appropriate access and retention.
Automated organization must respect institutional policy. Confidential or regulated files may require approved storage, encryption, access controls, and local-only processing.
Step-by-step workflow
- Create a documented project template before data collection starts.
- Keep raw data immutable and separate from transformed data.
- Store papers in a citation manager and project-specific notes in the project.
- Archive the project with a readme, environment details, and retention notes.
Use-case examples
Computational project
Before
Code, generated figures, and downloaded datasets in one folder
After
Code, Data, Results, Figures, Docs, and reproducibility metadata
Research workflow roles
No single organizer should replace citation, data, and versioning controls.
| Option | Best for | Tradeoff |
|---|---|---|
| Foldora | Local cleanup and categorization of mixed project documents | Not a repository, citation manager, or electronic lab notebook |
| Research repository | Preservation, sharing, identifiers, and governance | Not a daily desktop cleanup tool |
| Version control | Code and text history | Large binary data needs additional tooling |
Frequently asked questions
Can AI organize human-subject research files?
Only when the workflow complies with institutional approvals and data policy. Local processing helps but does not replace governance.
Where should raw data be stored?
Use approved storage, keep raw data unchanged, restrict access where required, and document every transformation into processed datasets.
Should papers be copied into every project?
Usually no. Keep one citation-managed library and store project-specific notes, exports, or links with each project.
Related guides
Organize a folder with Foldora
Run local AI on Windows, review the proposed structure and filenames, then apply the changes you approve.
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