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Data quality checking and processing 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, to find 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.

SaQC Workflow

Why?

During the implementation of data workflows in environmental sciences, our experience shows a significant knowledge gap between the people collecting the 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 errors that might result from these, 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.

Example config

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 extension language.

For a more specific round trip to some of SaQC's possibilities, please refer to our GettingStarted.

Installation

pip

SaQC is available on the Python Package Index (PyPI) and can be installed using pip:

python -m pip install saqc

Manual installation

The latest development version is directly available from the gitlab server of the Helmholtz Center for Environmental Research. All the dependencies are listed here and are resolvable with:

python -m pip install -r requirements.txt

Python version

The minimum Python version required is 3.6 and SaQC is directly compatible with Python versions 3.6 and 3.7. If you are already on Python 3.8 however, the installation process is currently a bit more involved as still not all dependencies are available as binary wheels.

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.

Project details


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This version

1.0.0

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