From Architecture to Operation: time.IO a User-Centric Digital Ecosystem for Time Series Data Management in Earth System Science

Research Data Infrastructures (RDIs) in Earth System Science must balance FAIR-compliant data management, operational requirements, and the practical needs of researchers operating heterogeneous sensor networks at scale. These design goals are not always fully aligned and may even conflict in operational environments. At the EGU General Assembly 2025, we introduced a modular digital ecosystem for time series data management designed to address these challenges. One year later, we report on the transition from prototype deployment to sustained operational use and reflect on how user feedback and operational constraints shaped the system’s evolution.

The ecosystem has since been deployed as a production infrastructure at the Helmholtz Centre for Environmental Research - UFZ, where it currently supports approximately 20 research projects. The system manages around three billion observations from diverse sensor networks, with temporal resolutions of up to 5 seconds. This operational setting exposed challenges that were not fully apparent at the design and implementation stages, particularly regarding the scalability of data integration workflows, robustness under continuous load, and the interaction between metadata management, data ingestion, and automated quality control.

The ecosystem comprises three modular components: the Sensor Management System – SMS [1] for standardized metadata registration, the time.IO [2] platform for storage, transfer, and visualization of time series data, and the System for Automated Quality Control – SaQC [3] for automated data analysis and quality assurance. While the modular design enabled reuse and interoperability, early operational phases revealed scaling bottlenecks that led to service outages, necessitating substantial refinements of ingestion pipelines, deployment strategies, and monitoring mechanisms.

User-centric development also played a central role in stabilizing and extending the infrastructure. Continuous feedback from active projects influenced interface design, automation levels, and operational workflows, highlighting the importance of iterative co-design in bridging the gap between conceptual design goals and sustainable, user-accepted operation. We summarize key lessons learned from one year of operational use and discuss implications for building and operating sustainable, interoperable RDIs that effectively support Earth system science across disciplines and scales.

[1] Lorenz, C., Brinckmann, N., Bumberger, J., Hanisch, M., Kuhnert, T., Loup, U., Moorthy, R., Obersteiner, F., Schäfer, D., Schnicke, T. (2025). Sensor Management System (SMS): Open-source software for FAIR sensor metadata management in Earth system sciences. SoftwareX (submitted), https://arxiv.org/abs/2512.17280

[2] Bumberger, J., Abbrent, M., Brinckmann N., Hemmen, J., Kunkel, R., Lorenz, C., Lünenschloß, P., Palm, B., Schnicke, T., Schulz, C., van der Schaaf, H., and Schäfer, D. (2025). Digital Ecosystem for FAIR Time Series Data Management in Environmental System Science. SoftwareX, 102038, https://doi.org/10.1016/j.softx.2025.102038

[3] 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. Environmental Modelling & Software, 105809. https://doi.org/10.1016/j.envsoft.2023.105809