Research Data Management

Finding data that you or your colleagues have created can be challenging as your data and files increase over time. They can very quickly become disorganised and unmanageable if the proper data organisation is not in place.

It is worth investing some time at the start of a project to plan how you will name and structure your files and folders. Good folder organisation and file naming strategy will help you to quickly find the files you need, to easily understand what a particular data file is and what it contains, and to differentiate between different files and different versions of the same file.

A logical folder structure facilitates access to your files and avoid duplication. Here are some tips on creating a file folder hierarchy:

• Think about how you or others will look for and access the files at a later date. By data type? By time period? By location? By instrument? etc.

• For instance, you might organise your files in folders according to types of:
  • Data – databases, text, images, models, sound
  • Research activities – interviews, surveys, focus groups
  • Material – data, documentation, publications

• Consider the best hierarchy for files, aim for a balance between breadth and depth (the UK Data Service recommends restricting the level of folders to three or four deep and not to have more than ten items in each list)

• Establish a folder hierarchy that aligns with the project
• Example: [Project] / [Experiment] / [Instrument or Type of file]

• Create a folder for documentation - it may include data dictionaries, lab or field notebooks, metadata, procedures, and anything else that would help you or others understand your research

Example Folder Structure

Here is an example from the UK Data Service, data and documentation files are held in separate folders.

Data files are further organised according to data type and then according to research activity.

Documentation files are organised also according to type of documentation file and research activity.

More tips:

• Use any existing conventions, e.g. in your research group, academic cluster or department
• Create separate folders for current/ongoing and completed work
• Review your file structure regularly and remove any unnecessary files

(Source: Cambridge University Library; MIT Libraries; UK Data Service)

File names should provide context for the files that they name, and distinguish them from files that may be similar.

Best practices include:

• Be consistent
  • Have conventions for naming (1) Directory structure, (2) Folder names, (3) File names
  • Always include the same information (e.g. date and time)
  • Retain the order of information (e.g. YYYYMMDD, not MMDDYYYY )
  • Document your file naming conventions
  • Include a README.txt file in the documentation folder that explains your naming convention along with any abbreviations or codes you have used

• Be descriptive (so others can understand your meaning)
• Include other relevant information such as:
  • Unique identifier (i.e. Project Name or Project ID or Grant ID in folder name)
  • Project name
  • Conditions (Lab instrument, Solvent, Temperature, etc.)
  • Run of experiment (sequential)
  • Date (in file properties too)
  • Use application-specific codes in 3-letter file extension: MOV, TIF, WRL

Example: Project_instrument_location_YYYYMMDD[hh][mm][ss][_extra].ext

Version control involves a process of naming and distinguishing between a series of draft documents which lead to a final (or approved) version.

• Use a sequential numbered system: v1, v2, v3, etc.
• Don't use confusing labels: revision, final, final2, etc.
• Consider version control software, if applicable
• Record all changes -- no matter how small
• Discard obsolete versions (but never the raw copy)
• Use auto-backup instead of self-archiving, if possible
• Avoid using slashes in file names (/ or \)

(Source: NC State University Libraries)