R/create_eml.R
In EDIorg/hymetDP: Tools to Create, Use, and Convert hymetDP data
Defines functions
create_eml
Documented in
create_eml
#' Create EML metadata
#'
#' @param path (character) Path to the directory containing hymetDP tables,
#' conversion script, and where EML metadata will be written.
#' @param source_id (character) Identifier of a data package published in a
#' supported repository. Currently, the EDI Data Repository is supported.
#' @param derived_id (character) Identifier of the dataset being created.
#' @param script (character) Name of file used to convert \code{source_id} to
#' \code{derived_id}.
#' @param script_description (character) Description of \code{script}.
#' @param is_about (named character) An optional argument for specifying dataset
#' level annotations describing what this dataset "is about".
#' @param contact (data.frame) Contact information for the person that created
#' this hymetDP dataset, containing these columns: \itemize{ \item givenName
#' \item surName \item organizationName \item electronicMailAddress }
#' @param user_id (character) Identifier of user associated with
#' \code{user_domain}.
#' @param user_domain (character) Domain (data repository) the \code{user_id}
#' belongs to. Currently, EDI is supported.
#' @param url (character) URL to the publicly accessible directory containing
#' hymetDP tables, conversion script, and EML metadata. This argument supports
#' direct download of the data entities by a data repository and is used for
#' automated revisioning and publication.
#'
#' @return An EML metadata file.
#'
#' @details This function creates an EML record for a hymetDP dataset by
#' combining metadata from \code{source_id} with boiler-plate metadata
#' describing the hymetDP model. Changes to the \code{source_id} EML include:
#' \itemize{ \item \strong{`<access>`} Adds \code{user_id} to the list of
#' principals granted read and write access to the hymetDP data package this
#' EML describes. \item \strong{`<title>`} Adds a note that this is a derived
#' data package in the hymetDP format. \item \strong{`<pubDate>`} Adds the
#' date this EML was created. \item \strong{`<abstract>`} Adds a note that
#' this is a derived data package in the hymetDP format. \item
#' \strong{`<keywordSet>`} Adds the "hymetDP" keyword to enable search and
#' discovery of all hymetDP data packages in the data repository it is
#' published. \item \strong{`<intellectualRights>`} Keeps intact the original
#' intellectual rights license \code{source_id} was released under, or uses
#' \href{https://creativecommons.org/publicdomain/zero/1.0/legalcode}{CCO} if
#' missing. \item \strong{`<contact>`} Adds the hymetDP creator as a point of
#' contact. \item \strong{`<methodStep>`} Adds a note that this data package
#' was created by the \code{script}, and adds provenance metadata noting that
#' this is a derived dataset and describes where the \code{source_id} can be
#' accessed. \item \strong{`<dataTables>`} Replaces the \code{source_id} table
#' metadata with descriptions of the the hymetDP tables. \item
#' \strong{`<otherEntity>`} Adds \code{script} and \code{script_description}.
#' otherEntities of \code{source_id} are removed. \item
#' \strong{`<annotations>`} Adds boilerplate annotations describing the
#' hymetDP at the dataset, entity, and entity attribute levels. }
#'
#'
#' @export
#'
#' @examples
#' \dontrun{
#' # Create directory with hymetDP tables for create_eml()
#' mypath <- paste0(tempdir(), "/data")
#' dir.create(mypath)
#' inpts <- c(hymet_L1$tables, path = mypath)
#' do.call(write_tables, inpts)
#' file.copy(system.file("extdata", "create_hymetDP.R", package = "hymetDP"), mypath)
#' dir(mypath)
#'
#' # Add self as contact information incase questions arise
#' additional_contact <- data.frame(
#' givenName = 'Kyle',
#' surName = 'Zollo-Venecek',
#' organizationName = 'Environmental Data Initiative',
#' electronicMailAddress = 'hymetdp@gmail.com',
#' stringsAsFactors = FALSE)
#'
#' # Create EML
#' eml <- create_eml(
#' path = mypath,
#' source_id = "knb-lter-mcm.9003.11",
#' derived_id = "edi.10101.1",
#' is_about = dataset_annotations,
#' script = "create_hymetDP.R",
#' script_description = "A function for converting knb-lter-mcm.9003 to hymetDP",
#' contact = additional_contact,
#' user_id = 'hymetdp',
#' user_domain = 'EDI')
#'
#' dir(mypath)
#' View(eml)
#'
#' # Clean up
#' unlink(mypath, recursive = TRUE)
#' }
#'
create_eml <- function(path,
source_id = NULL,
derived_id,
script,
script_description,
is_about = NULL,
contact,
user_id,
user_domain,
url = NULL) {
message("Creating EML for derived data package (" , derived_id, ")")
# Load Global Environment config --------------------------------------------
if (exists("config.repository", envir = .GlobalEnv)) {
repository <- get("config.repository", envir = .GlobalEnv)
} else {
repository <- "EDI"
}
if (exists("config.environment", envir = .GlobalEnv)) {
environment <- get("config.environment", envir = .GlobalEnv)
} else {
environment <- "production"
}
# Validate inputs -----------------------------------------------------------
validate_arguments(fun.name = "create_eml", fun.args = as.list(environment()))
# Parameterize --------------------------------------------------------------
# Read attributes of hymetDP tables for reference
attr_tbl <- read_criteria()
attr_tbl <- attr_tbl[!is.na(attr_tbl$column), ]
# Get table names for this L1 dataset for use in EAL_make_eml()
data.table <- unlist(
lapply(
unique(attr_tbl$table),
function(x) {
hymetDP_table <- stringr::str_detect(
list.files(path),
paste0("(?<=.{0,10000})", x, "(?=\\.[:alnum:]*$)"))
if (any(hymetDP_table)) {
list.files(path)[hymetDP_table]
}
}))
# Arrange tables in the preferred order to be listed in the EML
fext <- unique(tools::file_ext(data.table))
preferred_order <- c("Variables", "Methods", "Sites", "Sources",
"QualityControlLevels", "Qualifiers", "DataValues", "SeriesCatalog")
use_i <- preferred_order %in% tools::file_path_sans_ext(data.table)
data.table <- paste0(preferred_order[use_i], ".", fext)
# Match table names of this L1 to their boiler plate descriptions for use in
# EAL_make_eml()
descriptions <- data.table::fread(
system.file("extdata", "table_descriptions.txt", package = "hymetDP"))
data.table.description <- descriptions$description[
match(
stringr::str_remove_all(
data.table,
"(\\.[:alnum:]*$)"),
descriptions$table_name)]
# Map scripts and their descriptions to their EAL_make_eml()
# equivalents
if (!is.null(script)) {
other.entity <- script
other.entity.description <- script_description
} else {
other.entity <- NULL
other.entity.description <- NULL
}
# Expand url for each data object of this L1 for use in
# EAL_make_eml()
if (!is.null(url)) {
if (!is.null(data.table)) {
data.table.url <- paste0(url, "/", data.table)
}
if (!is.null(other.entity)) {
other.entity.url <- paste0(url, "/", other.entity)
}
} else {
data.table.url <- NULL
other.entity.url <- NULL
}
# Read L0 EML ---------------------------------------------------------------
message("Reading EML of L0 data package ", source_id)
# Create two objects of the same metadata, eml_L0 (emld list object) for
# editing, and xml_L0 (xml_document) for easy parsing
if (environment == "production") {
url_parent <- paste0(
"https://pasta.lternet.edu/package/metadata/eml/",
stringr::str_replace_all(source_id, "\\.", "/"))
} else if (environment == "staging") {
url_parent <- paste0(
"https://pasta-s.lternet.edu/package/metadata/eml/",
stringr::str_replace_all(source_id, "\\.", "/"))
}
# TODO accesses EDI
eml_L0 <- tryCatch({EML::read_eml(url_parent)},
error = function(e) {
stop("The EDI Repository is down for regular maintenance (Wednesday 01:00",
" - 03:00 UTC). If you have reached this message outside maintenance",
" hours, then there is an unexpected issue that will be resolved ",
"shortly. Our apologies for the inconvenience. Please try again ",
"later.", call. = FALSE)
})
xml_L0 <- suppressMessages(read_eml(source_id))
# Remove L0 elements that should not be inherited by the L1
eml_L0$dataset$dataTable <- NULL
eml_L0$dataset$spatialRaster <- NULL
eml_L0$dataset$spatialVector <- NULL
eml_L0$dataset$storedProcedure <- NULL
eml_L0$dataset$view <- NULL
eml_L0$dataset$otherEntity <- NULL
eml_L0$additionalMetadata <- NULL
# Create L1 EML -------------------------------------------------------------
message("Creating EML of L1 data package ", derived_id)
# This will not be a full EML record, it will only contain sections of the L1
# EML to combined with the L0 EML.
# Create list of inputs to EAL_make_eml()
eal_inputs <- EAL_template_arguments(
path = system.file("extdata", "/hymetDP", package = "hymetDP"),
data.path = path,
data.table = data.table,
other.entity = script)
eal_inputs$path <- system.file("extdata", "/hymetDP", package = "hymetDP")
eal_inputs$data.path <- path
eal_inputs$eml.path <- path
eal_inputs$dataset.title <- "placeholder"
eal_inputs$data.table <- data.table
eal_inputs$data.table.name <- tools::file_path_sans_ext(data.table)
eal_inputs$data.table.description <- data.table.description
eal_inputs$data.table.url <- data.table.url
eal_inputs$data.table.quote.character <- rep('"', length(data.table))
eal_inputs$other.entity <- other.entity
eal_inputs$other.entity.name <- tools::file_path_sans_ext(other.entity)
eal_inputs$other.entity.description <- other.entity.description
eal_inputs$other.entity.url <- other.entity.url
eal_inputs$package.id <- derived_id
eal_inputs$user.id <- user_id
eal_inputs$user.domain <- user_domain
eal_inputs$return.obj <- TRUE
# Remove unused data table attributes templates. All boiler plate attributes*
# files are read in with EAL_template_arguments() above, but
# only the ones being used should be kept and used in
# EAL_make_eml().
all_attribute_templates <- names(eal_inputs$x$template)[
stringr::str_detect(
names(eal_inputs$x$template),
"attributes_")]
expected_attribute_templates <- paste0(
"attributes_",
stringr::str_remove(data.table, "\\.[:alnum:]*$"),
".txt")
unused_attribute_templates <- all_attribute_templates[
!(all_attribute_templates %in% expected_attribute_templates)]
eal_inputs$x$template[
names(eal_inputs$x$template) %in% unused_attribute_templates] <- NULL
# Update attributes_* templates ----------------------------------------------
# Change unit of TimeSupport in Variables attributes
# TODO how to handle multiple units? Impossible?
eal_inputs$x$template$attributes_Variables.txt$content$unit[
eal_inputs$x$template$attributes_Variables.txt$content$attributeName == "TimeSupport"] <- unique(eal_inputs$x$data.table$Variables.csv$content$TimeUnitsName)
# Change <NoDataValue> in DataValues Missing value attributes template with
# the value specified in Variable table column NoDataValue
# TODO how to handle multiple missing values
eal_inputs$x$template$attributes_DataValues.txt$content$missingValueCode[
eal_inputs$x$template$attributes_DataValues.txt$content$missingValueCode == "<NoDataValue>"] <- unique(eal_inputs$x$data.table$Variables.csv$content$NoDataValue)
# Detect date and time format string directly from each table and add to the
# corresponding data table attributes template as required by
# EAL_make_eml().
for (i in expected_attribute_templates) {
date_column <- eal_inputs$x$template[[i]]$content$attributeName[
eal_inputs$x$template[[i]]$content$class == "Date"]
if (length(date_column) != 0) {
data_table <- which(
stringr::str_detect(
names(eal_inputs$x$data.table),
paste0(
"^",
stringr::str_extract(i, "(?<=attributes_).*(?=\\.txt)"),
"\\.[:alnum:]*$")))
for (j in seq(length(date_column))) {
datetime <- eal_inputs$x$data.table[[data_table]]$content[[date_column[[j]]]]
datetime_format <- parse_datetime_frmt_from_vals(datetime)
eal_inputs$x$template[[i]]$content$dateTimeFormatString[
eal_inputs$x$template[[i]]$content$attributeName == date_column[[j]]] <-
datetime_format
}
}
}
# Get table attributes and definitions from EML then create catvars templates for each data table of this dataset
# Add ODM CV terms as cat vars --------------------------------------------
cv_tbls <- subset(attr_tbl, !is.na(attr_tbl$cv))
r <- lapply(
# for each data table
unique(cv_tbls$table),
function(tbl) {
cont <- lapply(
cv_tbls$column[cv_tbls$table == tbl],
function(col) {
univars <- unique(eal_inputs$x$data.table[[paste0(tbl, '.csv')]]$content[[col]])
unidefs <- lapply(
univars,
function(var) {
cv <- cv_tbls$cv[cv_tbls$table == tbl & cv_tbls$column == col]
if (cv == "UnitsCV") {
t <- get(cv)
paste0("Unit: ",
t$UnitsName[t$UnitsName == var],
" (", t$UnitsAbbreviation[t$UnitsName == var], "); UnitType: ",
t$UnitsType[t$UnitsName == var]
)
} else if (cv == "SpatialReferencesCV") {
paste0("Spatial Reference System: ", var)
} else {
t <- get(cv)
t$Definition[t$Term == var]
}
})
catvars_template <- data.frame(
attributeName = col,
code = univars,
definition = unlist(unidefs),
stringsAsFactors = FALSE)
return(list(content = catvars_template))
})
# Manually add in the isRegular code and definition to catvars_Variables
if (tbl == 'Variables') {
cont[[8]] <- list(content = data.frame(
attributeName = "IsRegular",
code = c("TRUE", "FALSE"),
definition = c("Data values are from a regularly sampled time series", "Data values are not from a regularly sampled time series"),
stringsAsFactors = FALSE))
}
return(dplyr::bind_rows(cont))
})
names(r) <- paste0("catvars_", unique(cv_tbls$table), ".txt")
r <- Filter(Negate(is.null), r)
eal_inputs$x$template <- c(eal_inputs$x$template, r)
# The annotations template read in with EAL_template_arguments()
# serves as a map from tables of this L1 to the boilerplate annotations
# which are compiled here.
# TODO everything below involves annotations/variable mapping and should be added back!
annotations_map <- eal_inputs$x$template$annotations.txt$content
annotations <- annotations_map[0, ]
annotations <- rbind(
annotations,
annotations_map[annotations_map$context %in% "eml", ])
if (!is.null(is_about)) {
additional_dataset_annotations <- data.frame(
id = "/dataset",
element = "/dataset",
context = "eml",
subject = "dataset",
predicate_label = "is about",
predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
object_label = names(is_about),
object_uri = unname(is_about),
stringsAsFactors = FALSE)
annotations <- rbind(annotations, additional_dataset_annotations)
}
# TODO i wonder if there is a better object than analysis code. Processing code?
other_entity_annotations <- data.frame(
id = paste0("/", script),
element = "/otherEntity",
context = "dataset",
subject = script,
predicate_label = "is about",
predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
object_label = "analysis code",
object_uri = "http://purl.dataone.org/odo/ECSO_00002489",
stringsAsFactors = FALSE)
annotations <- rbind(annotations, other_entity_annotations)
for (i in data.table) {
table <- stringr::str_remove(i, "\\.[:alpha:]*$")
annotations_subset <- dplyr::filter(
annotations_map,
subject %in% table | context %in% table)
table_annotations <- annotations_subset[
annotations_subset$subject %in%
c(colnames(eal_inputs$x$data.table[[i]]$content), table), ]
table_annotations$id <- stringr::str_replace(
table_annotations$id,
paste0("(?<=/)", table, "(?=$|/)"),
i)
table_annotations$context <- stringr::str_replace(
table_annotations$context, table, i)
table_annotations$subject <- stringr::str_replace(
table_annotations$subject, paste0("^", table, "$"), i)
annotations <- rbind(annotations, table_annotations)
}
# variable_mapping <- stringr::str_subset(
# names(eal_inputs$x$data.table),
# "variable_mapping")
# if (length(variable_mapping) != 0) {
# tblnms_varmap <- eal_inputs$x$data.table[[variable_mapping]]$content$table_name # remove missing tables from variable_mapping
# tblnms_input <- tools::file_path_sans_ext(data.table)
# tbls2keep <- tblnms_varmap %in% tblnms_input
# eal_inputs$x$data.table[[variable_mapping]]$content <- eal_inputs$x$data.table[[variable_mapping]]$content[tbls2keep, ]
# variable_mappings_annotations <- lapply(
# unique(eal_inputs$x$data.table[[variable_mapping]]$content$table_name),
# function(table) {
# variable_mapping_subset <- dplyr::filter(
# eal_inputs$x$data.table[[variable_mapping]]$content,
# table_name == table)
# file_name <- stringr::str_subset(
# names(eal_inputs$x$data.table),
# paste0(table, "\\.[:alpha:]*$"))
#
# if (!is.null(variable_mapping_subset$mapped_label)) { # Handle missing columns
# objlbl <- variable_mapping_subset$mapped_label
# } else {
# objlbl <- ""
# }
# if (!is.null(variable_mapping_subset$mapped_id)) {
# objuri <- variable_mapping_subset$mapped_id
# } else {
# objuri <- ""
# }
#
# annotation <- data.frame(
# id = paste0("/", file_name, "/variable_name"),
# element = "/dataTable/attribute",
# context = file_name,
# subject = "variable_name",
# predicate_label = "is about",
# predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
# object_label = objlbl,
# object_uri = objuri,
# stringsAsFactors = FALSE)
# # Remove duplicate annotations or the variable_name attribute (a column
# # containing multiple variables as apart of a "long" table) will have
# # more than one of the same annotation
# annotation <- dplyr::distinct(
# annotation,
# object_label,
# object_uri,
# .keep_all = TRUE)
# return(annotation)
# })
# annotations <- rbind(
# annotations,
# data.table::rbindlist(variable_mappings_annotations))
# }
annotations[annotations == ""] <- NA_character_
annotations <- annotations[stats::complete.cases(annotations), ]
eal_inputs$x$template$annotations.txt$content <- annotations
# Only include metadata for existing columns (attributes)
for (i in data.table) {
table <- stringr::str_remove(i, "\\.[:alpha:]*$")
tmplt <- paste0("attributes_", table, ".txt")
attrnms <- eal_inputs$x$template[[tmplt]]$content$attributeName
colnms <- colnames(eal_inputs$x$data.table[[i]]$content)
attrs_to_keep <- attrnms %in% colnms
eal_inputs$x$template[[tmplt]]$content <- eal_inputs$x$template[[tmplt]]$content[attrs_to_keep, ]
}
# Call EAL_make_eml()
eml_L1 <- suppressWarnings(
suppressMessages(
do.call(
EAL_make_eml,
eal_inputs[
names(eal_inputs) %in% names(formals(EAL_make_eml))])))
# Update <eml> --------------------------------------------------------------
message("Updating:")
message("<eml>")
eml_L0$schemaLocation <- paste0(
"https://eml.ecoinformatics.org/eml-2.2.0 ",
"https://nis.lternet.edu/schemas/EML/eml-2.2.0/xsd/eml.xsd")
eml_L0$packageId <- derived_id
eml_L0$system <- "edi"
# Update <access> -----------------------------------------------------------
# Access control rules are used by some repositories to manage
# editing, viewing, downloading permissions. Adding the user_id and
# user_domain here expands editing permission to the creator of the DwC-A
# data package this EML will be apart of.
if (length(unlist(eml_L0$access$allow)) == 2) { # prevent single allow issue
eml_L0$access$allow <- list(eml_L0$access$allow,eml_L0$access$allow)
}
eml_L0$access$allow <- unique(
c(eml_L0$access$allow,
eml_L1$access$allow))
# Update <dataset> ----------------------------------------------------------
# For purposes of annotation references, the <dataset> attribute (which may
# have been set by the L0 creator) needs to be set to "dataset", which is
# expected by the L1 dataset annotation.
eml_L0$dataset$id <- "dataset"
# Remove <alternateIdentifier> ----------------------------------------------
# Some repositories assign a DOI to this element. Not removing it here
# an error when uploading to the repository.
message(" <dataset>")
message(" <alternateIdentifier>")
eml_L0$dataset$alternateIdentifier <- NULL
# Update <title> ------------------------------------------------------------
# Add notification the user that this is an hymetDP data package
message(" <title>")
eml_L0$dataset$title <- paste(
eml_L0$dataset$title, "(Reformatted to the hymetDP Design Pattern)")
# Update <pubDate> ----------------------------------------------------------
message(" <pubDate>")
eml_L0$dataset$pubDate <- format(Sys.time(), "%Y-%m-%d")
# Updating <abstract> -------------------------------------------------------
# Add link to L0 data packages and combine L0 and L1 abstracts
eml_L1$dataset$abstract$para[[1]] <- stringr::str_replace(
eml_L1$dataset$abstract$para[[1]],
"L0_PACKAGE_URL",
url_parent)
L1_para <- eml_L1$dataset$abstract$para[[1]]
L0_para <- xml2::xml_text(
xml2::xml_find_all(xml_L0, ".//abstract//para"))
eml_L0$dataset$abstract <- NULL
eml_L0$dataset$abstract$para <- c(
list(L1_para),
list(L0_para))
# Update <keywordSet> -------------------------------------------------------
# Add hymetDP specific keywords to the L0 keywords
message(" <keywordSet>")
# Two options for combining keyword sets, because of variation in the return
# from EML::read_eml() (i.e. lists nodes when length > 1, and unlists when
# length = 1).
if (!is.null(names(eml_L0$dataset$keywordSet))) {
eml_L0$dataset$keywordSet <- c(list(eml_L0$dataset$keywordSet),
eml_L1$dataset$keywordSet)
} else {
eml_L0$dataset$keywordSet <- c(eml_L0$dataset$keywordSet,
eml_L1$dataset$keywordSet)
}
# Update <intellectualRights> -----------------------------------------------
# Use parent intellectual rights or CC0 if none exists
if (is.null(eml_L0$dataset$intellectualRights)) {
message(" <intellectualRights>")
eml_L0$dataset$intellectualRights <- eml_L2$dataset$intellectualRights
}
# Update <contact> ----------------------------------------------------------
# Add hymetDP creator to list of contacts
message(" <contact>")
eml_L0$dataset$contact <- c(
list(
list(
individualName = list(
givenName = contact$givenName,
surName = contact$surName),
organizationName = contact$organizationName,
electronicMailAddress = contact$electronicMailAddress)),
list(eml_L0$dataset$contact))
# Update <methods> ----------------------------------------------------------
# Update parent methods with hymetDP creation process and provenance
# metadata to provide the user with a full understanding of how these data
# were created
message(" <methods>")
# Parse components to be reordered and combined for the L1
methods_L1 <- eml_L1$dataset$methods$methodStep
# Get provenance metadata
r <- suppressMessages(
api_get_provenance_metadata(
package.id = source_id,
environment = environment))
xml2::xml_set_attrs(xml2::xml_find_all(r, ".//*[@id]"), c(id = NULL)) # Remove attributes to prevent id clashing and schema invalidation
r <- EML::read_eml(r)
provenance_L1 <- list(
dataSource = r$dataSource,
description = r$description)
# Remove any provenance nodes from the L0 metadata, otherwise they will be
# transferred to the L1 metadata, which would be an inaccurate representation
# of the provenance chain.
method_steps <- xml2::xml_find_all(xml_L0, "./dataset/methods/methodStep")
prov <- unlist(lapply(method_steps, is_prov))
eml_L0$dataset$methods$methodStep <- eml_L0$dataset$methods$methodStep[!prov]
# Combine L1 methods, L0 methods, and L0 provenance
eml_L0$dataset$methods$methodStep <- c(
list(methods_L1),
list(eml_L0$dataset$methods$methodStep),
list(provenance_L1))
# Update <dataTable> --------------------------------------------------------
message(" <dataTable>")
eml_L0$dataset$dataTable <- eml_L1$dataset$dataTable
# Update <otherEntity> ------------------------------------------------------
message(" <otherEntity>")
eml_L0$dataset$otherEntity <- eml_L1$dataset$otherEntity
# Update <annotations> ------------------------------------------------------
message(" <annotations>")
eml_L0$annotations <- eml_L1$annotations
# Write EML -----------------------------------------------------------------
message("</eml>")
message("Writing EML")
emld::eml_version("eml-2.2.0")
EML::write_eml(
eml_L0,
paste0(path, "/", derived_id, ".xml"))
# Validate EML --------------------------------------------------------------
message("Validating EML")
r <- EML::eml_validate(eml_L0)
if (isTRUE(r)) {
message(" Validation passed :)")
} else {
message(" Validation failed :(")
}
message("Done.")
# Return --------------------------------------------------------------------
return(eml_L0)
}
EDIorg/hymetDP documentation built on Nov. 18, 2022, 5:28 p.m.
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Defines functions create_eml
Documented in create_eml
#' Create EML metadata
#'
#' @param path (character) Path to the directory containing hymetDP tables,
#' conversion script, and where EML metadata will be written.
#' @param source_id (character) Identifier of a data package published in a
#' supported repository. Currently, the EDI Data Repository is supported.
#' @param derived_id (character) Identifier of the dataset being created.
#' @param script (character) Name of file used to convert \code{source_id} to
#' \code{derived_id}.
#' @param script_description (character) Description of \code{script}.
#' @param is_about (named character) An optional argument for specifying dataset
#' level annotations describing what this dataset "is about".
#' @param contact (data.frame) Contact information for the person that created
#' this hymetDP dataset, containing these columns: \itemize{ \item givenName
#' \item surName \item organizationName \item electronicMailAddress }
#' @param user_id (character) Identifier of user associated with
#' \code{user_domain}.
#' @param user_domain (character) Domain (data repository) the \code{user_id}
#' belongs to. Currently, EDI is supported.
#' @param url (character) URL to the publicly accessible directory containing
#' hymetDP tables, conversion script, and EML metadata. This argument supports
#' direct download of the data entities by a data repository and is used for
#' automated revisioning and publication.
#'
#' @return An EML metadata file.
#'
#' @details This function creates an EML record for a hymetDP dataset by
#' combining metadata from \code{source_id} with boiler-plate metadata
#' describing the hymetDP model. Changes to the \code{source_id} EML include:
#' \itemize{ \item \strong{`<access>`} Adds \code{user_id} to the list of
#' principals granted read and write access to the hymetDP data package this
#' EML describes. \item \strong{`<title>`} Adds a note that this is a derived
#' data package in the hymetDP format. \item \strong{`<pubDate>`} Adds the
#' date this EML was created. \item \strong{`<abstract>`} Adds a note that
#' this is a derived data package in the hymetDP format. \item
#' \strong{`<keywordSet>`} Adds the "hymetDP" keyword to enable search and
#' discovery of all hymetDP data packages in the data repository it is
#' published. \item \strong{`<intellectualRights>`} Keeps intact the original
#' intellectual rights license \code{source_id} was released under, or uses
#' \href{https://creativecommons.org/publicdomain/zero/1.0/legalcode}{CCO} if
#' missing. \item \strong{`<contact>`} Adds the hymetDP creator as a point of
#' contact. \item \strong{`<methodStep>`} Adds a note that this data package
#' was created by the \code{script}, and adds provenance metadata noting that
#' this is a derived dataset and describes where the \code{source_id} can be
#' accessed. \item \strong{`<dataTables>`} Replaces the \code{source_id} table
#' metadata with descriptions of the the hymetDP tables. \item
#' \strong{`<otherEntity>`} Adds \code{script} and \code{script_description}.
#' otherEntities of \code{source_id} are removed. \item
#' \strong{`<annotations>`} Adds boilerplate annotations describing the
#' hymetDP at the dataset, entity, and entity attribute levels. }
#'
#'
#' @export
#'
#' @examples
#' \dontrun{
#' # Create directory with hymetDP tables for create_eml()
#' mypath <- paste0(tempdir(), "/data")
#' dir.create(mypath)
#' inpts <- c(hymet_L1$tables, path = mypath)
#' do.call(write_tables, inpts)
#' file.copy(system.file("extdata", "create_hymetDP.R", package = "hymetDP"), mypath)
#' dir(mypath)
#'
#' # Add self as contact information incase questions arise
#' additional_contact <- data.frame(
#' givenName = 'Kyle',
#' surName = 'Zollo-Venecek',
#' organizationName = 'Environmental Data Initiative',
#' electronicMailAddress = 'hymetdp@gmail.com',
#' stringsAsFactors = FALSE)
#'
#' # Create EML
#' eml <- create_eml(
#' path = mypath,
#' source_id = "knb-lter-mcm.9003.11",
#' derived_id = "edi.10101.1",
#' is_about = dataset_annotations,
#' script = "create_hymetDP.R",
#' script_description = "A function for converting knb-lter-mcm.9003 to hymetDP",
#' contact = additional_contact,
#' user_id = 'hymetdp',
#' user_domain = 'EDI')
#'
#' dir(mypath)
#' View(eml)
#'
#' # Clean up
#' unlink(mypath, recursive = TRUE)
#' }
#'
create_eml <- function(path,
source_id = NULL,
derived_id,
script,
script_description,
is_about = NULL,
contact,
user_id,
user_domain,
url = NULL) {
message("Creating EML for derived data package (" , derived_id, ")")
# Load Global Environment config --------------------------------------------
if (exists("config.repository", envir = .GlobalEnv)) {
repository <- get("config.repository", envir = .GlobalEnv)
} else {
repository <- "EDI"
}
if (exists("config.environment", envir = .GlobalEnv)) {
environment <- get("config.environment", envir = .GlobalEnv)
} else {
environment <- "production"
}
# Validate inputs -----------------------------------------------------------
validate_arguments(fun.name = "create_eml", fun.args = as.list(environment()))
# Parameterize --------------------------------------------------------------
# Read attributes of hymetDP tables for reference
attr_tbl <- read_criteria()
attr_tbl <- attr_tbl[!is.na(attr_tbl$column), ]
# Get table names for this L1 dataset for use in EAL_make_eml()
data.table <- unlist(
lapply(
unique(attr_tbl$table),
function(x) {
hymetDP_table <- stringr::str_detect(
list.files(path),
paste0("(?<=.{0,10000})", x, "(?=\\.[:alnum:]*$)"))
if (any(hymetDP_table)) {
list.files(path)[hymetDP_table]
}
}))
# Arrange tables in the preferred order to be listed in the EML
fext <- unique(tools::file_ext(data.table))
preferred_order <- c("Variables", "Methods", "Sites", "Sources",
"QualityControlLevels", "Qualifiers", "DataValues", "SeriesCatalog")
use_i <- preferred_order %in% tools::file_path_sans_ext(data.table)
data.table <- paste0(preferred_order[use_i], ".", fext)
# Match table names of this L1 to their boiler plate descriptions for use in
# EAL_make_eml()
descriptions <- data.table::fread(
system.file("extdata", "table_descriptions.txt", package = "hymetDP"))
data.table.description <- descriptions$description[
match(
stringr::str_remove_all(
data.table,
"(\\.[:alnum:]*$)"),
descriptions$table_name)]
# Map scripts and their descriptions to their EAL_make_eml()
# equivalents
if (!is.null(script)) {
other.entity <- script
other.entity.description <- script_description
} else {
other.entity <- NULL
other.entity.description <- NULL
}
# Expand url for each data object of this L1 for use in
# EAL_make_eml()
if (!is.null(url)) {
if (!is.null(data.table)) {
data.table.url <- paste0(url, "/", data.table)
}
if (!is.null(other.entity)) {
other.entity.url <- paste0(url, "/", other.entity)
}
} else {
data.table.url <- NULL
other.entity.url <- NULL
}
# Read L0 EML ---------------------------------------------------------------
message("Reading EML of L0 data package ", source_id)
# Create two objects of the same metadata, eml_L0 (emld list object) for
# editing, and xml_L0 (xml_document) for easy parsing
if (environment == "production") {
url_parent <- paste0(
"https://pasta.lternet.edu/package/metadata/eml/",
stringr::str_replace_all(source_id, "\\.", "/"))
} else if (environment == "staging") {
url_parent <- paste0(
"https://pasta-s.lternet.edu/package/metadata/eml/",
stringr::str_replace_all(source_id, "\\.", "/"))
}
# TODO accesses EDI
eml_L0 <- tryCatch({EML::read_eml(url_parent)},
error = function(e) {
stop("The EDI Repository is down for regular maintenance (Wednesday 01:00",
" - 03:00 UTC). If you have reached this message outside maintenance",
" hours, then there is an unexpected issue that will be resolved ",
"shortly. Our apologies for the inconvenience. Please try again ",
"later.", call. = FALSE)
})
xml_L0 <- suppressMessages(read_eml(source_id))
# Remove L0 elements that should not be inherited by the L1
eml_L0$dataset$dataTable <- NULL
eml_L0$dataset$spatialRaster <- NULL
eml_L0$dataset$spatialVector <- NULL
eml_L0$dataset$storedProcedure <- NULL
eml_L0$dataset$view <- NULL
eml_L0$dataset$otherEntity <- NULL
eml_L0$additionalMetadata <- NULL
# Create L1 EML -------------------------------------------------------------
message("Creating EML of L1 data package ", derived_id)
# This will not be a full EML record, it will only contain sections of the L1
# EML to combined with the L0 EML.
# Create list of inputs to EAL_make_eml()
eal_inputs <- EAL_template_arguments(
path = system.file("extdata", "/hymetDP", package = "hymetDP"),
data.path = path,
data.table = data.table,
other.entity = script)
eal_inputs$path <- system.file("extdata", "/hymetDP", package = "hymetDP")
eal_inputs$data.path <- path
eal_inputs$eml.path <- path
eal_inputs$dataset.title <- "placeholder"
eal_inputs$data.table <- data.table
eal_inputs$data.table.name <- tools::file_path_sans_ext(data.table)
eal_inputs$data.table.description <- data.table.description
eal_inputs$data.table.url <- data.table.url
eal_inputs$data.table.quote.character <- rep('"', length(data.table))
eal_inputs$other.entity <- other.entity
eal_inputs$other.entity.name <- tools::file_path_sans_ext(other.entity)
eal_inputs$other.entity.description <- other.entity.description
eal_inputs$other.entity.url <- other.entity.url
eal_inputs$package.id <- derived_id
eal_inputs$user.id <- user_id
eal_inputs$user.domain <- user_domain
eal_inputs$return.obj <- TRUE
# Remove unused data table attributes templates. All boiler plate attributes*
# files are read in with EAL_template_arguments() above, but
# only the ones being used should be kept and used in
# EAL_make_eml().
all_attribute_templates <- names(eal_inputs$x$template)[
stringr::str_detect(
names(eal_inputs$x$template),
"attributes_")]
expected_attribute_templates <- paste0(
"attributes_",
stringr::str_remove(data.table, "\\.[:alnum:]*$"),
".txt")
unused_attribute_templates <- all_attribute_templates[
!(all_attribute_templates %in% expected_attribute_templates)]
eal_inputs$x$template[
names(eal_inputs$x$template) %in% unused_attribute_templates] <- NULL
# Update attributes_* templates ----------------------------------------------
# Change unit of TimeSupport in Variables attributes
# TODO how to handle multiple units? Impossible?
eal_inputs$x$template$attributes_Variables.txt$content$unit[
eal_inputs$x$template$attributes_Variables.txt$content$attributeName == "TimeSupport"] <- unique(eal_inputs$x$data.table$Variables.csv$content$TimeUnitsName)
# Change <NoDataValue> in DataValues Missing value attributes template with
# the value specified in Variable table column NoDataValue
# TODO how to handle multiple missing values
eal_inputs$x$template$attributes_DataValues.txt$content$missingValueCode[
eal_inputs$x$template$attributes_DataValues.txt$content$missingValueCode == "<NoDataValue>"] <- unique(eal_inputs$x$data.table$Variables.csv$content$NoDataValue)
# Detect date and time format string directly from each table and add to the
# corresponding data table attributes template as required by
# EAL_make_eml().
for (i in expected_attribute_templates) {
date_column <- eal_inputs$x$template[[i]]$content$attributeName[
eal_inputs$x$template[[i]]$content$class == "Date"]
if (length(date_column) != 0) {
data_table <- which(
stringr::str_detect(
names(eal_inputs$x$data.table),
paste0(
"^",
stringr::str_extract(i, "(?<=attributes_).*(?=\\.txt)"),
"\\.[:alnum:]*$")))
for (j in seq(length(date_column))) {
datetime <- eal_inputs$x$data.table[[data_table]]$content[[date_column[[j]]]]
datetime_format <- parse_datetime_frmt_from_vals(datetime)
eal_inputs$x$template[[i]]$content$dateTimeFormatString[
eal_inputs$x$template[[i]]$content$attributeName == date_column[[j]]] <-
datetime_format
}
}
}
# Get table attributes and definitions from EML then create catvars templates for each data table of this dataset
# Add ODM CV terms as cat vars --------------------------------------------
cv_tbls <- subset(attr_tbl, !is.na(attr_tbl$cv))
r <- lapply(
# for each data table
unique(cv_tbls$table),
function(tbl) {
cont <- lapply(
cv_tbls$column[cv_tbls$table == tbl],
function(col) {
univars <- unique(eal_inputs$x$data.table[[paste0(tbl, '.csv')]]$content[[col]])
unidefs <- lapply(
univars,
function(var) {
cv <- cv_tbls$cv[cv_tbls$table == tbl & cv_tbls$column == col]
if (cv == "UnitsCV") {
t <- get(cv)
paste0("Unit: ",
t$UnitsName[t$UnitsName == var],
" (", t$UnitsAbbreviation[t$UnitsName == var], "); UnitType: ",
t$UnitsType[t$UnitsName == var]
)
} else if (cv == "SpatialReferencesCV") {
paste0("Spatial Reference System: ", var)
} else {
t <- get(cv)
t$Definition[t$Term == var]
}
})
catvars_template <- data.frame(
attributeName = col,
code = univars,
definition = unlist(unidefs),
stringsAsFactors = FALSE)
return(list(content = catvars_template))
})
# Manually add in the isRegular code and definition to catvars_Variables
if (tbl == 'Variables') {
cont[[8]] <- list(content = data.frame(
attributeName = "IsRegular",
code = c("TRUE", "FALSE"),
definition = c("Data values are from a regularly sampled time series", "Data values are not from a regularly sampled time series"),
stringsAsFactors = FALSE))
}
return(dplyr::bind_rows(cont))
})
names(r) <- paste0("catvars_", unique(cv_tbls$table), ".txt")
r <- Filter(Negate(is.null), r)
eal_inputs$x$template <- c(eal_inputs$x$template, r)
# The annotations template read in with EAL_template_arguments()
# serves as a map from tables of this L1 to the boilerplate annotations
# which are compiled here.
# TODO everything below involves annotations/variable mapping and should be added back!
annotations_map <- eal_inputs$x$template$annotations.txt$content
annotations <- annotations_map[0, ]
annotations <- rbind(
annotations,
annotations_map[annotations_map$context %in% "eml", ])
if (!is.null(is_about)) {
additional_dataset_annotations <- data.frame(
id = "/dataset",
element = "/dataset",
context = "eml",
subject = "dataset",
predicate_label = "is about",
predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
object_label = names(is_about),
object_uri = unname(is_about),
stringsAsFactors = FALSE)
annotations <- rbind(annotations, additional_dataset_annotations)
}
# TODO i wonder if there is a better object than analysis code. Processing code?
other_entity_annotations <- data.frame(
id = paste0("/", script),
element = "/otherEntity",
context = "dataset",
subject = script,
predicate_label = "is about",
predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
object_label = "analysis code",
object_uri = "http://purl.dataone.org/odo/ECSO_00002489",
stringsAsFactors = FALSE)
annotations <- rbind(annotations, other_entity_annotations)
for (i in data.table) {
table <- stringr::str_remove(i, "\\.[:alpha:]*$")
annotations_subset <- dplyr::filter(
annotations_map,
subject %in% table | context %in% table)
table_annotations <- annotations_subset[
annotations_subset$subject %in%
c(colnames(eal_inputs$x$data.table[[i]]$content), table), ]
table_annotations$id <- stringr::str_replace(
table_annotations$id,
paste0("(?<=/)", table, "(?=$|/)"),
i)
table_annotations$context <- stringr::str_replace(
table_annotations$context, table, i)
table_annotations$subject <- stringr::str_replace(
table_annotations$subject, paste0("^", table, "$"), i)
annotations <- rbind(annotations, table_annotations)
}
# variable_mapping <- stringr::str_subset(
# names(eal_inputs$x$data.table),
# "variable_mapping")
# if (length(variable_mapping) != 0) {
# tblnms_varmap <- eal_inputs$x$data.table[[variable_mapping]]$content$table_name # remove missing tables from variable_mapping
# tblnms_input <- tools::file_path_sans_ext(data.table)
# tbls2keep <- tblnms_varmap %in% tblnms_input
# eal_inputs$x$data.table[[variable_mapping]]$content <- eal_inputs$x$data.table[[variable_mapping]]$content[tbls2keep, ]
# variable_mappings_annotations <- lapply(
# unique(eal_inputs$x$data.table[[variable_mapping]]$content$table_name),
# function(table) {
# variable_mapping_subset <- dplyr::filter(
# eal_inputs$x$data.table[[variable_mapping]]$content,
# table_name == table)
# file_name <- stringr::str_subset(
# names(eal_inputs$x$data.table),
# paste0(table, "\\.[:alpha:]*$"))
#
# if (!is.null(variable_mapping_subset$mapped_label)) { # Handle missing columns
# objlbl <- variable_mapping_subset$mapped_label
# } else {
# objlbl <- ""
# }
# if (!is.null(variable_mapping_subset$mapped_id)) {
# objuri <- variable_mapping_subset$mapped_id
# } else {
# objuri <- ""
# }
#
# annotation <- data.frame(
# id = paste0("/", file_name, "/variable_name"),
# element = "/dataTable/attribute",
# context = file_name,
# subject = "variable_name",
# predicate_label = "is about",
# predicate_uri = "http://purl.obolibrary.org/obo/IAO_0000136",
# object_label = objlbl,
# object_uri = objuri,
# stringsAsFactors = FALSE)
# # Remove duplicate annotations or the variable_name attribute (a column
# # containing multiple variables as apart of a "long" table) will have
# # more than one of the same annotation
# annotation <- dplyr::distinct(
# annotation,
# object_label,
# object_uri,
# .keep_all = TRUE)
# return(annotation)
# })
# annotations <- rbind(
# annotations,
# data.table::rbindlist(variable_mappings_annotations))
# }
annotations[annotations == ""] <- NA_character_
annotations <- annotations[stats::complete.cases(annotations), ]
eal_inputs$x$template$annotations.txt$content <- annotations
# Only include metadata for existing columns (attributes)
for (i in data.table) {
table <- stringr::str_remove(i, "\\.[:alpha:]*$")
tmplt <- paste0("attributes_", table, ".txt")
attrnms <- eal_inputs$x$template[[tmplt]]$content$attributeName
colnms <- colnames(eal_inputs$x$data.table[[i]]$content)
attrs_to_keep <- attrnms %in% colnms
eal_inputs$x$template[[tmplt]]$content <- eal_inputs$x$template[[tmplt]]$content[attrs_to_keep, ]
}
# Call EAL_make_eml()
eml_L1 <- suppressWarnings(
suppressMessages(
do.call(
EAL_make_eml,
eal_inputs[
names(eal_inputs) %in% names(formals(EAL_make_eml))])))
# Update <eml> --------------------------------------------------------------
message("Updating:")
message("<eml>")
eml_L0$schemaLocation <- paste0(
"https://eml.ecoinformatics.org/eml-2.2.0 ",
"https://nis.lternet.edu/schemas/EML/eml-2.2.0/xsd/eml.xsd")
eml_L0$packageId <- derived_id
eml_L0$system <- "edi"
# Update <access> -----------------------------------------------------------
# Access control rules are used by some repositories to manage
# editing, viewing, downloading permissions. Adding the user_id and
# user_domain here expands editing permission to the creator of the DwC-A
# data package this EML will be apart of.
if (length(unlist(eml_L0$access$allow)) == 2) { # prevent single allow issue
eml_L0$access$allow <- list(eml_L0$access$allow,eml_L0$access$allow)
}
eml_L0$access$allow <- unique(
c(eml_L0$access$allow,
eml_L1$access$allow))
# Update <dataset> ----------------------------------------------------------
# For purposes of annotation references, the <dataset> attribute (which may
# have been set by the L0 creator) needs to be set to "dataset", which is
# expected by the L1 dataset annotation.
eml_L0$dataset$id <- "dataset"
# Remove <alternateIdentifier> ----------------------------------------------
# Some repositories assign a DOI to this element. Not removing it here
# an error when uploading to the repository.
message(" <dataset>")
message(" <alternateIdentifier>")
eml_L0$dataset$alternateIdentifier <- NULL
# Update <title> ------------------------------------------------------------
# Add notification the user that this is an hymetDP data package
message(" <title>")
eml_L0$dataset$title <- paste(
eml_L0$dataset$title, "(Reformatted to the hymetDP Design Pattern)")
# Update <pubDate> ----------------------------------------------------------
message(" <pubDate>")
eml_L0$dataset$pubDate <- format(Sys.time(), "%Y-%m-%d")
# Updating <abstract> -------------------------------------------------------
# Add link to L0 data packages and combine L0 and L1 abstracts
eml_L1$dataset$abstract$para[[1]] <- stringr::str_replace(
eml_L1$dataset$abstract$para[[1]],
"L0_PACKAGE_URL",
url_parent)
L1_para <- eml_L1$dataset$abstract$para[[1]]
L0_para <- xml2::xml_text(
xml2::xml_find_all(xml_L0, ".//abstract//para"))
eml_L0$dataset$abstract <- NULL
eml_L0$dataset$abstract$para <- c(
list(L1_para),
list(L0_para))
# Update <keywordSet> -------------------------------------------------------
# Add hymetDP specific keywords to the L0 keywords
message(" <keywordSet>")
# Two options for combining keyword sets, because of variation in the return
# from EML::read_eml() (i.e. lists nodes when length > 1, and unlists when
# length = 1).
if (!is.null(names(eml_L0$dataset$keywordSet))) {
eml_L0$dataset$keywordSet <- c(list(eml_L0$dataset$keywordSet),
eml_L1$dataset$keywordSet)
} else {
eml_L0$dataset$keywordSet <- c(eml_L0$dataset$keywordSet,
eml_L1$dataset$keywordSet)
}
# Update <intellectualRights> -----------------------------------------------
# Use parent intellectual rights or CC0 if none exists
if (is.null(eml_L0$dataset$intellectualRights)) {
message(" <intellectualRights>")
eml_L0$dataset$intellectualRights <- eml_L2$dataset$intellectualRights
}
# Update <contact> ----------------------------------------------------------
# Add hymetDP creator to list of contacts
message(" <contact>")
eml_L0$dataset$contact <- c(
list(
list(
individualName = list(
givenName = contact$givenName,
surName = contact$surName),
organizationName = contact$organizationName,
electronicMailAddress = contact$electronicMailAddress)),
list(eml_L0$dataset$contact))
# Update <methods> ----------------------------------------------------------
# Update parent methods with hymetDP creation process and provenance
# metadata to provide the user with a full understanding of how these data
# were created
message(" <methods>")
# Parse components to be reordered and combined for the L1
methods_L1 <- eml_L1$dataset$methods$methodStep
# Get provenance metadata
r <- suppressMessages(
api_get_provenance_metadata(
package.id = source_id,
environment = environment))
xml2::xml_set_attrs(xml2::xml_find_all(r, ".//*[@id]"), c(id = NULL)) # Remove attributes to prevent id clashing and schema invalidation
r <- EML::read_eml(r)
provenance_L1 <- list(
dataSource = r$dataSource,
description = r$description)
# Remove any provenance nodes from the L0 metadata, otherwise they will be
# transferred to the L1 metadata, which would be an inaccurate representation
# of the provenance chain.
method_steps <- xml2::xml_find_all(xml_L0, "./dataset/methods/methodStep")
prov <- unlist(lapply(method_steps, is_prov))
eml_L0$dataset$methods$methodStep <- eml_L0$dataset$methods$methodStep[!prov]
# Combine L1 methods, L0 methods, and L0 provenance
eml_L0$dataset$methods$methodStep <- c(
list(methods_L1),
list(eml_L0$dataset$methods$methodStep),
list(provenance_L1))
# Update <dataTable> --------------------------------------------------------
message(" <dataTable>")
eml_L0$dataset$dataTable <- eml_L1$dataset$dataTable
# Update <otherEntity> ------------------------------------------------------
message(" <otherEntity>")
eml_L0$dataset$otherEntity <- eml_L1$dataset$otherEntity
# Update <annotations> ------------------------------------------------------
message(" <annotations>")
eml_L0$annotations <- eml_L1$annotations
# Write EML -----------------------------------------------------------------
message("</eml>")
message("Writing EML")
emld::eml_version("eml-2.2.0")
EML::write_eml(
eml_L0,
paste0(path, "/", derived_id, ".xml"))
# Validate EML --------------------------------------------------------------
message("Validating EML")
r <- EML::eml_validate(eml_L0)
if (isTRUE(r)) {
message(" Validation passed :)")
} else {
message(" Validation failed :(")
}
message("Done.")
# Return --------------------------------------------------------------------
return(eml_L0)
}
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