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🎓 Purpose

File naming conventions help not only with the organization your research data but are important considerations when it comes to protecting the confidentiality of research participants and other data subjects.

👥Audience

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Initial considerations

Determine your data's classification.

• Classifying your data is an important step in understanding the risks associated with your data.

  • Classify data

  • While secure naming conventions are preferred regardless of data classification, files containing Level 3 and level 4 data should take confidentiality and privacy into account when naming files.

Consult your human ethics or animal use protocol.

• Your human ethics protocols or animal use protocols may outline specific privacy obligations regarding hiding or obfuscating certain types of information, therefore it is important to review your protocol when determining a naming convention.

• If you are unsure about your obligations, please contact the relevant ethics unit.

  • https://research.utoronto.ca/ethics-human-research/ethics-human-research

  • https://research.utoronto.ca/ethics-animal-research-teaching/ethics-animal-research-teaching

\uD83D\uDCD8 What can I do?

Consult with the Research Data Management experts within U of T Libraries.

• https://onesearch.library.utoronto.ca/researchdata/organizing-your-data

• Consistently formatted and descriptive filenames that avoid using special characters and spaces help to:

  • clearly outline the purpose and content of a file,

  • improve search functionality and organization of project,

  • reduce the chance of unintentional, unauthorized access or transfer,

  • reduce the chance of duplication and/or misplacement of data,

  • reduce the chance of errors or corruption during transfer.

Avoid including sensitive or confidential information in filenames.

• Sensitive or confidential information should not be included within filenames, as it may expose the personal and/or private information of data subjects, project members, or the University to unauthorized individuals.

  • Such information may include, but is not limited to:

    • direct identifiers, such as: names, addresses, phone numbers, email addresses, government-issue identification numbers, etc.,

    • indirect identifiers, where in conjunction with other local data elements, could identify an individual, such as: geographic indictors, birth dates, etc.