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dwctaxon has two major purposes, (1) editing and (2) validation of taxonomic data in Darwin Core (DwC) format. This vignette is about the latter.
Start by loading packages and setting the random number generator seed since this vignette involves some random samples.
library(dwctaxon)
library(dplyr)
set.seed(12345)As before,
we will use the example dataset that comes with dwctaxon,
dct_filmies:
dct_filmies
#> # A tibble: 2,451 × 5
#> taxonID acceptedNameUsageID taxonomicStatus taxonRank scientificName
#> <chr> <chr> <chr> <chr> <chr>
#> 1 54115096 <NA> accepted species Cephalomanes atrovirens Presl
#> 2 54133783 54115097 synonym species Trichomanes crassum Copel.
#> 3 54115097 <NA> accepted species Cephalomanes crassum (Copel.) M. G. Price
#> 4 54133784 54115098 synonym species Trichomanes densinervium Copel.
#> 5 54115098 <NA> accepted species Cephalomanes densinervium (Copel.) Copel.
#> 6 54133786 54115100 synonym species Cephalomanes curvatum (J. Sm.) V. D. Bosch
#> 7 54133787 54115100 synonym species Cephalomanes javanica (Bl.) V. D. Bosch
#> 8 54133788 54115100 synonym species Cephalomanes oblongifolium Presl
#> 9 54133789 54115100 synonym species Cephalomanes zollingeri V. D. Bosch
#> 10 54133790 54115100 synonym species Lacostea javanica (Bl.) Prantl
#> # ℹ 2,441 more rowsHowever, dct_filmies already is well-formatted and would
pass all validation checks! So lets introduce some noise to make things
more interesting.
filmies_dirty <-
dct_filmies |>
# Change taxonomic status of one row to 'good'
dct_modify_row(taxonID = "54115096", taxonomicStatus = "good") |>
# Duplicate some rows at the end
bind_rows(tail(dct_filmies)) |>
# Insert bad values for `acceptedNameUsageID` of 5 random rows
rows_update(
tibble(
taxonID = sample(dct_filmies$taxonID, 5),
acceptedNameUsageID = sample(letters, 5)
),
by = "taxonID"
)
filmies_dirty
#> # A tibble: 2,457 × 6
#> taxonID acceptedNameUsageID taxonomicStatus taxonRank scientificName modified
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 54115096 <NA> good species Cephalomanes atrovirens Presl 2023-12-13 18:14:21.349524
#> 2 54133783 54115097 synonym species Trichomanes crassum Copel. <NA>
#> 3 54115097 <NA> accepted species Cephalomanes crassum (Copel.) M. G. Price <NA>
#> 4 54133784 54115098 synonym species Trichomanes densinervium Copel. <NA>
#> 5 54115098 <NA> accepted species Cephalomanes densinervium (Copel.) Copel. <NA>
#> 6 54133786 54115100 synonym species Cephalomanes curvatum (J. Sm.) V. D. Bosch <NA>
#> 7 54133787 54115100 synonym species Cephalomanes javanica (Bl.) V. D. Bosch <NA>
#> 8 54133788 54115100 synonym species Cephalomanes oblongifolium Presl <NA>
#> 9 54133789 54115100 synonym species Cephalomanes zollingeri V. D. Bosch <NA>
#> 10 54133790 54115100 synonym species Lacostea javanica (Bl.) Prantl <NA>
#> # ℹ 2,447 more rowsThe first few rows may look the same, but we know that these data now have some problems.
dct_validate() is the workhorse function for validating
DwC data.
In default mode, dct_validate() will issue an error the
first time it finds something wrong with the data (in other words, on
the first check that fails):
dct_validate(filmies_dirty)
#> Error: check_taxon_id failed
#> taxonID detected with duplicated value
#> Bad taxonID: 54126747, 54135528, 54135530, 54135531, 54126748, 54126749dwctaxon tries to provide useful error messages that help you
determine what in the data is causing the problem. Here, we see that
rows with taxonID 54126747, 54135528, 54135530, 54135531,
54126748, and 54126749 are duplicated. Here of course we know that’s
because we duplicated them on purpose; in a real dataset, you could use
this information to search out the duplicated values and fix them.
If you are troubleshooting a DwC taxon dataset, it may be more useful
to know about all of the problems at once instead of fixing them one at
a time. In that case, set the on_fail argument to
"summary" (on_fail can be either its default
value "error" or "summary"):
dct_validate(filmies_dirty, on_fail = "summary")
#> Warning: taxonID detected with duplicated value
#> Warning: taxonID detected whose taxonomicStatus is not in valid_tax_status (accepted, synonym, variant, NA)
#> Warning: taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name.
#> Warning: scientificName detected with duplicated value
#> # A tibble: 18 × 6
#> taxonID acceptedNameUsageID scientificName taxonomicStatus error check
#> <chr> <chr> <chr> <chr> <glue> <chr>
#> 1 54133841 k Trichomanes cumingii (Presl) C. Chr. <NA> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name. check_mapping
#> 2 54134450 z Trichomanes omphalodes (Vieill.) C. Chr. <NA> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name. check_mapping
#> 3 54134462 b Trichomanes amabile Nakai <NA> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name. check_mapping
#> 4 54134950 v Mecodium atrovirens (Col.) Copel. <NA> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name. check_mapping
#> 5 54135730 x Leptocionium attenuatum (Hook.) Bosch <NA> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name. check_mapping
#> 6 54126747 <NA> Hymenophyllum myriocarpum var. endiviifolium (Desv.) Stolze <NA> scientificName detected with duplicated value check_sci_na…
#> 7 54135528 <NA> Hymenophyllum nigrescens Liebm. <NA> scientificName detected with duplicated value check_sci_na…
#> 8 54135530 <NA> Mecodium nigricans (Presl ex Kl.) Copel. <NA> scientificName detected with duplicated value check_sci_na…
#> 9 54135531 <NA> Sphaerocionium nigricans Presl ex Kl. <NA> scientificName detected with duplicated value check_sci_na…
#> 10 54126748 <NA> Hymenophyllum myriocarpum var. nigrescens (Liebm.) Stolze <NA> scientificName detected with duplicated value check_sci_na…
#> 11 54126749 <NA> Hymenophyllum trichophyllum var. buesii C. V. Morton <NA> scientificName detected with duplicated value check_sci_na…
#> 12 54115096 <NA> Cephalomanes atrovirens Presl good taxonID detected whose taxonomicStatus is not in valid_tax_status (accepted, synonym, variant, NA) check_tax_st…
#> 13 54126747 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…
#> 14 54135528 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…
#> 15 54135530 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…
#> 16 54135531 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…
#> 17 54126748 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…
#> 18 54126749 <NA> <NA> <NA> taxonID detected with duplicated value check_taxon_…(You may need to scroll to the right in the output below to see all the text).
In this case, dct_validate() still issues a warning to
let us know validation did not pass. The error and
check columns describe what went wrong; the other columns
tell us where in the data to find the errors.
With this detailed summary, we should definitely be able to hunt down the bugs in this dataset!
You may be wondering, why the separate “error” and “check” columns in the summary output?
That is because dct_validate() conducts many smaller
checks, each of which can be turned on or off. For a complete
description, run ?dct_validate(). In turn, the checks can
each identify different particular problems; the most granular
description is given in the “error” column.
Furthermore, each of the checks run by dct_validate()
can also be run as an individual function. For example, let’s just check
that all values of acceptedUsageID have a corresponding
taxonID (in other words, that all synonyms map
properly):
filmies_dirty |>
dct_check_mapping()
#> Error: check_mapping failed.
#> taxonID detected whose acceptedNameUsageID value does not map to taxonID of an existing name.
#> Bad taxonID: 54133841, 54134450, 54134462, 54134950, 54135730
#> Bad scientificName: Trichomanes cumingii (Presl) C. Chr., Trichomanes omphalodes (Vieill.) C. Chr., Trichomanes amabile Nakai, Mecodium atrovirens (Col.) Copel., Leptocionium attenuatum (Hook.) Bosch
#> Bad acceptedNameUsageID: k, z, b, v, xIt is important to note that not all checks are compatible with each
other. For example, check_sci_name checks that all
scientific names (DwC term scientificName) are non-missing
and unique; check_status_diff checks that in cases of
identical scientific names, the taxonomic status of each name
is different. The default settings for dct_validate() are
to use the former but not the latter. Whether you expect all scientific
names to be unique or not depends on how you set up your data1.
Some DwC taxon terms are expected only to take a small number values
from a controlled vocabulary. For example, taxonStatus
(taxonomic status of a scientific name) may only be expected to include
the values “accepted”, “synonym”, etc. This is unlike, e.g.,
scientificName, where we would not try to control the range
of possible values.
However, although DwC recommends using a controlled vocabulary for such terms, it does not specify the actual values! So dwctaxon lets you set those yourself (and tries to employ reasonable defaults), as shown in the next section.
Say you want to use a different set of allowed values for
taxonStatus. Here, let’s include “good” so that the data
will pass the check for taxonomic status (remember we modified the data so the
taxonomicStatus of one of the rows was
"good").
One way would be to use the valid_tax_status argument of
dct_validate() or dct_check_tax_status():
filmies_dirty |>
dct_check_tax_status(
valid_tax_status = "good, accepted, synonym",
on_success = "logical" # Issue "TRUE" if the check passes
)
#> [1] TRUEBut specifying this argument every time you want to check something gets tedious.
So we can change the default setting for
valid_tax_status with dct_options() like
so:
# First save the current settings before making any changes
old_settings <- dct_options()
# Change valid_tax_status setting
dct_options(valid_tax_status = "good, accepted, synonym")Now we can run dct_check_tax_status() and it will use
the new default value:
filmies_dirty |>
dct_check_tax_status(on_success = "logical")
#> [1] TRUEYou can change back to the original default values with
reset = TRUE:
dct_options(reset = TRUE)Now running the same code as above throws an error:
filmies_dirty |>
dct_check_tax_status(on_success = "logical")
#> Error: check_tax_status failed.
#> taxonID detected whose taxonomicStatus is not in valid_tax_status (accepted, synonym, variant, NA)
#> Bad taxonID: 54115096
#> Bad scientificName: Cephalomanes atrovirens Presl
#> Bad taxonomicStatus: goodThere are a large number of settings that can be modified. See
?dct_options() for a description of each.
You can view the current status of all options (default values) by
running dct_options() with no arguments:
dct_options()
#> $check_taxon_id
#> [1] TRUE
#>
#> $check_tax_status
#> [1] TRUE
#>
#> $check_mapping_accepted
#> [1] TRUE
#>
#> $check_mapping_parent
#> [1] TRUE
#>
#> $check_mapping_original
#> [1] TRUE
#>
#> $check_mapping_accepted_status
#> [1] FALSE
#>
#> $check_sci_name
#> [1] TRUE
#>
#> $check_status_diff
#> [1] FALSE
#>
#> $check_col_names
#> [1] TRUE
#>
#> $valid_tax_status
#> [1] "accepted, synonym, variant, NA"
#>
#> $extra_cols
#> NULL
#>
#> $skip_missing_cols
#> [1] FALSE
#>
#> $on_success
#> [1] "data"
#>
#> $on_fail
#> [1] "error"
#>
#> $fill_taxon_id
#> [1] TRUE
#>
#> $fill_usage_id
#> [1] TRUE
#>
#> $taxon_id_length
#> [1] 32
#>
#> $clear_usage_id
#> [1] TRUE
#>
#> $clear_usage_name
#> [1] TRUE
#>
#> $fill_usage_name
#> [1] TRUE
#>
#> $remap_names
#> [1] TRUE
#>
#> $remap_variant
#> [1] FALSE
#>
#> $stamp_modified
#> [1] TRUE
#>
#> $strict
#> [1] FALSE
#>
#> $quiet
#> [1] FALSEOr check the value of one particular setting by passing its name with
the $ operator:
dct_options()$valid_tax_status
#> [1] "accepted, synonym, variant, NA"We can restore the settings as they were before any of these changes
were applied by running do.call() on the settings we saved
above:
do.call(dct_options, old_settings)According to the rules of taxonomic nomenclature, of course each full scientific name should be unique, but there have been errors in the past where the same author published the same name more than once!↩︎
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.