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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.
Health stats visible at Monitor.