Revise and apply the Data Management Plan
Your Data Management Plan (DMP) becomes operational. It helps you make the analytical workflow clear: what happens to visual materials, how decisions are documented, and how the dataset is prepared for possible future reuse.
What should your DMP cover?
How you organize the dataset
Make your structure clear and consistent. For example:
- how files are grouped (by case, date, platform, participant, theme, etc.)
- naming conventions and folder structure
- versioning rules (what counts as a new version of an image or dataset)
What counts as “data” during analysis
Not only images are data. Your dataset may also include:
- coding sheets, codebooks, annotation files
- interpretive memos and reflexive notes (positionality, assumptions, interpretive choices)
- documentation of analytical steps (how categories were built, how comparisons were made)
How you document interpretation
Make your analytical process traceable.
- explain how interpretive decisions are made and recorded
- ensure that others can understand how you moved from data to findings
Metadata and contextual documentation
Context is essential for understanding visual data. Your DMP should specify:
- which metadata you create (e.g., how and in which conditions the visual was produced and used)
- how you capture key context (who produced the visual, when and where, under which conditions, and for what purpose in the study)
- how this documentation is stored with the visuals, so it does not get lost or separated