A Community Convention for Ecological Forecasting: Output Files and Metadata

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.

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Authors

Michael C. Dietze, R. Quinn Thomas, Jody Peters, Carl Boettiger, Alexey N Shiklomanov, Jaime Ashander

Abstract

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 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, output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity that 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.

DOI

https://doi.org/10.32942/osf.io/9dgtq

Subjects

Ecology and Evolutionary Biology, Life Sciences, Other Ecology and Evolutionary Biology

Keywords

Dates

Published: 2021-05-27 21:42

Last Updated: 2023-01-18 09:40

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License

CC-By Attribution-ShareAlike 4.0 International

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