During Research

Organizing data is essential to ensure clarity, traceability, and reuse. Good practices in file naming, versioning, and file formats facilitate efficient information management.

  • File Naming
    Use standardized names that include essential information (date, data type, version).
    Ex: 20260129_ProjectA_EnvironmentalData_v1.csv
  • Versioning
    Clearly identify different file versions, allowing tracking of changes over time. This can be done manually, through tables, or using software.
    Ex.: v1, v1.1, v2
  • File Formats
    Adopt open and widely compatible formats to facilitate access, reuse, and preservation of data.
    Ex.: .csv, .txt,


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Documenting data involves systematically recording all information necessary to interpret, validate, and reuse the data and software generated during research.

Examples:

  • Laboratory Notebooks: Physical or digital, for recording data, notes, and structured observations.
  • README Files: Simple texts describing the organization, content, and format of data files.
  • Data Dictionaries / Code: Documents detailing variables, data types, units, and possible values.
  • Code Comments: Explanatory notes describing the function, logic, and use of scripts or software.
  • Supporting Documents: Protocols, questionnaires, forms, or other materials providing additional context for the data.
  • Whenever possible, use appropriate metadata standards and controlled terms (e.g., vocabularies, ontologies, and thesauri) to improve clarity and interoperability.


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Data should be stored securely with regular backups to ensure integrity and prevent loss.

  • Centralized and Secure Storage: Store data on institutional servers, research platforms, or trusted repositories, avoiding personal devices whenever possible.
  • Regular Backups: Create automatic or manual backups in locations separate from the primary storage.
  • Versioning and Change Control: Keep track of file versions to ensure traceability.
  • Standardized Organization: Maintain the project’s folder structure and file naming conventions.
  • Protection and Access: Use passwords, encryption, or access permissions for sensitive data.


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Documenting and managing research data requires adherence to ethical and legal standards, ensuring participant protection, privacy, and responsible data use.

  • Personal Data Protection: Apply anonymization or pseudonymization to safeguard sensitive information.
  • Informed Consent: Ensure that all participants agree to the collection, processing, and use of their data.
  • Licensing and Copyright: Respect intellectual property rights, licenses, and institutional data-sharing policies.
  • Legal Compliance: Follow national and international regulations, such as the GDPR.
  • Ethical Decision Records: Document ethics committee approvals, consent protocols, and relevant authorizations.


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