stk-data-annotations

To align and validate survey data meta JSON files, apply bootstrapping and validation workflows to standardize category mappings and processing rules, ensuring YAML frontmatter drives discovery and prevents semantic drift in analyses.

Category mapping alignment for survey waves is the process of auditing annotations across different survey modes like CATI and WEB to standardize mappings and prevent semantic drift during data analysis.

Audit category mappings and top-k maxdiff configurations in JSON metadata by applying validation workflows that check annotations for semantic drift and ensure transform adjustments align across multiple surveys and waves.

Yes, you can use read_and_process_data to load aligned annotations from multiple survey modes, applying bootstrapping and validation workflows to standardize category mappings and processing rules across datasets.

Yes, you need YAML frontmatter to define name and description for survey data annotations, as the frontmatter drives discovery and validation workflows while ensuring provenance and consistency across raw data and processed outputs.

The best way to prevent semantic drift in survey data annotations is to audit category mappings, translations, and top-k maxdiff configurations using validation workflows that align annotations across multiple surveys and waves.