cr_cn(dois="10.16126/science.169.3946.635")
cr_cn(dois="10.1126/science.169.3946.635", "citeproc-json")
cr_cn(dois="10.1126/science.169.3946.635", "citeproc-json-ish")
cr_cn("10.1126/science.169.3946.635", "rdf-xml")
cr_cn("10.1126/science.169.3946.635", "crossref-xml")
cr_cn("10.1126/science.169.3946.635", "text")
# return an R bibentry type
cr_cn("10.1126/science.169.3946.635", "bibentry")
cr_cn("10.6084/m9.figshare.97218", "bibentry")
# return an apa style citation
cr_cn("10.1126/science.169.3946.635", "text", "apa")
cr_cn("10.1126/science.169.3946.635", "text", "harvard3")
cr_cn("10.1126/science.169.3946.635", "text", "elsevier-harvard")
cr_cn("10.1126/science.169.3946.635", "text", "ecoscience")
cr_cn("10.1126/science.169.3946.635", "text", "heredity")
cr_cn("10.1126/science.169.3946.635", "text", "oikos")
# example with many DOIs
dois <- cr_r(2)
cr_cn(dois, "text", "apa")
# Cycle through random styles - print style on each try
stys <- get_styles()
foo <- function(x){
cat(sprintf("<Style>:%s\n", x), sep = "\n\n")
cr_cn("10.1126/science.169.3946.635", "text", style=x)
}
foo(sample(stys, 1))
# Using DataCite DOIs
## some formats don't work
# cr_cn("10.5284/1011335", "text")
# cr_cn("10.5284/1011335", "crossref-xml")
# cr_cn("10.5284/1011335", "crossref-tdm")
## But most do work
cr_cn("10.5284/1011335", "datacite-xml")
cr_cn("10.5284/1011335", "rdf-xml")
cr_cn("10.5284/1011335", "turtle")
cr_cn("10.5284/1011335", "citeproc-json")
cr_cn("10.5284/1011335", "ris")
cr_cn("10.5284/1011335", "bibtex")
cr_cn("10.5284/1011335", "bibentry")
cr_cn("10.5284/1011335", "bibtex")
dois <- c('10.5167/UZH-30455','10.5167/UZH-49216','10.5167/UZH-503',
'10.5167/UZH-38402','10.5167/UZH-41217')
cat(cr_cn(dois[1]))
cat(cr_cn(dois[2]))
cat(cr_cn(dois[3]))
cat(cr_cn(dois[4]))
# Get raw output
cr_cn(dois = "10.1002/app.27716", format = "citeproc-json", raw = TRUE)
Run the code above in your browser using DataLab