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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.
@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}
}

Journal Article:
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  • 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 reportingmore » 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.« less
  • FRAMES is a a set of Excel metadata files and package-level descriptive metadata that are designed to facilitate and improve capture of desired metadata for ecohydrological observations. The metadata are bundled with data files into a data package and submitted to a data repository (e.g. the NGEE Tropics Data Repository) via a web form. FRAMES standardizes reporting of diverse ecohydrological and biogeochemical data for synthesis across a range of spatiotemporal scales and incorporates many best data science practices. This version of FRAMES supports observations for primarily automated measurements collected by permanently located sensors, including sap flow (tree water use), leafmore » surface temperature, soil water content, dendrometry (stem diameter growth increment), and solar radiation. Version 1.1 extend the controlled vocabulary and incorporates functionality to facilitate programmatic use of data and FRAMES metadata (R code available at NGEE Tropics Data Repository).« less
  • The effect of forest decline on water resources is not well described, for there have been no long-term measurements on catchments with declining forests. The precipitation/runoff relationship of the declining forests of the Eyach catchment in the Northern Black Forest/Federal Republic of Germany is analyzed. The uninhabited catchment is subdivided into four subcatchments (7, 10, 30, 52 km{sup 2}) and is totally covered with coniferous forest, mostly Norway spruce. Long-term monitoring from 1973 to 1986 indicates a significant increase in water yield and the runoff coefficient for the growing season, although there has been no extensive cutting in the catchment.more » An ecohydrological systems model was developed by the incorporation of field data and plant physiological processes to describe the increase in water yield. Field data include hydrological, hydrogeological, geological, soil-physical, soil-chemical, water-chemical, air-chemical, pollutant deposition, forest inventory, and forest decline field measurements from the Eyach catchment and comparable neighboring regions. The model indicates that the observed increase in water yield is likely to be caused by a reduction of forest transpiration. This change in water yield is linked to forest decline and soil acidification caused by anthropogenic sources of air pollution.« less
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  • We report our experience on migrating STARs Online Services (Run Control System, Data Acquisition System, Slow Control System and Subsystem Monitoring) from direct read/write database accesses to a modern non-blocking message-oriented infrastructure. Based on the Advanced Messaging Queuing Protocol (AMQP) and standards, this novel approach does not specify the message data structure, allowing great flexibility in its use. After careful consideration, we chose Google Protocol Buffers as our primary (de)serialization format for structured data exchange. This migration allows us to reduce the overall system complexity and greatly improve the reliability of the metadata collection and the performance of our onlinemore » services in general. We will present this new framework through its software architecture overview, providing details about our staged and non-disruptive migration process as well as details of the implementation of pluggable components to provide future improvements without compromising stability and availability of services.« less