time.IO – Digital Ecosystem for FAIR Time Series Data Management in Environmental System Science

The field of earth system sciences relies heavily on the collection, analysis, and interpretation of data to understand complex spatiotemporal environmental processes and predict future trends. Time series data, which capture measurements or observations at regular intervals over time, play a crucial role in elucidating patterns, detecting changes, and informing decision-making in various environmental domains. However, the effective storage and management of time series data present significant challenges that necessitate the development of robust and scalable data infrastructures. A well-designed data infrastructure is crucial to ensure the reliability, accessibility, interoperability, and sustainability of time series data across different domains and scales. It enables efficient data collection through automated sensing technologies, standardized data exchange protocols, and quality control procedures. Moreover, robust time series data infrastructures facilitate the integration of data from diverse sources into distributed data infrastructures on national and/or continental scales and advance the dissemination of data to a wide range of stakeholders, including scientists, policymakers, resource managers, and the general public. With time.IO, we present such a time series data management system that encompasses powerful data storage and management capabilities, a comprehensive sensor metadata management solution, and an integrated anomaly detection module, all in an easily deployable package.