Organise your data

Are there any standards or methodologies in your field to collect, process, transcribe, check, validate or verify data?

• e.g. standard protocols, templates or input forms.
• If you are using a specific repository, do you have to organize your data in a certain way?
• How will you document any changes? It is best practice to document changes so that you have a history, version control and a provenance trail.
• How will you check the quality of your data? Are there quality assurance processes you can adopt?
• Examples include calibration, repeat samples or measurements, standardised data capture or recording, data entry validation, peer review of data or representation with controlled vocabularies.

Organise your data as you go.

• Consider how best to structure folders and name your files in order to ensure version control.
• Include version number, date, initials and content in file names. Avoid capitalisation, spaces and special characters.
• Identify master/milestone versions of files that you want to keep and put these in a single location.
• Think about how you will avoid confusion with multiple versions of your data in different locations – laptop, audio recorder, OneDrive etc.
• Make a record of changes and relationships between items.
• Sync files regularly.
• It can be helpful to use a diagram to represent the file structure for your own reference and for your team.
• Use the FAIR principles (Findable, Accessible, Interoperable and Reusable).

What formats are best suited for data creation, analysis, reuse and sharing?

• e.g. MS Word, MS Excel, jpeg, SPSS, Open Document Format, etc.
• What is generally used in your field?
• Will the formats and software you use enable others to understand and use your data? Do they enable sharing and long-term access to the data?
• If you are using specialist software and you intend to make data available after the project, can you easily convert it to other more accessible formats at the end of the project?

Think about the likely volume of data you will produce.

• e.g. number of files, size – this has implications for managing, accessing and storing the data.
• What information do you intend to collect, what format will you store it in?
• If you will create a large amount of data, do you need technical support from IT Services or to request external funding for additional storage?