There are plenty of options for organizing your data in TUM eLabFTW. Instead of employing a folder system, this system works by assigning tags, categories and certain status to describe entries.
Metadata instead of Folders 👤🟩👥🟦
TUM eLabFTW does not support folder creation for organizing entries. It is designed around a metadata-driven organization rather than traditional folder structures. This approach promotes flexibility, scalability, and powerful search capabilities.
Use tags, categories, and custom metadata fields to classify and filter your entries. This allows you to apply multiple labels to a single entry, making it easier to find and group related content without being locked into a single folder path.
Using Tags 👤🟩👥🟦
Tags help organize your entries by labeling them with keywords. They replace traditional folder structures and make it easier to sort, group, and search for content.
By default, tags can be freely assigned by users. However, team admins can restrict this feature, forcing users to use already existing tags.
Maintaining Tag Quality 👥🟦
Since users can create tags freely, it’s a good idea for admins to review them occasionally. In the admin panel, use the Tag Manager to rename tags for consistency. Use the de-duplicate function to merge similar or identical tags.
Using Categories 👤🟩
Team admins can create experiment categories to help organize the team’s work. These categories make it easier to sort and find experiments based on their type or purpose.
If you are a team member and want to group related experiments or resources, consider using tags or linking them to a shared project resource. This approach keeps your work connected and easy to navigate, even without predefined categories.
Managing Categories 👥🟦
Categories are used to group related experiments and resources. These are created and managed by team admins. It’s helpful to plan your categories early, based on the types of work your team expects to do. This avoids the need for time-consuming reorganization later on.
Keep categories broad and practical: just detailed enough to be useful, but not overly complex. You can create categories and assign color codes in the team admin settings (link to official documentation).
Examples
💡 Best Practice: Think about experiment and resource categories early in the research project.
Examples of experiment categories might include:
wet lab, in silico, simulation, interview, poll, scraping, archival analysis, case study, field work, text processing
Examples of resource categories might include:
lab equipment, protocols, chemicals, rooms, antibodies, datasets, guidelines, software, vehicles
Categories as Templates
💡 Best Practice: Resource categories also have the double function of serving as templates for resources. Read about these templates in the section on Templates.
Using Status 👤🟩
Status labels help track the progress of experiments and resources. Status labels are pre-defined by your team-admin. You should use status labels to indicate in which state or phase your experiment or resource currently is in.
Managing Status Options 👥🟦
Status labels help track the progress of experiments and resources. These can be customized to fit your team’s workflow. Keep the number of status options manageable, ideally fewer than ten.
Some useful examples include: archival, publishing, running, success, fail, planning
