{"skill":{"slug":"data-quality-check","displayName":"Data Quality Check","summary":"Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thres...","tags":{"latest":"2.1.0"},"stats":{"comments":0,"downloads":1261,"installsAllTime":8,"installsCurrent":8,"stars":0,"versions":2},"createdAt":1770475532210,"updatedAt":1777525153922},"latestVersion":{"version":"2.1.0","createdAt":1771175403466,"changelog":"- Added comprehensive data quality assessment covering completeness, accuracy, consistency, timeliness, and validity for construction datasets.\n- Introduced automated validation using regex patterns, rule-based thresholds, and column checks.\n- Included programmatic usage examples and quick start guide in Python.\n- Enhanced reporting with per-metric results, threshold checks, and detailed issue logging.\n- Documentation now references the DDC methodology and main quality standards for construction data.","license":null},"metadata":{"os":["win32"],"systems":null},"owner":{"handle":"datadrivenconstruction","userId":"publishers:datadrivenconstruction","displayName":"datadrivenconstruction","image":"https://avatars.githubusercontent.com/u/94158709?v=4"},"moderation":null}