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Small values in big data: The continuing need for appropriate metadata

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Craig A. Stow, Katherine E. Webster, Tyler Wagner, Noah R. Lottig, Patricia A. Soranno, and YoonKyung Cha, 2018, Small values in big data: The continuing need for appropriate metadata: Ecological Informatics, v. 45.

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Compiling data from disparate sources to address pressing ecological issues is increasingly common. Many ecological datasets contain left-censored data – observations below an analytical detection limit. Studies from single and typically small datasets show that common approaches for handling censored data — e.g., deletion or substituting fixed values — result in systematic biases. However, no studies have explored the degree to which the documentation and presence of censored data influence outcomes from large, multi-sourced datasets. We describe left-censored data in a lake water quality database assembled from 74 sources and illustrate the challenges of dealing with small values in big data, including detection limits that are absent, [...]

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Type Scheme Key
local-index unknown 70197439
local-pk unknown 70197439
doi http://www.loc.gov/standards/mods/mods-outline-3-5.html#identifier doi:10.1016/j.ecoinf.2018.03.002
series unknown Ecological Informatics

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journalEcological Informatics
parts
typevolume
value45
languageEnglish
citationTypeArticle

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