TY - JOUR
T1 - A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations
AU - Christianson, Danielle S.
AU - Varadharajan, Charuleka
AU - Christoffersen, Bradley
AU - Detto, Matteo
AU - Faybishenko, Boris
AU - Gimenez, Bruno O.
AU - Hendrix, Val
AU - Jardine, Kolby J.
AU - Negron-Juarez, Robinson
AU - Pastorello, Gilberto Z.
AU - Powell, Thomas L.
AU - Sandesh, Megha
AU - Warren, Jeffrey M.
AU - Wolfe, Brett T.
AU - Chambers, Jeffrey Q.
AU - Kueppers, Lara M.
AU - McDowell, Nathan G.
AU - Agarwal, Deborah A.
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/11
Y1 - 2017/11
N2 - Metadata describe the ancillary information needed for data preservation and independent interpretation, comparison across heterogeneous datasets, and quality assessment and quality control (QA/QC). Environmental observations are vastly diverse in type and structure, 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 environmental observations collected across field sites. However, existing metadata reporting protocols do not support the complex data synthesis and model-data integration needs of interdisciplinary earth system research. We developed a metadata reporting framework (FRAMES) to enable management and synthesis of observational data that are essential in advancing a predictive understanding of earth systems. FRAMES utilizes best practices for data and metadata organization enabling consistent data reporting and compatibility with a variety of standardized data protocols. We used an iterative scientist-centered design process to develop FRAMES, resulting in a data reporting format that incorporates existing field practices to maximize data-entry efficiency. Thus, FRAMES has a modular organization that streamlines metadata reporting and can be expanded to incorporate additional data types. 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 originators (persons generating data) and consumers (persons using data and metadata). In this paper, we describe FRAMES, identify lessons learned, and discuss areas of future development.
AB - Metadata describe the ancillary information needed for data preservation and independent interpretation, comparison across heterogeneous datasets, and quality assessment and quality control (QA/QC). Environmental observations are vastly diverse in type and structure, 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 environmental observations collected across field sites. However, existing metadata reporting protocols do not support the complex data synthesis and model-data integration needs of interdisciplinary earth system research. We developed a metadata reporting framework (FRAMES) to enable management and synthesis of observational data that are essential in advancing a predictive understanding of earth systems. FRAMES utilizes best practices for data and metadata organization enabling consistent data reporting and compatibility with a variety of standardized data protocols. We used an iterative scientist-centered design process to develop FRAMES, resulting in a data reporting format that incorporates existing field practices to maximize data-entry efficiency. Thus, FRAMES has a modular organization that streamlines metadata reporting and can be expanded to incorporate additional data types. 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 originators (persons generating data) and consumers (persons using data and metadata). In this paper, we describe FRAMES, identify lessons learned, and discuss areas of future development.
KW - Data management system
KW - Data preservation
KW - Data synthesis
KW - Informatics
KW - Metadata
KW - Model-data integration
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U2 - 10.1016/j.ecoinf.2017.06.002
DO - 10.1016/j.ecoinf.2017.06.002
M3 - Article
AN - SCOPUS:85033472625
SN - 1574-9541
VL - 42
SP - 148
EP - 158
JO - Ecological Informatics
JF - Ecological Informatics
ER -