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Statements

Subject Item
n2:RIV%2F61989592%3A15310%2F12%3A33141590%21RIV13-MSM-15310___
rdf:type
n6:Vysledek skos:Concept
dcterms:description
Applied geochemistry and environmental sciences invariably deal with compositional data. Classically, the original or log-transformed absolute element concentrations are studied. However, compositional data do not vary independently, and a concentration based approach to data analysis can lead to faulty conclusions. For this reason a better statistical approach was introduced in the 1980s, exclusively based on relative information. Because the difference between the two methods should be most pronounced in large-scale, and therefore highly variable, datasets, here a new dataset of agricultural soils, covering all of Europe (5.6 million km2) at an average sampling density of 1 site/2500 km2, is used to demonstrate and compare both approaches. Absolute element concentrations are certainly of interest in a variety of applications and can be provided in tabulations or concentration maps. Maps for the opened data (ratios to other elements) provide more specific additional information. For compositional data XY plots for raw or log-transformed data should only be used with care in an exploratory data analysis (EDA) sense, to detect unusual data behaviour, candidate subgroups of samples, or to compare pre-defined groups of samples. Correlation analysis and the Euclidean distance are not mathematically meaningful concepts for this data type. Element relationships have to be investigated via a stability measure of the (log-)ratios of elements. Logratios are also the key ingredient for an appropriate multivariate analysis of compositional data. Applied geochemistry and environmental sciences invariably deal with compositional data. Classically, the original or log-transformed absolute element concentrations are studied. However, compositional data do not vary independently, and a concentration based approach to data analysis can lead to faulty conclusions. For this reason a better statistical approach was introduced in the 1980s, exclusively based on relative information. Because the difference between the two methods should be most pronounced in large-scale, and therefore highly variable, datasets, here a new dataset of agricultural soils, covering all of Europe (5.6 million km2) at an average sampling density of 1 site/2500 km2, is used to demonstrate and compare both approaches. Absolute element concentrations are certainly of interest in a variety of applications and can be provided in tabulations or concentration maps. Maps for the opened data (ratios to other elements) provide more specific additional information. For compositional data XY plots for raw or log-transformed data should only be used with care in an exploratory data analysis (EDA) sense, to detect unusual data behaviour, candidate subgroups of samples, or to compare pre-defined groups of samples. Correlation analysis and the Euclidean distance are not mathematically meaningful concepts for this data type. Element relationships have to be investigated via a stability measure of the (log-)ratios of elements. Logratios are also the key ingredient for an appropriate multivariate analysis of compositional data.
dcterms:title
The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils in Europe The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils in Europe
skos:prefLabel
The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils in Europe The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils in Europe
skos:notation
RIV/61989592:15310/12:33141590!RIV13-MSM-15310___
n6:predkladatel
n18:orjk%3A15310
n3:aktivita
n16:Z
n3:aktivity
Z(MSM6198959214)
n3:cisloPeriodika
duben
n3:dodaniDat
n11:2013
n3:domaciTvurceVysledku
n15:5138299
n3:druhVysledku
n10:J
n3:duvernostUdaju
n12:S
n3:entitaPredkladatele
n8:predkladatel
n3:idSjednocenehoVysledku
128367
n3:idVysledku
RIV/61989592:15310/12:33141590
n3:jazykVysledku
n19:eng
n3:klicovaSlova
Agricultural soil, XRF, Major elements, Europe, Geochemistry, Compositional data
n3:klicoveSlovo
n9:Europe n9:XRF n9:Compositional%20data n9:Major%20elements n9:Geochemistry n9:Agricultural%20soil
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[DBEC5E9E4547]
n3:nazevZdroje
Science of the Total Environment
n3:obor
n7:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
8
n3:rokUplatneniVysledku
n11:2012
n3:svazekPeriodika
426
n3:tvurceVysledku
Ladenberger, Anna Reimann, Clemens Hron, Karel Fabian, Karl Filzmoser, Peter Birke, Manfred Demetriades, Alecos Dinelli, Enrico
n3:wos
000304795300023
n3:zamer
n14:MSM6198959214
s:issn
0048-9697
s:numberOfPages
15
n20:doi
10.1016/j.scitotenv.2012.02.032
n13:organizacniJednotka
15310