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Why should you organize your data?
The organizational structure of your data can help you easily locate files when revisiting a past project and can help secondary users find, identify, select, and obtain the data they require.
How do you organize your data?
For best results, data structure should be fully modeled top-to-bottom/beginning-to-end in the planning phase of a project.
You'll want to devise ways to express the following:
- The context of data collection: project history, aim, objectives, and hypothesis
- Data collection methods: sampling, data collection process, instruments used, hardware and software used, scale and resolution, temporal and geographic coverage, and secondary data sources used
- Dataset structure of data files, study cases, and relationships between files
- Data validation, checking, proofing, cleaning, and quality assurance procedure carried out
- Changes made to data over time since their original creation and identification of different versions of data files
- Information on access and use conditions or data confidentiality
File Naming & Structure
Why is file naming important?
Think of a file name as a unique identifier for each of your files. Following a naming convention allows you to simplify the organization of your files and locate your files with ease, as well as making it easier for others to understand and reuse your data. This is particularly important when you are working on a collaborative project.
How should you name your file?
Here are some recommended best practices for naming your files:
- Use names that are brief but descriptive
- Avoid spaces and special characters (ex: *, #, %, etc.)
- Come up with a naming convention adhered to by everyone using the files
- Identify versions of files using dates and version numbering in file name
- Use three letter file extensions to ensure backwards compatibility (ex: .doc, .tif, .txt)
- Do not use letter case to identify different files (ex: datasetA.txt vs. dataseta.txt)
How should files be structured?
Folder structure for your files can assist in the unique identification of the files contained within them. Consider the structure of the folders containing your data files before you begin to collect your data. Ideas for how to organize your folders include:
- Data type (text, images, models, etc.)
- Time (year, month, session, etc.)
- Subject characteristic (species, age grouping, etc.)
- Research activity (interview, survey, experiment, etc.)
Consider these examples:
- File naming: File001.txt vs. 201206blood_ID0234.txt
- Folder structure: MyDocuments\Research\Sample12.jpg vs. C:\\NEHGrant01234\WWI\Images\London_001.jpg
File Naming Resources
Why does data format matter?
To maximize the share-ability and re-usability of your data, you will want to carefully consider the format in which your data is saved. Careful selection of data format can also help you down the road by limiting the chances of your data becoming obsolete when a proprietary format is no longer supported.
What format should you use?
Formats which are more than likely to be accessible in the long-term are:
- Open format (or free file formats), non-proprietary
- Commonly used within your field or discipline
- Have a standard encoding (ASCII, Unicode)
- Not encrypted or compressed
See the University of Washington's ResearchWorks Collection Policy for more information about file formats.
If you have questions about data organization and format or would like to request a consultation with a member of the Scholarly Communications and Publishing Team, please email firstname.lastname@example.org or click the "Ask Us" link on the top right side of this site.