This function downloads and sources the SHARK4R required and recommended field definitions directly from the SHARK4R-statistics GitHub repository.
Value
Invisibly returns a list with two elements:
- required_fields
Object containing required SHARK fields.
- recommended_fields
Object containing recommended SHARK fields.
Details
The definitions are stored in an R script (fields.R) located in the fields/ folder of the repository.
The function sources this file directly from GitHub into the current R session.
The sourced script defines two main objects:
required_fields— vector or data frame of required SHARK fields.recommended_fields— vector or data frame of recommended SHARK fields.
The output of this function can be directly supplied to the
check_fields function through its field_definitions argument
for validating SHARK4R data consistency.
If sourcing fails (e.g., due to a network issue or repository changes), the function throws an error with a descriptive message.
See also
check_fields for validating datasets using the loaded field definitions (as field_definitions).
load_shark4r_stats for loading precomputed SHARK4R statistics,
Examples
# \donttest{
# Load SHARK4R field definitions from GitHub
fields <- load_shark4r_fields(verbose = FALSE)
# Access required or recommended fields for the first entry
fields[[1]]$required
#> [1] "visit_year" "station_name"
#> [3] "sample_project_name_sv" "sample_orderer_name_sv"
#> [5] "platform_code" "sample_date"
#> [7] "sample_time" "sample_latitude_dd"
#> [9] "sample_longitude_dd" "positioning_system_code"
#> [11] "water_depth_m" "sample_min_depth_m"
#> [13] "sample_max_depth_m" "sampling_laboratory_name_sv"
#> [15] "sampling_laboratory_accreditated" "sampler_type_code"
#> [17] "sampled_volume_l" "scientific_name"
#> [19] "value" "quality_flag"
#> [21] "analysis_method_code" "method_reference_code"
#> [23] "analytical_laboratory_name_sv" "analytical_laboratory_accreditated"
#> [25] "analysed_volume_cm3" "preservation_method_code"
#> [27] "counted_portions" "reporting_institute_name_sv"
fields[[1]]$recommended
#> [1] "monitoring_program_code"
# }
if (FALSE) { # \dontrun{
# Use the loaded definitions in check_fields()
check_fields(my_data, field_definitions = fields)
} # }