Already during data collection, a consistent filing and folder structure can lay the foundation for later traceability of the data.
Are there guidelines or best practices for a consistent filing and folder structure?
Data should always be prepared in a way that makes them easy to understand and locate — both for oneself and for others. This is particularly important for colleagues who may need access to the same information, as well as for future or external researchers who wish to engage with the data. A hierarchical structure facilitates findability.
Prior planning of the data storage and folder structure should also be part of a Data Management Plan (DMP). It should specify:
- The criteria according to which files will be structured.
- The agreed naming conventions.
- How version control (including version numbers and storage dates in the YYYYMMDD format) will be ensured.
- At which project phase (especially for team projects) “milestone versions” will be saved that can no longer be modified and are stored in a designated location.
A special case of data storage is Electronic Lab Notebooks (ELNs). They offer a digital platform for systematically and structurally documenting laboratory results, experimental protocols, and observations. Unlike traditional paper lab notebooks, ELNs improve traceability and accessibility of data, as they often include search functions and allow the integration of images, tables, and even raw data directly into the document.
Which naming conventions and structures are used for data organization?
The goal of naming conventions is to clearly identify content. This enhances findability, as the content can be recognized before opening a file. Relevant files can thus be identified more quickly, resulting in significant long-term efficiency gains. Naming conventions create a consistent and transparent structure that benefits both individual work and collaboration.
Recommendations
- Short, clear, consistent, and content-related file names
- Avoid generic names (e.g., “data”)
- Avoid spaces, special characters (e.g., &?! #@%), periods, and umlauts
- Use capital letters and underscores “_” to separate parts of a file name (e.g., InterviewQuestionnaire or Interview_Questionnaire)
- Include the file format at the end of the name (e.g., .docx, .mp3, .xlsx)
Typical file name components
- Editing status (e.g., original, draft, revised)
- Keyword or short title (e.g., interview, video, questionnaire)
- Version number (to document changes)
- Date (in the format YYYYMMDD)
- Serial number (e.g., for multiple audio files per interview)
- Project number or ID (e.g., JB007)
- Name of the research team/department and/or researcher initials (e.g., OIS)
Hier finden Sie Textbausteine für informierte Einverständniserklärungen.
Welche Datenschutzregelungen bestehen während der Erhebungsphase?
Datenschutz während der Erhebungsphase erfordert eine transparente Aufklärung über die geplante Verwendung der gesammelten Daten sowie die Einholung informierter Einwilligungen der Teilnehmenden.
Aber auch das Speichern von personenbezogenen Daten auf nicht öffentlich zugänglichen Laufwerken kann hier relevant sein.
Bei Unsicherheiten kann der der HSLU weiterhelfen, um zu prüfen welche Regeln Sie einhalten müssen.
Here you will find text templates for informed consent forms.