A Performant, Scalable Processing Pipeline for High‐Quality and FAIR Environmental Sensor Data

High‐resolution environmental monitoring is necessary to record, understand, and predict biogeochemical and ecological changes particularly in coastal systems but brings significant challenges in processing and making rapidly available the resulting data. The COMPASS‐FME project established a network of coastal observational sites across the Chesapeake Bay and western Lake Erie regions extensively instrumented with soil, vegetation, and weather sensors logging data every 15 min. Our data processing framework, written in R and completely open source, prioritizes rapid model‐experiment iteration and makes biogeochemical data rapidly available for quality assurance/quality control, analysis, and model ingestion. This pipeline is distinguished by a standardized and modular approach to data curation, extensive metadata and documentation, and its high performance. These attributes combine to make biogeochemical data rapidly accessible across COMPASS‐FME and the broader community. Flexible, powerful, and reproducible approaches to handling high‐volume environmental data are crucial for accelerating biogeosciences research.

• Publication year

  2025

• Venue

  Journal of Geophysical Research: Biogeosciences

• Publication date

  2025-11-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1029/2025JG008807
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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