Abstract
Data provides the practical means by which we conduct a scientific investigation of metrics that facilitate informed operational decision-making, and of the construction and parameterization of predictive models. Especially today in the computer age where computing power is abundant, adequate data now tends to be the limiting factor on the quality of our estimation, modeling, understanding, decision-making, and prediction. Fortunately, there is a lot of data available about FEW systems. But, this data is not easy to locate, access, or utilize. This data is often privacy-restricted and privileged. This data is patchy with surprisingly large gaps for critical layers and scales of FEW systems. The lack of seamless, high-quality, synthetic datasets describing FEW systems across sectors and scales is one of the major practical barriers to FEW systems work at the present time. Most data sets were collected to answer a single question about a single layer, process, and scale in the FEW system, but systems science and systems management requires data that interoperates across layers and scales. The science and tools of Data are essential for the study of FEW systems.
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Notes
- 1.
The Coalition for Publishing Data in the Earth and Space Sciences (COPDESS) provides some detailed advice on best practices for implementing the FAIR principles for your research project or other data product project.
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Ruddell, B.L. (2020). Data. In: Saundry, P., Ruddell, B. (eds) The Food-Energy-Water Nexus. AESS Interdisciplinary Environmental Studies and Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-29914-9_14
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