Abstract
Metadata describe the ancillary information needed for data interpretation, comparison across heterogeneous datasets, and quality control and quality assessment (QA/QC). Metadata enable the synthesis of diverse ecohydrological and biogeochemical observations, an essential step in advancing a predictive understanding of earth systems. Environmental observations can be taken across a wide range of spatiotemporal scales in a variety of measurement settings and approaches, and saved in multiple formats. Thus, well-organized, consistent metadata are required to produce usable data products from diverse observations collected in disparate field sites. However, existing metadata reporting protocols do not support the complex data synthesis needs of interdisciplinary earth system research. We developed a metadata reporting framework (FRAMES) to enable predictive understanding of carbon cycling in tropical forests under global change. FRAMES adheres to best practices for data and metadata organization, enabling consistent data reporting and thus compatibility with a variety of standardized data protocols. We used an iterative scientist-centered design process to develop FRAMES. The resulting modular organization streamlines metadata reporting and can be expanded to incorporate additional data types. The flexible data reporting format incorporates existing field practices to maximize data-entry efficiency. With FRAMES’s multi-scale measurement position hierarchy, data can be reported at observed spatial resolutions and then easily aggregated and linked across measurement types to support model-data integration. FRAMES is in early use by both data providers and users. In this paper, we describe FRAMES, identify lessons learned, and discuss areas of future development.
