Having a well-considered plan for the structure and organisation of your research data will improve it's management, access, and re-use. The organisation of data is especially important in team projects where more than one person will be accessing and analysing the data.
The key methods and approaches to consider are:
Digital file names are important for identifying and finding a digital file. Researchers should develop and communicate a clear system of naming files so everyone involved in the research project understands and can appropriately apply the file naming rules to create and locate files.
The most important things to remember about file naming are:
Descriptiveness - Good naming conventions should provide useful cues to the content and status of a file, including its version.
Consistent application - By selecting an appropriate naming convention for files as early as possible and follow it throughout the research, the benefit from file naming systems will be maximised.
The following examples highlight basic principles of file naming.
Good file names:
20191004 Registry of participants - Survey.doc
ROBERTSON Thomas Logan - 2011 Interview.mp4
Bad file names:
crt doc scan.pdf
Lit review, bib., chpt2-4, rev, cvr page, appendices.docx
Consider the advice in the Document Naming Guidelines and how it applies to your own research.
Like file naming, systems to organise folder and file directories require coherency and consistency.
Coherency - Anyone using the folders should be aware that there is a system and what it means.
Consistency - Anyone using the folders should be consistent in creating folder names in line with the system, but also in keeping the relevant files in the appropriate folders.
This will ensure it is easy to locate, organise, navigate and understand the context of all files and versions.
Other concepts to consider include:
Over the duration of a research project, a dataset will undergo many changes. They may be as simple as adding more sets of findings, or as major as the addition of a new dimension or type of measurement. This is important for 2 reasons:
One of the tools used to address these needs is versioning. This refers to a system of keeping the old versions of a file and tracking the changes made in each version.
The most basic forms of versioning are manual systems. These usually contain two important elements:
These are outlined in the ARDC Versioning guide and the UK Data Service Version Control and Authenticity page linked below.
While a manual system can work for many research projects, they can become difficult to use once your needs become complex or multiple people begin working on the same dataset, as explained in the video below. In these cases you should consider using version control software - Git is the best known and most widely used of this type of software.
By working with file formats that are widely-used, interchangeable and with good long-term preservation qualities, you will improve the impact and reach of your research outputs. Choosing good formats will improve the accessibility of your research and make it easier for yourself and other future researchers to use or reuse with a wide range of computer systems regardless of available software packages.
When performing research it’s often necessary to use specialised and proprietary file formats. This may be for many reasons: your method of data analysis; the hardware used; the software available to you or to meet discipline-specific standards. Regardless of these issues, it’s still important to make a conscious and informed decision on choosing file formats. At a minimum you should consider:
At later stages of your research, such as when publishing traditional research outputs or making your data publicly available, you should consider transferring your data to a file format that can be utilised by people who may not have access to the exact suite of software you have. The UK Data Service Recommended Formats table can help you use a file format best suited to long term accessibility.