Applying standards to the structure and organisation of research data will improve the management, access, and re-use of the data. A sound strategy to the organisation of data is particularly important in team projects where more than one person will be accessing and analysing the data. Where possible, consider automated methods to save time.
Digital file names can be important for identifying and finding a digital file. Researchers should develop an organised electronic filing system where everyone involved in data collection, analysis, reuse, and storage understands the file naming protocols.
The most important things to remember about file naming are to be consistent and descriptive in naming and organizing the files. The use of good naming conventions provides a useful cue to the content and status of a file, including its version. Select an appropriate naming convention for your files as early as possible and follow it throughout your research.
The use of good naming conventions provides a useful cue to the content and status of a file, including its version. The following examples highlight basic principles of file naming.
Developing a system to organise files requires consideration of good naming conventions, consistency of terms used and a development of a coherent and consistent folder structure. This will ensure it is easy to locate, organise and navigate all files and versions.
The UK Data Archive provides an example of a well-organised folder structure.
Version control is necessary when data is constantly updated and/or is accessed by more than one person and can be implemented by agreeing on a standard for naming files or folders. For example:
You can find more information about data version control under the More resources sidebar on this page.
This is an example data organisation and structure from the data management plan for a fictitious research project:
Physical data sheets will be sorted by date in a single folder.
Digital records will be organised in a simple hierarchical structure e.g.
The photos will be named according to the partial species ID, survey number, date and time the photo was taken e.g.
The survey analysis file will be worked on and updated regularly. Weekly snapshots of the data file will be made, and each snapshot will be date stamped for easy identification e.g.
The digital record of transcribed survey data and survey analysis will be kept in Excel 2010 xlsx format. Photographs will be originally shot in RAW, but processed to JPEG in Adobe Lightroom.