Integrate manually-cleaned data from Paige Chesshire

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)

Arguments

db_standardized

A data frame or tibble. Occurrence records as input.

PaigeNAm

A data frame or tibble. The Paige Chesshire dataset.

columnStrings

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.

Value

Returns db_standardized (input occurrence records) with the Paige Chesshire data integrated.

Examples

if (FALSE) { # \dontrun{
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)
} # }