A User-Friendly Self-Service for Configuring the Ingestion and Processing of Time Series Data

The management of environmental time series data requires reliable configuration of data ingestion, processing, and quality control across heterogeneous sensors, formats, and research projects. Within Helmholtz Earth & Environment, this challenge is amplified by the need for standardized, reproducible, and interoperable workflows that align with the DataHub framework. To address these requirements, the Time Series Management Self-Service (TSM Self-Service) application provides a user-friendly, project-oriented platform for configuring time series data workflows. The platform enables users to define data loggers, configure diverse data sources, and design quality assurance and quality control (QA / QC) pipelines through an intuitive web-based interface. It supports flexible parsing rules, structured metadata management, time zone handling, and rule-based validation of time series data. Using a service-oriented backend architecture and standardized APIs, user configurations are translated into orchestrated processing pipelines and persistent storage integrated with DataHub services. By adopting a self-service paradigm, TSM Self-Service reduces operational complexity and manual intervention while improving transparency, traceability, and data quality throughout the time series lifecycle. The platform enables research projects to independently manage data ingestion and processing workflows while complying with institutional standards for data governance, interoperability, and long-term sustainability.