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read_camtrapdp() now updates (or creates) the spatial,
temporal and taxonomic scope in the metadata based on the data (#130,
#164).read_camtrapdp() now upgrades datasets to Camtrap DP
1.0.1. The internal function convert() has been renamed to
upgrade() (#113).write_camtrapdp() writes a Camera Trap Data Package
to disk as a datapackage.json and CSV files (#137). This
means you can now read, update and write Camtrap DP datasets.contributors() returns a tibble with contributors
(#140).individuals() returns a data frame with unique
individuals (#149).taxa() now removes duplicates (#130).filter_deployments() and
deployments()<- now update the spatial, temporal and
taxonomic scope in the metadata based on the returned data (#100,
#132).filter_observations(), filter_media(),
media()<- and observations()<- now
update the taxonomic scope in the metadata based on the returned data
(#89, #100, #130).write_dwc() now adds
identificationVerificationStatus for observations
classified by humans with 100% certainty (#158).write_dwc() now allows to create occurrences from
media-based observations (#172).write_eml() transforms Camtrap DP metadata to EML
(#99). This function is used by GBIF to create metadata for a dataset
page.merge_camtrapdp() allows to merge two datasets
(#112). This can be useful to combine data from multiple studies.round_coordinates() allows to fuzzy/generalize
location information by rounding deployment latitude and
longitude. It also updates
coordinateUncertainty in the deployments and
coordinatePrecision and spatial scope in the metadata
(#106).shift_time() allows to shift/correct date-times in
data and metadata for specified deploymentIDs and duration (#108).update_taxon() allows to update taxonomic
information in data and metadata (#159).build_taxa() is renamed to
taxonomic() (#130).print() prints a human-readable summary of
the Camera Trap Data Package (#8).fieldsEnclosedBy issue in meta.xml, so
GBIF occurrence processing correctly handles commas in fields
(#95).write_dwc() no longer writes to "." by
default, since this is not allowed by CRAN policies. The user needs to
explicitly define a directory (#79).read_camtrapdp() reads data files from a
Camtrap DP into memory (#9). It will make the data easier to use, by
assigning taxonomic information (found in the metadata) to the
observations and eventIDs (found in the observations) to
the media (#37).deployments(),
media() and observations() return a data frame
with the deployments, media and observations respectively (#29). These
functions also have an assignment equivalent (#50).locations(),
events() and taxa() return a data frame with
unique locations, events and taxa respectively (#22, #57, #17).filter_deployments(),
filter_observations() and filter_media() allow
to filter data. They work similarly to dplyr’s
filter() (#23).write_dwc() transforms a Camera Trap Data
Package to a Darwin Core Archive (#55).example_package() returns the latest
Camtrap DP example dataset and caches the result (#24, #67).version() allows to get the version of a
camtrapdp object.check_camtrapdp() validates a
camtrapdp object (#34).convert() converts camtrapdp
objects to the latest version. This function is currently not used, as
the only supported version is Camtrap DP 1.0 (#9).%>%) is included in NAMESPACE, so you don’t have to
load dplyr (or magrittr) to use it (#56). %>% and
.data are imported at package level, so they can be used in
functions without namespace (#37).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.