Data quality checking and processing tool/framework
Project description
System for automated Quality Control (SaQC)
Quality Control of numerical data requires a significant amount of domain knowledge and practical experience. Finding a robust setup of quality tests that identifies as many suspicious values as possible, without removing valid data, is usually a time-consuming and iterative endeavor, even for experts.
SaQC is both, a Python framework and a command line application, that addresses the exploratory nature of quality control by offering a continuously growing number of quality check routines through a flexible and simple configuration system.
Below its user interface, SaQC is highly customizable and extensible. A modular structure and well-defined interfaces make it easy to extend the system with custom quality checks and even core components, like the flagging scheme, are exchangeable.
Why?
During the implementation of data workflows in environmental sciences, our experience shows a significant knowledge gap between the people collecting data and those responsible for the processing and the quality-control of these datasets. While the former usually have a solid understanding of the underlying physical properties, measurement principles and the resulting errors, the latter are mostly software developers with expertise in data processing.
The main objective of SaQC is to bridge this gap by allowing both parties to focus on their strengths: The data collector/owner should be able to express his/her ideas in an easy and succinct way, while the actual implementation of the algorithms is left to the respective developers.
How?
The most import aspect of SaQC, the general configuration of the system, is text-based. All the magic takes place in a semicolon-separated table file listing the variables within the dataset and the routines to inspect, quality control and/or modify them.
varname ; test ; plot
#----------;-------------------------------------;------
SM2 ; harm_shift2Grid(freq="15Min") ; False
SM2 ; flagMissing(nodata=NAN) ; False
'SM(1|2)+' ; flagRange(min=10, max=60) ; False
SM2 ; spikes_flagMad(window="30d", z=3.5) ; True
While a good (but still growing) number of predefined and highly configurable functions are included and ready to use, SaQC additionally ships with a python based for quality control but also general purpose data processing extension language.
For a more specific round trip to some of SaQC's possibilities, please refer to our GettingStarted.
Installation
Python Package Index
SaQC is available on the Python Package Index (PyPI) and can be installed using pip:
python -m pip install saqc
Anaconda
Currently we don't provide pre-build conda packages but the installing of SaQC
using the conda package manager is
straightforward:
- Create an anaconda environment including all the necessary dependencies with:
conda env create -f environment.yml
- Load the freshly created environment with:
conda activate saqc
Manual installation
The latest development version is directly available from the gitlab server of the Helmholtz Center for Environmental Research. More details on how to setup an respective environment are available here
Python version
The minimum Python version required is 3.6.
Usage
Command line interface (CLI)
SaQC provides a basic CLI to get you started. As soon as the basic inputs, a dataset and the configuration file are prepared, running SaQC is as simple as:
saqc \
--config path_to_configuration.txt \
--data path_to_data.csv \
--outfile path_to_output.csv
Integration into larger workflows
The main function is exposed and can be used in within your own programs.
License
Copyright(c) 2019, Helmholtz Centre for Environmental Research - UFZ. All rights reserved.
The "System for Automated Quality Control" is free software. You can redistribute it and/or modify it under the terms of the GNU General Public License as published by the free Software Foundation either version 3 of the License, or (at your option) any later version. See the license for details.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
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