knitr::opts_chunk$set(collapse = FALSE)
library(dplyr);library(impactr)
data_presentations <- readRDS("~/starsurg_impact/data/data_pre.rds") %>%
  dplyr::filter(level == "International") %>%
  dplyr::distinct(title, .keep_all = TRUE) %>%
  dplyr::mutate(title = ifelse(title=="Collaborative Research: How to Get Involved", NA, title)) %>%
  dplyr::mutate(author = ifelse(con_city=="Belfast", NA, author)) %>%
  dplyr::select(type:author) %>% dplyr::arrange(con_date_start) %>% tail(5)

out_doi <- impactr::extract_doi(doi = c("10.1136/bmjopen-2015-009812", "10.1136/bmjopen-2015-008811", "10.1002/bjs5.86"),
                       get_auth = TRUE, get_altmetric = FALSE, get_impact = FALSE)

Citation of Research Outputs

The most common vehicles for research impact tend to be for presentations and publications of the work conducted. These often are often listed at both an individual- (CV) and institutional-level to demonstrate scholary activity.

1. ref_publication()

The ref_publication() function will accept direct input from both extract_pmid() and extract_doi(), however will also accept other dataframes with the prerequisite columns. These columns can be specified within the function. Other features include:

 out_doi %>%
  # If a single-authorship collaborative publication (e.g. "STARSurg Collaborative") then display that
  dplyr::mutate(author = ifelse(is.na(author_group)==TRUE, author, author_group)) %>%

  impactr::ref_publication(journal = "journal_full", max_auth = 10,
                   ref_format = "author. title. journal. year; volume (issue): pages. PMID: pmid. DOI: doi.") %>%

  dplyr::mutate(citation = gsub("\\]", "", gsub("\\[", "", as.character(citation)))) %>%
  dplyr::select(citation) %>%
  knitr::kable(format="html") %>% kableExtra::kable_styling(bootstrap_options = "striped", full_width = F)

 

2. ref_presentation()

Presentations of academic work are important additional research outputs, yet are often not recorded online and so cannot be extracted. Therefore, the ref_presentation() function will accept any dataframe with the prerequisite columns. The columns can be specified within the function. Other features include:

col_pre7 <- which(colnames(data_presentations) %in% c("title"))
col_pre3 <- which(colnames(data_presentations) %in% c("author", "con_org", "con_name"))
col_pre1 <- which(colnames(data_presentations) %in% c("type", "con_country"))

 data_presentations %>%
     magrittr::set_colnames(gsub("_", " ", names(.))) %>%
  knitr::kable(format="html") %>%
  kableExtra::column_spec(col_pre7, width_min="7in") %>%
  kableExtra::column_spec(col_pre3, width_min="3in") %>%
  kableExtra::column_spec(col_pre1, width_min="1.5in") %>%
  kableExtra::kable_styling(bootstrap_options = "striped", full_width = F) %>%
  kableExtra::scroll_box(width = "1000px")

 

impactr::ref_presentation(data_presentations, ref_format = "author. title. con_org con_name, con_date_range, con_city (con_country).") %>%

  dplyr::mutate(citation = gsub("\\]", "", gsub("\\[", "", as.character(citation)))) %>%
  dplyr::select(citation) %>%
  knitr::kable(format="html") %>% kableExtra::kable_styling(bootstrap_options = "striped", full_width = F)

 



kamclean/impactr documentation built on Jan. 11, 2023, 2:51 p.m.