Derivatives of Image-based Data

Nature:

Derivatives of image-based data include for example

• morphometry data derived from measurements of images and statistical analysis thereof
• chromosome counts
• tables containing characters matrices compiled from image analysis and analyses of these tables
• phenotypic data recorded from living plants due to their similar nature and purpose.

File formats: various formats. CSV or Excel for numerical data, or use special software, e.g. for character matrices. Analysis output format based on software.

Storage / folder organization:

• Store in (a) subfolder(s) within a project folder.
• Organize folder(s) by type of derivative data and analyses.
• Create subfolders for each analysis with a date and indicating the analysis method. These folders contain all files used for the analysis.
• Store visualizations alongside the analysis data

Naming convention: Use descriptive and consistent naming, include the type of analysis, date and relevant identifiers in the file name.

Version control: Include version numbers or dates in the file names to keep track of different versions.

Metadata: Document the source images, analysis method, software used and any other relevant parameters or settings. Store metadata in a README file within each folder.

Link to source data: Maintain clear links to source images, and to samples or specimens through consistent naming and metadata documentation.

Retention: Retain key data and final versions of analysis results indefinitely. Periodically review and delete intermediate or obsolete versions that are not necessary for future reference or publications.

Publication: Publish data tables, character matrices or similar data as supplementary materials.