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

A community convention for ecological forecasting: Output files and metadata version 1.0
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生态预测社区公约:输出文件和元数据版本 1.0

DOI:
10.1002/ecs2.4686
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发表时间:
2023
期刊:
影响因子:
2.7
通讯作者:
Ashander, Jaime
Ashander, Jaime
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Dietze, Michael C.;Thomas, R. Quinn;Peters, Jody;Boettiger, Carl;Koren, Gerbrand;Shiklomanov, Alexey N.;Ashander, Jaime

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本文概述了生态预报倡议(EFI)为生态预报的通用格式化和存档以及与这些预报相关的元数据制定的开放社区惯例。这样的开放标准旨在促进互操作性,并促进预报的通信、分发、验证和综合。对于输出文件,我们首先从全局属性、预测维度、预测变量和辅助指标变量等方面对约定进行概念性描述。然后,我们将说明将该约定应用于EFI当前首选的两种文件格式:netCDF(网络公共数据格式)和逗号分隔值(CSV),但请注意,该约定可扩展到未来的格式。对于元数据,EFI的约定确定了所需的常规元数据变量的子集(例如,时间分辨率和输出变量),但重点是开发一个框架,用于存储有关预报不确定性传播、数据同化和模式复杂性的信息,旨在促进交叉预报合成。该约定的最初应用是对生态元数据语言(EML)的扩展,生态元数据语言是生态学中常用的元数据标准。为了促进社区采用,我们还提供了一个Github存储库,其中包含一个元数据验证器工具和几个关于如何在EFI标准中写入和读取EFI标准的R和Python小插曲。最后,我们提供了关于预测归档的指导,对短期传播和长期预测归档进行了重要区分,同时还涉及到代码和工作流的归档。总体而言,EFI公约是一份活的文件,可以通过开放的社区进程随着时间的推移继续发展。
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.
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