dc.contributorGorgoglione Angela, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.contributorCastro Alberto, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.contributorChreties Christian, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.contributorEtcheverry Lorena, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.creatorGorgoglione, Angela
dc.creatorCastro, Alberto
dc.creatorChreties, Christian
dc.creatorEtcheverry, Lorena
dc.date.accessioned2021-04-13T15:31:45Z
dc.date.accessioned2022-10-28T20:08:53Z
dc.date.available2021-04-13T15:31:45Z
dc.date.available2022-10-28T20:08:53Z
dc.date.created2021-04-13T15:31:45Z
dc.date.issued2020
dc.identifierGorgoglione, A., Castro, A., Chreties, C. y otros. "Overcoming data scarcity in earth science". Data. [en línea]. 2020, vol. 5, no 1, pp. 1-5. DOI: 10.3390/data5010005
dc.identifierhttps://hdl.handle.net/20.500.12008/27059
dc.identifier10.3390/data5010005
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4981040
dc.description.abstractThe Data Scarcity problem is repeatedly encountered in environmental research. This may induce an inadequate representation of the response?s complexity in any environmental system to any input/change (natural and human-induced). In such a case, before getting engaged with new expensive studies to gather and analyze additional data, it is reasonable first to understand what enhancement in estimates of system performance would result if all the available data could be well exploited. The purpose of this Special Issue, "Overcoming Data Scarcity in Earth Science" in the Data journal, is to draw attention to the body of knowledge that leads at improving the capacity of exploiting the available data to better represent, understand, predict, and manage the behavior of environmental systems at meaningful space-time scales. This Special Issue contains six publications (three research articles, one review, and two data descriptors) covering a wide range of environmental fields: geophysics, meteorology/climatology, ecology, water quality, and hydrology.
dc.languageen
dc.publisherMDPI
dc.relationData, vol. 5, no 1, pp. 1-5, jan 2020.
dc.rightsLicencia Creative Commons Atribución (CC - By 4.0)
dc.rightsLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)
dc.subjectEarth-science data
dc.subjectData scarcity
dc.subjectMissing data
dc.subjectData quality
dc.subjectData imputation
dc.subjectStatistical methods
dc.subjectMachine learning
dc.subjectEnvironmental modeling
dc.subjectEnvironmental observations
dc.titleOvercoming data scarcity in earth science.
dc.typeArtículo


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