synthesisr (version 0.3.0)

read_refs: Import bibliographic search results

Description

Imports common bibliographic reference formats (i.e. .bib, .ris, or .txt).

Usage

read_refs(
  filename,
  tag_naming = "best_guess",
  return_df = TRUE,
  verbose = FALSE
)
read_ref(
  filename,
  tag_naming = "best_guess",
  return_df = TRUE,
  verbose = FALSE
)

Arguments

filename

A path to a filename or vector of filenames containing search results to import.

tag_naming

Either a length-1 character stating how should ris tags be replaced (see details for a list of options), or an object inheriting from class data.frame containing user-defined replacement tags.

return_df

If TRUE (default), returns a data.frame; if FALSE, returns a list.

verbose

If TRUE, prints status updates (defaults to FALSE).

Value

Returns a data.frame or list of assembled search results.

Functions

• read_ref: Import a single file

Details

The default for argument tag_naming is "best_guess", which estimates what database has been used for ris tag replacement, then fills any gaps with generic tags. Any tags missing from the database (i.e. code_lookup) are passed unchanged. Other options are to use tags from Web of Science ("wos"), Scopus ("scopus"), Ovid ("ovid") or Academic Search Premier ("asp"). If a data.frame is given, then it must contain two columns: "code" listing the original tags in the source document, and "field" listing the replacement column/tag names. The data.frame may optionally include a third column named "order", which specifies the order of columns in the resulting data.frame; otherwise this will be taken as the row order. Finally, passing "none" to replace_tags suppresses tag replacement.

Examples

# NOT RUN {
litsearchr <- c(
  "@article{grames2019,
  title={An automated approach to identifying search terms for
  systematic reviews using keyword co-occurrence networks},
  author={Grames, Eliza M and Stillman, Andrew N and Tingley, Morgan W and Elphick, Chris S},
  journal={Methods in Ecology and Evolution},
  volume={10},
  number={10},
  pages={1645--1654},
  year={2019},
  publisher={Wiley Online Library}
}"
)

tmp <- tempfile()

writeLines(litsearchr, tmp)

df <- read_refs(tmp, return_df = TRUE, verbose = TRUE)
# }