A community convention for ecological forecasting: Output files and metadata version 1.0

被引:8
|
作者
Dietze, Michael C. [1 ]
Thomas, R. Quinn [2 ,3 ]
Peters, Jody [4 ]
Boettiger, Carl [5 ]
Koren, Gerbrand [6 ]
Shiklomanov, Alexey N. [7 ]
Ashander, Jaime [8 ]
机构
[1] Boston Univ, Dept Earth & Environm, Boston, MA 02215 USA
[2] Virginia Tech, Dept Forest Resources & Conservat, Blacksburg, VA USA
[3] Virginia Tech, Dept Biol Sci, Blacksburg, VA USA
[4] Univ Notre Dame, Dept Biol Sci, South Bend, IN USA
[5] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA USA
[6] Univ Utrecht, Copernicus Inst Sustainable Dev, Utrecht, Netherlands
[7] NASA, Goddard Space Flight Ctr, Greenbelt, MD USA
[8] US Geol Survey, Eastern Ecol Sci Ctr, Laurel, MD USA
来源
ECOSPHERE | 2023年 / 14卷 / 11期
关键词
comma-separated values (CSV); data assimilation; ecological forecasting; Ecological Metadata Language (EML); ensemble; netCDF; standards; uncertainty; CLIMATE; MODEL;
D O I
10.1002/ecs2.4686
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.
引用
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页数:23
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