Replaces publicly available data with data that has been manually cleaned and error-corrected for use in the paper Chesshire, P. R., Fischer, E. E., Dowdy, N. J., Griswold, T., Hughes, A. C., Orr, M. J., . . . McCabe, L. M. (In Press). Completeness analysis for over 3000 United States bee species identifies persistent data gaps. Ecography.
PaigeIntegrater(db_standardized = NULL, PaigeNAm = NULL, columnStrings = NULL)A data frame or tibble. Occurrence records as input.
A data frame or tibble. The Paige Chesshire dataset.
A list of character vectors. Each vector is a set of columns that will be used to iteratively match the public dataset against the Paige dataset.
Returns db_standardized (input occurrence records) with the Paige Chesshire data integrated.
if (FALSE) {
library(dplyr)
# set the DataPath to tempdir for this example
DataPath <- tempdir()
# Integrate Paige Chesshire's cleaned dataset.
PaigeNAm <- readr::read_csv(paste(DataPath, "Paige_data", "NorAmer_highQual_only_ALLfamilies.csv",
sep = "/"), col_types = ColTypeR()) %>%
# Change the column name from Source to dataSource to match the rest of the data.
dplyr::rename(dataSource = Source) %>%
# add a NEW database_id column
dplyr::mutate(
database_id = paste0("Paige_data_", 1:nrow(.)),
.before = scientificName)
# Set up the list of character vectors to iteratively check for matches with public data.
columnList <- list(
c("decimalLatitude", "decimalLongitude",
"recordNumber", "recordedBy", "individualCount", "samplingProtocol",
"associatedTaxa", "sex", "catalogNumber", "institutionCode", "otherCatalogNumbers",
"recordId", "occurrenceID", "collectionID"), # Iteration 1
c("catalogNumber", "institutionCode", "otherCatalogNumbers",
"recordId", "occurrenceID", "collectionID"), # Iteration 2
c("decimalLatitude", "decimalLongitude",
"recordedBy", "genus", "specificEpithet"), # Iteration 3
c("id", "decimalLatitude", "decimalLongitude"), # Iteration 4
c("recordedBy", "genus", "specificEpithet", "locality"), # Iteration 5
c("recordedBy", "institutionCode", "genus",
"specificEpithet","locality"),# Iteration 6
c("occurrenceID","decimalLatitude", "decimalLongitude"), # Iteration 7
c("catalogNumber","decimalLatitude", "decimalLongitude"), # Iteration 8
c("catalogNumber", "locality") # Iteration 9
)
# Merge Paige's data with downloaded data
db_standardized <- BeeBDC::PaigeIntegrater(
db_standardized = db_standardized,
PaigeNAm = PaigeNAm,
columnStrings = columnList)
}