Let’s try to access summary data for . We can access this data using its full name or its unique ISSN identifier.
## title issn
## 1 A Critical Introduction to Media and Communication Theory 1947-6264
## romeocolour preprint postprint pdf pre_embargo post_embargo
## 1 yellow can restricted restricted <NA> 12 months
## pdf_embargo
## 1 12 months
You can also search for partial matches.
## Warning in parse_answer(api_answer, multiple = multiple, key = api_key): 5 journals match your query terms.
## Warning in parse_answer(api_answer, multiple = multiple, key = api_key):
## Select one journal from the provided list or enable multiple = TRUE
## title issn
## 1 Biogeography 1345-0662
## 2 Frontiers of Biogeography 1948-6596
## 3 Global Ecology and Biogeography 1466-822X
## 4 Global Ecology and Biogeography Letters 0960-7447
## 5 Journal of Biogeography 0305-0270
If rromeo finds multiple journals matching your query terms, it will only return the list of titles and ISSN by default.
You can then use this list to select the exact journal you are looking for (in this case, it is recommended to use the ISSN).
Alternatively, you may want to get data for all those journals. To achieve this, you may enable the multiple
option:
## Warning in parse_answer(api_answer, multiple = multiple, key = api_key): 43 journals match your query terms.
## Recursively fetching data from each journal. This may take some time...
## title issn romeocolour preprint
## 41 Revolutionary Russia 0954-6545 green can
## 42 Swarm and Evolutionary Computation 2210-6502 green can
## 43 Trends in Evolutionary Biology 2036-265X green can
## postprint pdf pre_embargo post_embargo pdf_embargo
## 41 can cannot <NA> <NA> <NA>
## 42 can cannot <NA> <NA> <NA>
## 43 can can <NA> <NA> <NA>
Unfortunately, the API does not provide any way to search for full words. So in this case, when searching for journal with "Evolutionary"
in their titles, we also get results such as "Revolutionary Russia"
. We can manually remove those false positives:
has_evolutionary_title <- !grepl("\\w+evolutionary|evolutionary\\w+",
res$title, ignore.case = TRUE)
res <- res[has_evolutionary_title,]
This tool is useful in bibliometric studies. For example, we can now have a visual overview of the policies of journals in a given field:
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library("ggplot2")
theme_set(theme_minimal())
res %>%
select(preprint, postprint, pdf) %>%
tidyr::gather(key = "file", value = "policy") %>%
ggplot(aes(x = factor(file, c("preprint", "postprint", "pdf")),
fill = policy)) +
geom_histogram(stat = "count") +
xlab("")
## Warning: Ignoring unknown parameters: binwidth, bins, pad
## Warning: Ignoring unknown parameters: binwidth, bins, pad