Research file management: time to get organised
Save yourself time and effort in the long run by adopting good organisation practices
The number of files generated over the course of a research project can be overwhelming. To ensure that you can easily find what you need when you need it, here are some tips and techniques that will help you manage your data.
Key principles of file organisation
Good file organisation should be:
Consistent
There are many different methods for naming files and structuring folders but the key is to apply it to all files. So, if you start using a naming convention, apply this to all of your files. Likewise, if you use a folder structure in one folder, apply to all other folders and subfolders. This will make it easier for you to quickly find the file you are looking for in future.
Meaningful to you and your colleagues
A filename reading ‘meetingnotes’ might mean something to you now, but will the same be true in a couple of months or years? A lack of detail in filenames could make it more difficult for you to find information you need later on in your project, costing you time and effort. Choose a file naming convention that gives you all the details you need to know exactly what is contained in each file. If you are working in a team, make sure that all team members are using the same naming convention and file structure to make sure nothing important gets lost!
File structure
Using a file structure like the one above will help you to organise a large number of files into subfolders so that you can quickly and easily find relevant documents. Adopting a file structure early in a project can save you a great deal of time later on. File structures like this can be replicated across a variety of different projects.
Naming convention
The above image shows the naming convention used by the Division of Technology, Information and Learning Support at Queensland University of Technology. This naming convention can be broken down as follows:
Prefix: A three letter code that denotes what kind of file it is e.g. GDL for guidelines, PRE for presentation, TEM for template, etc. Use upper case for this.
Document Title: A couple of words that outline the content of the file e.g. TILSDocNaming, ResearchDataManagement, InternalFundingApplication, etc. Capitalise the start of each word to make it easier to read.
Version Number: For documents that will continue in various versions use V followed by the version number. New versions should not be created after significant changes have been made to the document or when it has been reviewed or changed by another author.
Date: Using the YYYYMMDD format will allow you to sort your files into date order easily.
Metadata, documentation and README files
Metadata is data about other data. It is structured information about your data in standards recognised in your discipline e.g. title, authors, license.
Documentation is detailed information about what is in your dataset (filenames, units, software required) and the methodology used (calibration of instruments, quality controls).
A README file is an easy way to capture all of the supplemental information needed to understand your data. Simply create a .txt file at the start of your project and use it to note any additional information that may be helpful in future. You may wish to include some of the following:
- Title of the dataset
- Author information
- Date of data collection
- Location of data collection
- Information about relevant funding sources
- Contents list of files in dataset (a manifest)
- Relevant relationships between file
- Information about versioning
- Data collection methods
- Quality assurance procedures
Documentation is as much for your benefit as it is for others using your data as it will clarify exactly how your dataset was produced.
Sharing your data
Organising your files will help you in the long run too, when it comes time to share data. Research shows 28% of researchers say the main reason they don’t share data is because of the time it would take to organise it into a fit state to share
‘Data’ relates to any underpinning materials relating to your research project and can apply to the methodology used and any analysis materials. It can also be annotated manuscripts or photographs, translations, recordings of performances, or thematic analysis codes.
But, why is it important to share your data?
Sharing your data may lead to higher citations. Research articles with open data are cited on average 25% more, based on a study of around 500,000 articles. Sharing also increases the visibility of your work and provides more opportunities for collaboration.
You can find out more about sharing on our Research Data Management Sharing webpage.
Key points
To summarise, here are our key points for research file management:
- Data organisation should be consistent, meaningful to you and your colleagues and should allow you to find files easily
- File structures and naming conventions will help you to keep everything orderly, no matter how much data you generate
- Getting into good documentation practices early on will help you keep track of exactly how your data was produced making it easy to replicate if necessary
- Sharing your datasets could help your research reach a wider audience
If you have any further questions about file management or research data management in general, please email the RDM team.
