Qualitis is a one-stop data quality management platform that supports quality verification, notification, and management for various datasource. It is used to solve various data quality problems caused by data processing. https://github.com/WeBankFinTech/Qualitis

🖇 Android hodgepodge static code quality check tool gradle plugin.

Dynamic Generation and Quality Checks of Formula Objects

Columbus - the powerful monitoring tool

yalsa is Yet Another Live Stream Analyzer running in console.

Sistema (lib + REST APIs) para validação de boas práticas na construção de contratos de API em OpenAPI Specification.

BEE (Bug rEport analyzEr), a tool for structuring and analyzing bug reports

A Matlab toolbox for examining the quality of structural (SNR) and functional (tSNR, SFNR) MRI

Data quality monitoring for high energy physics. Doc available at

NPM package quality monitoring tool

Estimate the quality of your diffusion-weighted data to map human connectomes.

The package RNAseqAnalysis does the complete analysis of RNA seq data starting from raw reads. It provides the user with differnt functions like generation of qc report, filtering, assembly and GO-term annotation, differential expression analysis and heatmap generation, and Alternative splicing-site prediction

Brake pad quality inspection

Simple and fast linter for Git commit messages

CNAqc - Copy Number Alteration (CNA) Quality Check package

This application will provide a recommendation on which axis you should flip the bvecs of your data, if it is necessary. It will perform fiber tracking using 4 different gradient flip options (no flip, x flip, y flip, and z flip) and report the most likely flip needed for your data. The flip recommendation is made based on the flip direction with the highest number of long fibers.

Python scripts for transforming specific metocean datasets from text-based to binary formats and checking them for data quality issues

This service creates images of 3D surfaces of the major tracts segmented by AFQ or WMA in 4 views: axial, coronal, left and right sagittal.

CSV Data Validator is a tool to validate csv file. It parse csv and validate the data with .hdr(csv meta data) before ingestion to Data Lake. It checks data file availability for every day load and validate data with respective meta data like File Size, Checksum, Delimiter, Record count etc. It ensure landed data conformity before give go ahead for data ingestion to Data Lake. It generate complete stats or error log.

Package for validating IDSR data (check missings and threshold flags), produce weekly data summary and template for monthly bulletin

Universal Maya Production Inspect Redundant Elements

This service creates 4 figures of each AFQ tract: axial, left sagittal, right sagittal, coronal. Please choose the t1 image slices you would like displayed. The default slices work well for the HCP t1 images if they have not been re-ACPC aligned. If you have ACPC aligned your t1 images using the ACPC alignment app on Brain Life the following values are a good starting point: coronal = 105, sagittal = 89, axial = 65. The img_min and img_max values refer to the value range displayed for the t1 image. The value range is calulated as follow (mean + img_min * std, mean + img_max * std). The default values are a good starting place, adjust them if your t1 is too dark or too light.

Labs to load measurements request web services

Generates multiple graphs that can be used as a quality check for the outputs of AFQ and LiFE. This application will only work if the zero weighted fibers are removed AFTER AFQ.