Sourcesan

Sourcesan refers to a class of tools and methodologies designed to sanitize sources in data workflows. The goal is to ensure that external information—whether from APIs, logs, web content, or user submissions—meets quality, security, and reproducibility standards before further processing.

Typical sourcesan implementations combine three elements: a validator to check structural correctness and schema conformance; a sanitizer to clean or transform data (for example, removing harmful content, normalizing encodings, and normalizing formats); and a provenance module to record source origin, timestamp, and transformation steps.

Applications include data pipelines, content management systems, journalism and fact-checking workflows, and web scraping platforms. By enforcing standardized inputs, sourcesan aims to reduce errors, mitigate security risks, and improve traceability of data from source to output.

There is no single universal standard for sourcesan; the concept appears across tools in data engineering, software development, and information governance, each implementing its own rulesets and plug-in interfaces.

Related topics include data sanitization, input sanitization, data provenance, data cleansing, and schema validation.