Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.envsoft.2023.105809
Licence creative commons licence
Title (Primary) System for automated Quality Control (SaQC) to enable traceable and reproducible data streams in environmental science
Author Schmidt, L.; Schäfer, D.; Geller, J.; Lünenschloß, P.; Palm, B.; Rinke, K.; Rebmann, C.; Rode, M.; Bumberger, J.
Source Titel Environmental Modelling & Software
Year 2023
Department ASAM; SEEFO; CHS; MET
Volume 169
Page From art. 105809
Language englisch
Topic T5 Future Landscapes
Data and Software links https://doi.org/10.5281/zenodo.8092119
Supplements https://www.sciencedirect.com/science/article/pii/S1364815223001950#tbl1
https://www.sciencedirect.com/science/article/pii/S1364815223001950#tbl2
https://www.sciencedirect.com/science/article/pii/S1364815223001950#tbl3
https://www.sciencedirect.com/science/article/pii/S1364815223001950#tbl4
https://www.sciencedirect.com/science/article/pii/S1364815223001950#tbl5
Keywords Data management; Quality control; Quality assurance; Anomaly detection; Sensor data; FAIR
Abstract Environmental sensor networks produce ever-growing volumes of raw data that need to be transformed into actionable data for monitoring of ongoing environmental changes and decision-support. The crucial challenge is the data provisioning in real-time which requires rigorous automation of quality control (QC) workflows using suitable software tools. We present the System for automated Quality Control (SaQC), a software framework for automated quality control of time series data that is universal and extensible in its set of domain-agnostic QC and processing functionalities, yet user-friendly in its low-code configuration environment. Two use cases present the configuration of basic and advanced quality control applications using SaQC. Also, we elaborate on the explicit user controls over the handling of quality flags and how SaQC can be used to make QC-workflows traceable and reproducible, thus promoting FAIR data streams of high quality.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=27902
Schmidt, L., Schäfer, D., Geller, J., Lünenschloß, P., Palm, B., Rinke, K., Rebmann, C., Rode, M., Bumberger, J. (2023):
System for automated Quality Control (SaQC) to enable traceable and reproducible data streams in environmental science
Environ. Modell. Softw. 169 , art. 105809 10.1016/j.envsoft.2023.105809