IsoMemo is a Big Data initiative bringing together isotopic data from archaeology, ecology, and environmental & life sciences. Isotopic tracers are used across a variety of research fields to provide a rich diversity of scientific information, but lack of centralized storage limits efficient data use. The IsoMemo initiative brings together independent repositories of isotopic data within the fields of archaeology, ecology, and environmental & life sciences. The goals of the initiative are to make isotopic data easily findable and accessible so that it can be easily reused for research purposes. IsoMemo also promotes the creation of data standards and interoperability with other types. Within IsoMemo each independent database self-manages and curates their data and defines metadata requirements. However, the initiative also promotes the creation of networks linking different databases.
This R package to retrieve data from Max-Planck-Institute (MPI) IsoMemo Web-application API and publish on CRAN for public download. For more information and access all IsoMemo Apps: https://isomemoapp.com/
Isomemo Project Director:
Developer: INWT Statistics GmbH
You can install the released version of IsoMemo from CRAN with:
install.packages("IsoMemo")
#> Installiere Paket nach '/home/ljabel/R/x86_64-pc-linux-gnu-library/4.3'
#> (da 'lib' nicht spezifiziert)And the development version from GitHub with:
options(repos = c(getOption("repos"), PANDORA = "https://Pandora-IsoMemo.github.io/drat/"))
install.packages("IsoMemo")
#> Installiere Paket nach '/home/ljabel/R/x86_64-pc-linux-gnu-library/4.3'
#> (da 'lib' nicht spezifiziert)options(repos = c(getOption("repos"), PANDORA = "https://Pandora-IsoMemo.github.io/drat/"))
install.packages("IsoMemo")
#> Installiere Paket nach '/home/ljabel/R/x86_64-pc-linux-gnu-library/4.3'
#> (da 'lib' nicht spezifiziert)
library(IsoMemo)
## basic example code
df = getData(db="LiVES")
head(df)
#> source id description d13C d15N latitude longitude
#> 1 LiVES 1000 Ajdovska Jama 21 , S Neo (Lengyel) -20.4 9.0 45.9667 15.4833
#> 2 LiVES 1001 Ajdovska Jama 3 , S Neo (Lengyel) -20.6 8.1 45.9667 15.4833
#> 3 LiVES 1002 Ajdovska Jama 6 , S Neo (Lengyel) -20.8 9.0 45.9667 15.4833
#> 4 LiVES 1003 Ajdovska Jama 7 , S Neo (Lengyel) -20.3 8.1 45.9667 15.4833
#> 5 LiVES 1004 Ajdovska Jama , S Neo (Lengyel) -22.4 5.8 45.9667 15.4833
#> 6 LiVES 1005 Ajdovska Jama , S Neo (Lengyel) -21.0 6.6 45.9667 15.4833
#> site dateMean dateLower dateUpper dateUncertainty datingType
#> 1 Ajdovska Jama 5365 4328 4055 31 radiocarbon
#> 2 Ajdovska Jama 5421 4340 4235 30 radiocarbon
#> 3 Ajdovska Jama 5436 4344 4244 30 radiocarbon
#> 4 Ajdovska Jama 5485 4448 4243 50 radiocarbon
#> 5 Ajdovska Jama 4250 4450 4050 100 expert
#> 6 Ajdovska Jama 4250 4450 4050 100 expert
# with category argument
df = getData(db="LiVES",category = "Location")
head(df)
#> latitude longitude site
#> 1 45.9667 15.4833 Ajdovska Jama
#> 2 45.9667 15.4833 Ajdovska Jama
#> 3 45.9667 15.4833 Ajdovska Jama
#> 4 45.9667 15.4833 Ajdovska Jama
#> 5 45.9667 15.4833 Ajdovska Jama
#> 6 45.9667 15.4833 Ajdovska Jama
# with field argument
df = getData(db="LiVES",category = "Location",field= "latitude")
head(df)
#> latitude
#> 1 45.9667
#> 2 45.9667
#> 3 45.9667
#> 4 45.9667
#> 5 45.9667
#> 6 45.9667