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Title: A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations

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 resolutionsmore » 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. Here in this article, we describe FRAMES, identify lessons learned, and discuss areas of future development.« less

Authors:
 [1];  [2];  [3];  [4];  [2];  [5];  [6];  [2];  [2];  [6];  [2];  [6];  [7];  [8];  [2];  [9];  [10];  [6]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Science Area; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Science Area
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Smithsonian Tropical Research Inst., Ancon (Panama). Center for Tropical Forest Science; Princeton Univ., NJ (United States). Dept. of Ecology and Evolutionary Biology
  5. National Inst. of Amazonian Research (INPA), Manaus (Brazil)
  6. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
  7. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. & Environmental Science Division
  8. Smithsonian Tropical Research Inst., Ancon (Panama). Center for Tropical Forest Science
  9. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Science Area; Univ. of California, Berkeley, CA (United States). Energy and Resources Group
  10. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. & Environmental Science Division
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Institute of Amazonia Research (INPA)
OSTI Identifier:
1408589
Alternate Identifier(s):
OSTI ID: 1435093
Grant/Contract Number:  
AC05-00OR22725; AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Ecological Informatics
Additional Journal Information:
Journal Volume: 42; Journal Issue: C; Journal ID: ISSN 1574-9541
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 58 GEOSCIENCES; Metadata; Data management system; Model-data integration; Data synthesis; Data preservation; Informatics

Citation Formats

Christianson, Danielle S., Varadharajan, Charuleka, Christoffersen, Bradley, Detto, Matteo, Faybishenko, Boris, Gimenez, Bruno O., Hendrix, Val, Jardine, Kolby J., Negron-Juarez, Robinson, Pastorello, Gilberto Z., Powell, Thomas L., Sandesh, Megha, Warren, Jeffrey M., Wolfe, Brett T., Chambers, Jeffrey Q., Kueppers, Lara M., McDowell, Nathan G., and Agarwal, Deborah A.. A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations. United States: N. p., 2017. Web. doi:10.1016/j.ecoinf.2017.06.002.
Christianson, Danielle S., Varadharajan, Charuleka, Christoffersen, Bradley, Detto, Matteo, Faybishenko, Boris, Gimenez, Bruno O., Hendrix, Val, Jardine, Kolby J., Negron-Juarez, Robinson, Pastorello, Gilberto Z., Powell, Thomas L., Sandesh, Megha, Warren, Jeffrey M., Wolfe, Brett T., Chambers, Jeffrey Q., Kueppers, Lara M., McDowell, Nathan G., & Agarwal, Deborah A.. A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations. United States. doi:10.1016/j.ecoinf.2017.06.002.
Christianson, Danielle S., Varadharajan, Charuleka, Christoffersen, Bradley, Detto, Matteo, Faybishenko, Boris, Gimenez, Bruno O., Hendrix, Val, Jardine, Kolby J., Negron-Juarez, Robinson, Pastorello, Gilberto Z., Powell, Thomas L., Sandesh, Megha, Warren, Jeffrey M., Wolfe, Brett T., Chambers, Jeffrey Q., Kueppers, Lara M., McDowell, Nathan G., and Agarwal, Deborah A.. Tue . "A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations". United States. doi:10.1016/j.ecoinf.2017.06.002. https://www.osti.gov/servlets/purl/1408589.
@article{osti_1408589,
title = {A metadata reporting framework (FRAMES) for synthesis of ecohydrological observations},
author = {Christianson, Danielle S. and Varadharajan, Charuleka and Christoffersen, Bradley and Detto, Matteo and Faybishenko, Boris and Gimenez, Bruno O. and Hendrix, Val and Jardine, Kolby J. and Negron-Juarez, Robinson and Pastorello, Gilberto Z. and Powell, Thomas L. and Sandesh, Megha and Warren, Jeffrey M. and Wolfe, Brett T. and Chambers, Jeffrey Q. and Kueppers, Lara M. and McDowell, Nathan G. and Agarwal, Deborah A.},
abstractNote = {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. Here in this article, we describe FRAMES, identify lessons learned, and discuss areas of future development.},
doi = {10.1016/j.ecoinf.2017.06.002},
journal = {Ecological Informatics},
number = C,
volume = 42,
place = {United States},
year = {Tue Jun 20 00:00:00 EDT 2017},
month = {Tue Jun 20 00:00:00 EDT 2017}
}

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