FAIR Principle
Applying the FAIR principles in visual social research is prepared through how visual data are organized, interpreted, and documented during analysis.
Structuring data for traceability and reuse
During analysis, visual materials are selected, compared, and organized into coherent datasets. This process requires making analytical steps explicit and ensuring that interpretations remain traceable over time.
Visual data are highly context-dependent and cannot be understood without reference to the circumstances of their production and interpretation. For this reason, analysis should be accompanied by systematic documentation that preserves the meaning and conditions of the data.
Building meaningful metadata
Contextual information is essential to make visual data interpretable and reusable. This includes documenting how visuals were produced, selected, and used within the study, as well as the social and cultural contexts in which they are embedded.
Such documentation forms the basis for metadata that will later support findability and reuse, ensuring that visual materials can be understood beyond the original research setting.
Keeping future use in view
Although decisions about access conditions, licensing, and degrees of openness are typically finalized later, this phase shapes what will be possible. The way visual data are structured, contextualized, and documented during analysis directly affects their accessibility, interpretability, and potential reuse.