Managing large amounts of qualitative data effectively is crucial for the integrity and efficiency of your research. A clear, consistent file naming and folder structure will save you immense time and prevent headaches down the line.

Here's a comprehensive system designed for qualitative data, emphasizing clarity, consistency, and scalability:

Qualitative Data Management System: File Naming & Folder Structure

Core Principles for Success:

• Consistency is Key: Once you decide on a convention, stick to it rigidly.


• Be Specific & Descriptive: File names and folder names should immediately tell you what's inside.


• Machine-Readable: Avoid spaces ( ), use underscores (_) or hyphens (-). Keep names relatively short but informative.


• Chronological Sorting: Use YYYYMMDD format for dates at the beginning of file names to ensure proper sorting.


• Hierarchical: Structure from broad categories down to specific items.


• Redundancy (Managed): Sometimes it's okay for similar files to exist in different places (e.g., raw audio vs. transcribed text), but their file names should reflect their status.


• Anonymity/Confidentiality: Build in mechanisms for anonymizing participant IDs from the outset.

1. Folder Structure (Project-Level)

Start with a top-level folder for your entire research project. Within this, create a logical hierarchy. Numbering folders often helps maintain a preferred order in file explorers.

├── [Project_Name_YYYY] / (e.g., YouthMentalHealth_2023)
│
├── 00_Project_Administration
│   ├── Ethics_IRB
│   │   ├── Application_Submitted_YYYYMMDD.pdf
│   │   ├── Approval_Granted_YYYYMMDD.pdf
│   │   └── ConsentForms_Template_v01.docx
│   ├── Proposals_Grants
│   │   ├── Proposal_Draft_v01.docx
│   │   └── GrantApplication_Final_v01.pdf
│   ├── Team_Contacts_Roles.xlsx
│   ├── Meetings
│   │   ├── YYYYMMDD_MeetingMinutes.docx
│   │   └── YYYYMMDD_Agenda.pdf
│   └── DataManagementPlan_v01.pdf
│
├── 01_Data_Collection (Raw, Unmodified Data)
│   ├── Interview_Audio
│   │   ├── YYYYMMDD_P001_Audio_Int.mp3
│   │   └── YYYYMMDD_P002_Audio_Int.m4a
│   ├── Interview_Notes
│   │   ├── YYYYMMDD_P001_Notes_Int.docx
│   │   └── YYYYMMDD_P002_Notes_Int.pdf
│   ├── FocusGroup_Audio
│   │   ├── YYYYMMDD_FG001_Audio.mp3
│   │   └── YYYYMMDD_FG002_Audio.mp3
│   ├── Observation_FieldNotes
│   │   ├── YYYYMMDD_Obs_LocationX_ResearcherY.docx
│   │   └── YYYYMMDD_Obs_EventA_ResearcherZ.pdf
│   ├── Documents_Secondary
│   │   ├── Policy_SchoolA_Discipline_2022.pdf
│   │   ├── Report_LocalCouncil_YouthPrograms_2021.pdf
│   │   └── Website_Screenshot_OrgB_AboutUs_YYYYMMDD.png
│   ├── Visual_Data (Photos, Videos, Art)
│   │   ├── YYYYMMDD_P003_Drawing_01.jpg
│   │   └── YYYYMMDD_EventC_Video_01.mp4
│   └── Survey_OpenEnded_Raw (if applicable, export from survey tool)
│       └── SurveyExport_OpenEnded_YYYYMMDD.xlsx
│
├── 02_Data_Processing (Transcripts, Anonymization, Cleaning)
│   ├── Interview_Transcripts
│   │   ├── YYYYMMDD_P001_Transcript_Int_v01_raw.docx
│   │   ├── YYYYMMDD_P001_Transcript_Int_v02_clean.docx (Anonymized)
│   │   └── YYYYMMDD_P002_Transcript_Int_v01_clean.pdf
│   ├── FocusGroup_Transcripts
│   │   ├── YYYYMMDD_FG001_Transcript_v01_raw.docx
│   │   └── YYYYMMDD_FG001_Transcript_v02_clean.docx
│   ├── Processed_ObservationNotes
│   │   └── YYYYMMDD_Obs_LocationX_clean.docx
│   ├── Cleaned_Secondary_Docs
│   │   └── Policy_SchoolA_Discipline_2022_Annotated.pdf
│   └── Anonymization_Log_Key.xlsx (Crucial! Links real IDs to anonymous IDs)
│
├── 03_Analysis (Coding, Memos, Software Files)
│   ├── Qualitative_Software (e.g., NVivo, ATLAS.ti, Dedoose)
│   │   ├── NVivo_Project_YouthMH_YYYYMMDD.nvp
│   │   ├── NVivo_Backup_YYYYMMDD.nvp
│   │   └── ATLAS_ti_Project_YouthMH_YYYYMMDD.ti8
│   ├── Memos_Reflexivity
│   │   ├── YYYYMMDD_Memo_InitialThoughts_TopicX.docx
│   │   ├── YYYYMMDD_Memo_CodingStrategy_Phase1.docx
│   │   └── YYYYMMDD_Reflexivity_JournalEntry.docx
│   ├── Coding_Schemes
│   │   ├── Codebook_v01_initial.docx
│   │   └── Codebook_v02_final.xlsx
│   ├── Thematic_Analysis_Worksheets
│   │   ├── Theme_Development_Sheet_v01.docx
│   │   └── Theme_Mapping_Diagram_v01.pptx
│   └── Data_Excerpts (e.g., coded snippets exported from software)
│       └── ThematicExcerpts_SupportNeeds.docx
│
├── 04_Outputs (Reports, Publications, Presentations)
│   ├── Reports
│   │   ├── InternalReport_YouthMH_Draft_v01.docx
│   │   └── FinalReport_YouthMH_Published_YYYYMMDD.pdf
│   ├── Publications
│   │   ├── JournalArticle_MentalHealth_Manuscript_v01.docx
│   │   └── ConferencePaper_YouthServices_Published.pdf
│   ├── Presentations
│   │   ├── Stakeholder_Presentation_v01.pptx
│   │   └── Conference_Poster_v01.pdf
│   └── Media_Dissemination
│       └── PressRelease_YouthMH_YYYYMMDD.docx
│
└── 99_Archive (Final versions of everything, read-only)
    └── [Project_Name_YYYY]_FINAL_ARCHIVE_YYYYMMDD.zip

2. File Naming Conventions

The core idea is to include the most critical information at the beginning of the file name, allowing for logical sorting and quick identification.

General Format:
YYYYMMDDIdentifierDataTypeVersionBriefDescription.extension

Elements Explained:

• YYYYMMDD (Date):


• Purpose: Ensures chronological sorting. Date of data collection or creation of the file.


• Format: YYYYMMDD (e.g., 20231026)


• Example: 20231026


• Identifier (Participant/Group/Source ID):


• Purpose: Links data to its source. Crucial for anonymity.


• Format:


• Individuals: P001, P002 (for Participant 001, 002). Do NOT use real names or identifying numbers here. Maintain a separate, secure AnonymizationLogKey.xlsx in your 02DataProcessing folder that links P001 to Jane Doe's real name.


• Focus Groups: FG001, FG002 (for Focus Group 001, 002).


• Observations: ObsLocationX, ObsEventA (descriptive of the observation).


• Documents: OrgAPolicy, ReportCouncilB (source and type).


• Example: P001, FG001, ObsParkVisit, SchoolAPolicy


• DataType (Type of Data):


• Purpose: Identifies the nature of the file.


• Format: Short, descriptive codes.


• Examples:


• Audio_Int (Interview Audio)


• Notes_Int (Interview Notes)


• Transcript_Int (Interview Transcript)


• Audio_FG (Focus Group Audio)


• Transcript_FG (Focus Group Transcript)


• FieldNotes (Observation Field Notes)


• PolicyDoc (Policy Document)


• Report (Research Report)


• Photo


• Video


• Memo


• Codebook


• Presentation


• Version (Versioning):


• Purpose: Tracks changes and iterations, especially important for transcripts and analysis.


• Format: v01, v02, v03 (for versions). Can also include status like raw, initial, clean, final.


• Example: v01raw, v02clean, v03_final


• BriefDescription (Optional but Recommended):


• Purpose: Adds extra context if needed, especially for documents or memos.


• Format: Concise, use hyphens for readability.


• Example: SuicidePrevention, YouthEngagement, Phase1Coding


• .extension (File Type):


• Purpose: Standard file extension.


• Examples: .mp3, .docx, .pdf, .xlsx, .nvp, .jpg

Examples of File Naming:

Raw Data:

• 20231026P001AudioIntv01.mp3 (Interview audio from Participant P001, collected Oct 26, 2023, version 1)


• 20231026P001NotesIntv01.docx (Field notes from the same interview)


• 20231101FG001Audio_v01.mp3 (Focus Group 001 audio, Nov 1, 2023)


• 20230915ObsParkVisitResearcherAv01.docx (Observation notes from a park visit by Researcher A, Sep 15, 2023)


• 20230801PolicyDocSchoolADisciplinePolicy2022.pdf (Policy document from School A)


• 20231110P003Art_SelfPortrait.jpg (Visual data - Participant P003's self-portrait, Nov 10, 2023)

• 20231026P001TranscriptIntv01_raw.docx (Initial transcript, not yet anonymized)


• 20231026P001TranscriptIntv02_clean.docx (Cleaned and anonymized transcript, ready for analysis)


• 20231101FG001Transcriptv02clean.docx (Cleaned and anonymized Focus Group transcript)


• 20230915ObsParkVisitResearcherAv02_processed.docx (Processed and anonymized observation notes)

• 20231205MemoInitialCodingThoughts_ThemeA.docx (Memo about initial coding for Theme A)


• 20231210Codebookv01_Initial.xlsx (Initial version of your codebook)


• 20240115NVivoProjectYouthMHv03_PostCoding.nvp (NVivo project file after a round of coding)


• 20240120ExcerptsTheme_CopingStrategies.docx (Exported data excerpts related to 'Coping Strategies')

• 20240201ReportDraftYouthMHv01.docx


• 20240315PresentationStakeholderMeeting_v01.pptx

Key Considerations & Best Practices:

• Anonymization Log: Create a highly secure, separate file (e.g., AnonymizationLogKey.xlsx) that links your anonymized participant IDs (P001, FG001) to their real names or contact details. This file should be stored separately, ideally encrypted, and accessed only when absolutely necessary and by authorized personnel.


• README.txt Files: In each major folder (e.g., 01DataCollection, 02DataProcessing), include a README.txt file. This file should explain:


• The purpose of the folder.


• The file naming conventions used within that folder.


• Any specific abbreviations or codes.


• The date the folder was last updated.


• Data Dictionary/Codebook: For your entire project, maintain a master data dictionary or codebook (e.g., ProjectCodebookv01.xlsx in 00ProjectAdministration). This defines:


• All participant IDs and their associated demographic data (without direct identifiers).


• Any specific codes or abbreviations used in file names.


• Definitions of your analytical codes.


• Back-Up Regularly: Store your data in a secure, backed-up location (e.g., institutional server, cloud storage with versioning). Follow the "3-2-1 rule": 3 copies of your data, on 2 different media, with 1 copy off-site.


• Start Early & Train Your Team: Implement this structure from day one. If working with a team, ensure everyone understands and adheres to the conventions. Conduct a brief training session and provide a cheat sheet.


• Review and Adapt: Periodically review your structure. As your project evolves, you might discover a need for minor adjustments. Document any changes in your README.txt or data management plan.