diff --git a/DESCRIPTION b/DESCRIPTION
index 882df32ca..d5dc606ad 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -54,16 +54,21 @@ Imports:
     gridExtra,
     data.table,
     methods,
-    dplyr
+    dplyr,
+    cli,
+    purrr,
+    assertthat
 Suggests:
     lme4,
     httr,
     tibble,
-    testthat,
+    testthat (>= 3.0.0),
     e1071,
     DescTools,
     DSOpal,
     DSMolgenisArmadillo,
-    DSLite
+    DSLite,
+    dsBase
 RoxygenNote: 7.3.2
 Encoding: UTF-8
+Config/testthat/edition: 3
diff --git a/NAMESPACE b/NAMESPACE
index d737d5e6a..59da737b4 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -104,6 +104,7 @@ export(ds.seq)
 export(ds.setSeed)
 export(ds.skewness)
 export(ds.sqrt)
+export(ds.standardiseDf)
 export(ds.summary)
 export(ds.table)
 export(ds.table1D)
@@ -117,6 +118,24 @@ export(ds.var)
 export(ds.vectorCalc)
 import(DSI)
 import(data.table)
+import(dplyr)
+importFrom(DSI,datashield.aggregate)
+importFrom(DSI,datashield.assign)
+importFrom(assertthat,assert_that)
+importFrom(cli,cli_abort)
+importFrom(cli,cli_alert_danger)
+importFrom(cli,cli_alert_info)
+importFrom(cli,cli_alert_success)
+importFrom(cli,cli_alert_warning)
+importFrom(cli,cli_end)
+importFrom(cli,cli_li)
+importFrom(cli,cli_ol)
+importFrom(cli,cli_text)
+importFrom(cli,cli_ul)
+importFrom(purrr,map)
+importFrom(purrr,map_lgl)
+importFrom(purrr,pmap)
+importFrom(purrr,pmap_lgl)
 importFrom(stats,as.formula)
 importFrom(stats,na.omit)
 importFrom(stats,ts)
diff --git a/R/ds.standardiseDf.R b/R/ds.standardiseDf.R
new file mode 100644
index 000000000..daaadbd6a
--- /dev/null
+++ b/R/ds.standardiseDf.R
@@ -0,0 +1,603 @@
+#' Fill DataFrame with Missing Columns and Adjust Classes
+#'
+#' This function fills a given DataFrame by adding missing columns, ensuring consistent column classes, and adjusting factor levels where necessary.
+#' It performs checks to detect class and factor level conflicts and prompts the user for decisions to resolve these conflicts.
+#'
+#' @param df.name Name of the input DataFrame to fill.
+#' @param newobj Name of the new DataFrame object created after filling.
+#' @param fix_class Character, determines behaviour if class of variables is not the same in all
+#' studies. Option "ask" (default) provides the user with a prompt asking if they want to set the
+#' class across all studies, option "no" will throw an error if class conflicts are present.
+#' @param fix_levels Character, determines behaviour if levels of factor variables is not the same
+#' in all studies. Option "ask" (default) provides the user with a prompt asking if they want to set
+#' the levels of factor variables to be the same across all studies, whilst option "no" will throw
+#' an error if factor variables do not have the same class.
+#' @param datasources Data sources from which to aggregate data. Default is `NULL`.
+#' @importFrom assertthat assert_that
+#' @importFrom DSI datashield.aggregate datashield.assign
+#' @return The filled DataFrame with added columns and adjusted classes or factor levels.
+#' @export
+ds.standardiseDf <- function(df.name = NULL, newobj = NULL, fix_class = "ask", fix_levels = "ask",
+                             datasources = NULL) {
+  fill_warnings <- list()
+
+  .check_arguments(df.name, newobj, fix_class, fix_levels)
+
+  if(is.null(datasources)){
+    datasources <- datashield.connections_find()
+  }
+
+  col_names <- datashield.aggregate(datasources, call("colnamesDS", df.name))
+  .stop_if_cols_identical(col_names)
+
+  var_classes <- .get_var_classes(df.name, datasources)
+  class_conflicts <- .identify_class_conflicts(var_classes)
+
+  datashield.assign(datasources, newobj, as.symbol(df.name))
+
+  if (length(class_conflicts) > 0 & fix_class == "no") {
+    DSI::datashield.aggregate(datasources, call("rmDS", newobj))
+    cli_abort("Variables do not have the same class in all studies and `fix_class` is 'no'")
+  } else if (length(class_conflicts) > 0 & fix_class == "ask") {
+    class_decisions <- prompt_user_class_decision_all_vars(
+      names(class_conflicts),
+      var_classes$server,
+      dplyr::select(var_classes, all_of(names(class_conflicts))),
+      newobj,
+      datasources
+    )
+
+    withCallingHandlers({
+      .fix_classes(newobj, names(class_conflicts), class_decisions, newobj, datasources)
+    }, warning = function(w) {
+      fill_warnings <<- c(fill_warnings, conditionMessage(w))  # Append warning to the list
+      invokeRestart("muffleWarning")  # Suppress immediate display of the warning
+    })
+  }
+
+  unique_cols <- .get_unique_cols(col_names)
+  .add_missing_cols_to_df(newobj, unique_cols, newobj, datasources)
+  new_names <- datashield.aggregate(datasources, call("colnamesDS", newobj))
+  added_cols <- .get_added_cols(col_names, new_names)
+
+  new_classes <- .get_var_classes(newobj, datasources)
+  factor_vars <- .identify_factor_vars(new_classes)
+  factor_levels <- .get_factor_levels(newobj, factor_vars, datasources)
+  level_conflicts <- .identify_level_conflicts(factor_levels)
+
+  if (length(level_conflicts) > 0 & fix_levels == "no") {
+    DSI::datashield.aggregate(datasources, call("rmDS", newobj))
+    cli_abort("Factor variables do not have the same levels in all studies and `fix_levels` is 'no'")
+  } else if (length(level_conflicts) > 0 & fix_levels == "ask") {
+    levels_decision <- ask_question_wait_response_levels(level_conflicts, newobj, datasources)
+  }
+
+  if (levels_decision == "1") {
+    unique_levels <- .get_unique_levels(factor_levels, level_conflicts)
+    .set_factor_levels(newobj, unique_levels, datasources)
+  }
+
+  .print_out_messages(added_cols, class_decisions, names(class_conflicts), unique_levels,
+                      level_conflicts, levels_decision, newobj)
+
+  .handle_warnings(fill_warnings)
+  .print_class_warning(class_conflicts, fix_class, class_decisions)
+}
+
+#' Check Function Arguments for Validity
+#'
+#' This function validates the arguments provided to ensure they meet specified conditions.
+#' It checks that the `fix_class` and `fix_levels` arguments are set to accepted values
+#' and that `df.name` and `newobj` are character strings.
+#'
+#' @param df.name A character string representing the name of the data frame.
+#' @param newobj A character string representing the name of the new object to be created.
+#' @param fix_class A character string indicating the method for handling class issues.
+#'   Must be either `"ask"` or `"no"`.
+#' @param fix_levels A character string indicating the method for handling level issues.
+#'   Must be either `"ask"` or `"no"`.
+#' @return NULL. This function is used for validation and does not return a value.
+#' @importFrom assertthat assert_that
+#' @noRd
+.check_arguments <- function(df.name, newobj, fix_class, fix_levels) {
+  assert_that(fix_class %in% c("ask", "no"))
+  assert_that(fix_levels %in% c("ask", "no"))
+  assert_that(is.character(df.name))
+  assert_that(is.character(newobj))
+}
+
+#' Stop If Columns Are Identical
+#'
+#' Checks if the columns in the data frames are identical and throws an error if they are.
+#'
+#' @param col_names A list of column names from different data sources.
+#' @return None. Throws an error if columns are identical.
+#' @importFrom cli cli_abort
+#' @noRd
+.stop_if_cols_identical <- function(col_names) {
+  are_identical <- all(sapply(col_names, identical, col_names[[1]]))
+  if (are_identical) {
+    cli_abort("Columns are identical in all data frames: nothing to fill")
+  }
+}
+
+#' Get Variable Classes from DataFrame
+#'
+#' Retrieves the class of each variable in the specified DataFrame from different data sources.
+#'
+#' @param df.name Name of the input DataFrame.
+#' @param datasources Data sources from which to aggregate data.
+#' @return A DataFrame containing the variable classes from each data source.
+#' @import dplyr
+#' @noRd
+.get_var_classes <- function(df.name, datasources) {
+  cally <- call("getClassAllColsDS", df.name)
+  classes <- datashield.aggregate(datasources, cally) %>%
+    bind_rows(.id = "server")
+  return(classes)
+}
+
+#' Identify Class Conflicts
+#'
+#' Identifies conflicts in variable classes across different data sources.
+#'
+#' @param classes A DataFrame containing variable classes across data sources.
+#' @return A list of variables that have class conflicts.
+#' @import dplyr
+#' @importFrom purrr map
+#' @noRd
+.identify_class_conflicts <- function(classes) {
+  server <- NULL
+  different_class <- classes |>
+    dplyr::select(-server) |>
+    map(~ unique(na.omit(.)))
+
+  out <- different_class[which(different_class %>% map(length) > 1)]
+  return(out)
+}
+
+#' Prompt User for Class Decision for All Variables
+#'
+#' Prompts the user to resolve class conflicts for all variables.
+#'
+#' @param vars A vector of variable names with class conflicts.
+#' @param all_servers The names of all servers.
+#' @param all_classes The classes of the variables across servers.
+#' @return A vector of decisions for each variable's class.
+#' @noRd
+prompt_user_class_decision_all_vars <- function(vars, all_servers, all_classes, newobj, datasources) {
+  decisions <- c()
+  for (i in 1:length(vars)) {
+    decisions[i] <- prompt_user_class_decision(vars[i], all_servers, all_classes[[i]], newobj, datasources)
+  }
+  return(decisions)
+}
+
+#' Prompt User for Class Decision for a Single Variable
+#'
+#' Prompts the user to resolve a class conflict for a single variable.
+#'
+#' @param var The variable name with a class conflict.
+#' @param all_servers The names of all servers.
+#' @param all_classes The classes of the variable across servers.
+#' @importFrom cli cli_alert_warning cli_alert_danger
+#' @return A decision for the variable's class.
+#' @noRd
+prompt_user_class_decision <- function(var, servers, classes, newobj, datasources) {
+  cli_alert_warning("`ds.dataFrameFill` requires that all columns have the same class.")
+  cli_alert_danger("Column {.strong {var}} has following classes:")
+  print_all_classes(servers, classes)
+  cli_text("")
+  return(ask_question_wait_response_class(var, newobj, datasources))
+}
+
+#' Print All Server-Class Pairs
+#'
+#' This function prints out a list of server names along with their corresponding
+#' class types. It formats the output with a bullet-point list using the `cli` package.
+#'
+#' @param all_servers A character vector containing the names of servers.
+#' @param all_classes A character vector containing the class types corresponding
+#' to each server.
+#' @return This function does not return a value. It prints the server-class pairs
+#' to the console as a bulleted list.
+#' @importFrom cli cli_ul cli_li cli_end
+#' @noRd
+print_all_classes <- function(all_servers, all_classes) {
+  combined <- paste(all_servers, all_classes, sep = ": ")
+  cli_ul()
+  for (i in 1:length(combined)) {
+    cli_li("{combined[i]}")
+  }
+  cli_end()
+}
+
+#' Ask Question and Wait for Class Response
+#'
+#' Prompts the user with a question and waits for a response related to class decisions.
+#'
+#' @param question The question to ask the user.
+#' @return The user's decision.
+#' @importFrom cli cli_text cli_alert_warning cli_abort
+#' @noRd
+ask_question_wait_response_class <- function(var, newobj, datasources) {
+  readline <- NULL
+  ask_question_class(var)
+  answer <- readline()
+  if (answer == "6") {
+    DSI::datashield.aggregate(datasources, call("rmDS", newobj))
+    cli_abort("Aborted `ds.dataFrameFill`", .call = NULL)
+  } else if (!answer %in% as.character(1:5)) {
+    cli_text("")
+    cli_alert_warning("Invalid input. Please try again.")
+    cli_text("")
+    ask_question_wait_response_class(var, newobj, datasources)
+  } else {
+    return(answer)
+  }
+}
+
+#' Prompt User for Class Conversion Options
+#'
+#' This function prompts the user with options to convert a variable to a specific class (e.g., factor, integer, numeric, character, or logical).
+#' The function provides a list of class conversion options for the specified variable and includes an option to cancel the operation.
+#'
+#' @param var The name of the variable for which the user is prompted to select a class conversion option.
+#'
+#' @importFrom cli cli_alert_info cli_ol
+#' @return None. This function is used for prompting the user and does not return a value.
+#' @examples
+#' ask_question("variable_name")
+#' @noRd
+ask_question_class <- function(var) {
+  cli_alert_info("Would you like to:")
+  class_options <- c("a factor", "an integer", "numeric", "a character", "a logical vector")
+  class_message <- paste0("Convert `{var}` to ", class_options, " in all studies")
+  cli_ol(
+    c(class_message, "Cancel `ds.dataFrameFill` operation")
+  )
+}
+
+#' Fix Variable Classes
+#'
+#' Applies the user's class decisions to fix the classes of variables across different data sources.
+#'
+#' @param df.name The name of the DataFrame.
+#' @param different_classes A list of variables with class conflicts.
+#' @param class_decisions The decisions made by the user.
+#' @param newobj The name of the new DataFrame.
+#' @param datasources Data sources from which to aggregate data.
+#' @return None. Updates the DataFrame with consistent variable classes.
+#' @noRd
+.fix_classes <- function(df.name, different_classes, class_decisions, newobj, datasources) {
+  cally <- call("fixClassDS", df.name, different_classes, class_decisions)
+  datashield.assign(datasources, newobj, cally)
+}
+
+#' Get Unique Columns from Data Sources
+#'
+#' Retrieves all unique columns from the data sources.
+#'
+#' @param col_names A list of column names.
+#' @return A vector of unique column names.
+#' @noRd
+.get_unique_cols <- function(col_names) {
+  return(
+    unique(
+      unlist(col_names)
+    )
+  )
+}
+
+#' Add Missing Columns to DataFrame
+#'
+#' Adds any missing columns to the DataFrame to ensure all columns are present across data sources.
+#'
+#' @param df.name The name of the DataFrame.
+#' @param unique_cols A vector of unique column names.
+#' @param newobj The name of the new DataFrame.
+#' @param datasources Data sources from which to aggregate data.
+#' @return None. Updates the DataFrame with added columns.
+#' @noRd
+.add_missing_cols_to_df <- function(df.name, cols_to_add_if_missing, newobj, datasources) {
+  cally <- call("fixColsDS", df.name, cols_to_add_if_missing)
+  datashield.assign(datasources, newobj, cally)
+}
+
+#' Get Added Columns
+#'
+#' Compares the old and new column names and identifies newly added columns.
+#'
+#' @param old_names A list of old column names.
+#' @param new_names A list of new column names.
+#' @importFrom purrr pmap
+#' @return A list of added column names.
+#' @noRd
+.get_added_cols <- function(old_names, new_names) {
+  list(old_names, new_names) %>%
+    pmap(function(.x, .y) {
+      .y[!.y %in% .x]
+    })
+}
+
+#' Identify Factor Variables
+#'
+#' Identifies which variables are factors in the DataFrame.
+#'
+#' @param var_classes A DataFrame containing variable classes.
+#' @return A vector of factor variables.
+#' @noRd
+.identify_factor_vars <- function(var_classes) {
+  return(
+    var_classes %>%
+      dplyr::filter(row_number() == 1) %>%
+      dplyr::select(where(~ . == "factor"))
+  )
+}
+
+#' Get Factor Levels from Data Sources
+#'
+#' Retrieves the levels of factor variables from different data sources.
+#'
+#' @param factor_vars A vector of factor variables.
+#' @param newobj The name of the new DataFrame.
+#' @param datasources Data sources from which to aggregate data.
+#' @return A list of factor levels.
+#' @noRd
+.get_factor_levels <- function(df, factor_vars, datasources) {
+  factor_vars <- paste(names(factor_vars), collapse = ",")
+  cally <- call("getAllLevelsDS", df, factor_vars)
+  return(datashield.aggregate(datasources, cally))
+}
+
+#' Identify Factor Level Conflicts
+#'
+#' Identifies conflicts in factor levels across different data sources.
+#'
+#' @param factor_levels A list of factor levels.
+#' @return A list of variables with level conflicts.
+#' @importFrom purrr map_lgl pmap_lgl
+#' @noRd
+.identify_level_conflicts <- function(factor_levels) {
+  levels <- factor_levels %>%
+    pmap_lgl(function(...) {
+      args <- list(...)
+      !all(map_lgl(args[-1], ~ identical(.x, args[[1]])))
+    })
+
+  return(names(levels[levels == TRUE]))
+}
+
+#' Ask Question and Wait for Response on Factor Levels
+#'
+#' Prompts the user with options for resolving factor level conflicts and waits for a response.
+#'
+#' @param level_conflicts A list of variables with factor level conflicts.
+#' @return The user's decision.
+#' @noRd
+ask_question_wait_response_levels <- function(level_conflicts, newobj, datasources) {
+  .make_levels_message(level_conflicts)
+  answer <- readline()
+  if (answer == "3") {
+    DSI::datashield.aggregate(datasources, call("rmDS", newobj))
+    cli_abort("Aborted `ds.dataFrameFill`", .call = NULL)
+  } else if (!answer %in% as.character(1:2)) {
+    cli_alert_warning("Invalid input. Please try again.")
+    cli_alert_info("")
+    .make_levels_message(level_conflicts)
+    return(ask_question_wait_response_levels(level_conflicts, newobj, datasources))
+  } else {
+    return(answer)
+  }
+}
+
+#' Make Factor Level Conflict Message
+#'
+#' Creates a message to alert the user about factor level conflicts and prompt for action.
+#'
+#' @param level_conflicts A list of variables with factor level conflicts.
+#' @importFrom cli cli_alert_warning cli_alert_info cli_ol
+#' @return None. Prints the message to the console.
+#' @noRd
+.make_levels_message <- function(level_conflicts) {
+  cli_alert_warning("Warning: factor variables {level_conflicts} do not have the same levels in all studies")
+  cli_alert_info("Would you like to:")
+  cli_ol(c("Create the missing levels where they are not present", "Do nothing", "Cancel `ds.dataFrameFill` operation"))
+}
+
+#' Get Unique Factor Levels
+#'
+#' Retrieves the unique factor levels for variables with conflicts.
+#'
+#' @param factor_levels A list of factor levels.
+#' @param level_conflicts A list of variables with level conflicts.
+#' @importFrom purrr pmap
+#' @return A list of unique factor levels.
+#' @noRd
+.get_unique_levels <- function(factor_levels, level_conflicts) {
+  unique_levels <- factor_levels %>%
+    map(~ .[level_conflicts]) %>%
+    pmap(function(...) {
+      as.character(c(...))
+    }) %>%
+    map(~ unique(.))
+  return(unique_levels)
+}
+
+#' Set Factor Levels in DataFrame
+#'
+#' Applies the unique factor levels to the DataFrame.
+#'
+#' @param newobj The name of the new DataFrame.
+#' @param unique_levels A list of unique factor levels.
+#' @param datasources Data sources from which to aggregate data.
+#' @return None. Updates the DataFrame with the new factor levels.
+#' @noRd
+.set_factor_levels <- function(df, unique_levels, datasources) {
+  cally <- call("fixLevelsDS", df, names(unique_levels), unique_levels)
+  datashield.assign(datasources, df, cally)
+}
+
+#' Print Out Summary Messages
+#'
+#' Prints summary messages regarding the filled DataFrame, including added columns, class decisions, and factor level adjustments.
+#'
+#' @param added_cols A list of added columns.
+#' @param class_decisions A vector of class decisions.
+#' @param different_classes A list of variables with class conflicts.
+#' @param unique_levels A list of unique factor levels.
+#' @param level_conflicts A list of variables with level conflicts.
+#' @param levels_decision The decision made regarding factor levels.
+#' @param newobj The name of the new DataFrame.
+#' @importFrom cli cli_text
+#' @return None. Prints messages to the console.
+#' @noRd
+.print_out_messages <- function(added_cols, class_decisions, different_classes, unique_levels,
+                                level_conflicts, levels_decision, newobj) {
+  .print_var_recode_message(added_cols, newobj)
+
+  if (length(different_classes) > 0) {
+    .print_class_recode_message(class_decisions, different_classes, newobj)
+    cli_text("")
+  }
+
+  if (length(level_conflicts) > 0 & levels_decision == "1") {
+    .print_levels_recode_message(unique_levels, newobj)
+  }
+}
+
+#' Print Variable Recode Message
+#'
+#' Prints a message summarizing the columns that were added to the DataFrame.
+#'
+#' @param added_cols A list of added columns.
+#' @param newobj The name of the new DataFrame.
+#' @importFrom cli cli_text
+#' @return None. Prints the message to the console.
+#' @noRd
+.print_var_recode_message <- function(added_cols, newobj) {
+  cli_alert_success("The following variables have been added to {newobj}:")
+  added_cols_neat <- added_cols %>% map(~ ifelse(length(.) == 0, "", .))
+  var_message <- paste0(names(added_cols), " --> ", added_cols_neat)
+  for (i in 1:length(var_message)) {
+    cli_alert_info("{var_message[[i]]}")
+  }
+  cli_text("")
+}
+
+#' Print Class Recode Message
+#'
+#' Prints a message summarizing the class decisions that were made for variables with conflicts.
+#'
+#' @param class_decisions A vector of class decisions.
+#' @param different_classes A list of variables with class conflicts.
+#' @param newobj The name of the new DataFrame.
+#' @importFrom cli cli_alert_info cli_alert_success
+#' @return None. Prints the message to the console.
+#' @noRd
+.print_class_recode_message <- function(class_decisions, different_classes, newobj) {
+  choice_neat <- .change_choice_to_string(class_decisions)
+  class_message <- paste0(different_classes, " --> ", choice_neat)
+  cli_alert_success("The following classes have been set for all datasources in {newobj}: ")
+  for (i in 1:length(class_message)) {
+    cli_alert_info("{class_message[[i]]}")
+  }
+}
+
+#' Convert Class Decision Code to String
+#'
+#' This function converts a numeric class decision input (represented as a string)
+#' into the corresponding class type string (e.g., "factor", "integer", "numeric", etc.).
+#' @param class_decision A string representing the class decision. It should be
+#' one of the following values: "1", "2", "3", "4", or "5".
+#' @return A string representing the class type corresponding to the input:
+#' "factor", "integer", "numeric", "character", or "logical".
+#' @noRd
+.change_choice_to_string <- function(class_decision) {
+  case_when(
+    class_decision == "1" ~ "factor",
+    class_decision == "2" ~ "integer",
+    class_decision == "3" ~ "numeric",
+    class_decision == "4" ~ "character",
+    class_decision == "5" ~ "logical"
+  )
+}
+
+#' Print Factor Levels Recode Message
+#'
+#' Prints a message summarizing the factor level decisions that were made for variables with conflicts.
+#'
+#' @param unique_levels A list of unique factor levels.
+#' @param newobj The name of the new DataFrame.
+#' @importFrom cli cli_alert_success cli_alert_info
+#' @return None. Prints the message to the console.
+#' @noRd
+.print_levels_recode_message <- function(unique_levels, newobj) {
+  levels_message <- .make_levels_recode_message(unique_levels)
+  cli_alert_success("The following levels have been set for all datasources in {newobj}: ")
+  for (i in 1:length(levels_message)) {
+    cli_alert_info("{levels_message[[i]]}")
+  }
+}
+
+#' Make Levels Recode Message
+#'
+#' Creates a message to alert the user about factor level recoding.
+#'
+#' @param unique_levels A list of unique factor levels.
+#' @return A formatted string summarizing the level recoding.
+#' @importFrom purrr pmap
+#' @noRd
+.make_levels_recode_message <- function(unique_levels) {
+  return(
+    list(names(unique_levels), unique_levels) %>%
+      pmap(function(.x, .y) {
+        paste0(.x, " --> ", paste0(.y, collapse = ", "))
+      })
+  )
+}
+
+#' Handle Warnings for Class Conversion Issues
+#'
+#' This function iterates through a list of warnings generated during class conversion and
+#' triggers a danger alert if any warnings indicate that the conversion has resulted in `NA` values.
+#'
+#' @param fill_warnings A list or vector of warning messages generated during class conversion.
+#'   If any warnings indicate that `NA` values were introduced, a danger alert will be displayed.
+#' @return NULL. This function is used for its side effects of printing alerts.
+#' @importFrom cli cli_alert_danger
+#' @noRd
+.handle_warnings <- function(fill_warnings) {
+  if (length(fill_warnings) > 0) {
+    for (i in seq_along(fill_warnings)) {
+      if (grepl("NAs introduced by coercion", fill_warnings[[i]])) {
+        cli_alert_danger("Class conversion resulted in the creation of NA values.")
+      } else {
+        cli_alert_danger(fill_warnings[[i]])
+      }
+    }
+  }
+}
+
+#' Print Warning for Class Conflicts in Data Conversion
+#'
+#' This function displays a warning when there are class conflicts in a dataset that may have resulted
+#' from incompatible class changes during data conversion. It alerts users to verify column classes,
+#' as incompatible changes could corrupt the data.
+#'
+#' @param class_conflicts A list or vector of conflicting classes identified during conversion.
+#' @param fix_class A string indicating the user's choice for fixing class conflicts. Typically,
+#'   this is "ask" if the user is prompted to confirm class changes.
+#' @param class_decisions A vector of decisions made for class conversions. When any value is not
+#'   "6", it indicates unresolved class conflicts.
+#' @return NULL. This function is used for its side effects of printing alerts.
+#' @importFrom cli cli_alert_warning
+#' @noRd
+.print_class_warning <- function(class_conflicts, fix_class, class_decisions) {
+  if(length(class_conflicts) > 0 & fix_class == "ask" & all(!class_decisions == "6")) {
+    cli_alert_warning("Please check all columns that have changed class. Not all class changes
+    are compatible with all data types, so this could have corrupted the data.")
+  }
+}
+
+readline <- NULL
diff --git a/man/ds.standardiseDf.Rd b/man/ds.standardiseDf.Rd
new file mode 100644
index 000000000..4f544f1d8
--- /dev/null
+++ b/man/ds.standardiseDf.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/ds.standardiseDf.R
+\name{ds.standardiseDf}
+\alias{ds.standardiseDf}
+\title{Fill DataFrame with Missing Columns and Adjust Classes}
+\usage{
+ds.standardiseDf(
+  df.name = NULL,
+  newobj = NULL,
+  fix_class = "ask",
+  fix_levels = "ask",
+  datasources = NULL
+)
+}
+\arguments{
+\item{df.name}{Name of the input DataFrame to fill.}
+
+\item{newobj}{Name of the new DataFrame object created after filling.}
+
+\item{fix_class}{Character, determines behaviour if class of variables is not the same in all
+studies. Option "ask" (default) provides the user with a prompt asking if they want to set the
+class across all studies, option "no" will throw an error if class conflicts are present.}
+
+\item{fix_levels}{Character, determines behaviour if levels of factor variables is not the same
+in all studies. Option "ask" (default) provides the user with a prompt asking if they want to set
+the levels of factor variables to be the same across all studies, whilst option "no" will throw
+an error if factor variables do not have the same class.}
+
+\item{datasources}{Data sources from which to aggregate data. Default is `NULL`.}
+}
+\value{
+The filled DataFrame with added columns and adjusted classes or factor levels.
+}
+\description{
+This function fills a given DataFrame by adding missing columns, ensuring consistent column classes, and adjusting factor levels where necessary.
+It performs checks to detect class and factor level conflicts and prompts the user for decisions to resolve these conflicts.
+}
diff --git a/tests/testthat/_snaps/smk-standardiseDf.md b/tests/testthat/_snaps/smk-standardiseDf.md
new file mode 100644
index 000000000..4fa52ecac
--- /dev/null
+++ b/tests/testthat/_snaps/smk-standardiseDf.md
@@ -0,0 +1,86 @@
+# ask_question displays the correct prompt
+
+    Code
+      ask_question_class("my_var")
+    Message
+      i Would you like to:
+      1. Convert `my_var` to a factor in all studies
+      2. Convert `my_var` to an integer in all studies
+      3. Convert `my_var` to numeric in all studies
+      4. Convert `my_var` to a character in all studies
+      5. Convert `my_var` to a logical vector in all studies
+      6. Cancel `ds.dataFrameFill` operation
+
+# print_all_classes prints the correct message
+
+    Code
+      print_all_classes(c("server_1", "server_2", "server_3"), c("numeric", "factor",
+        "integer"))
+    Message
+      * server_1: numeric
+      * server_2: factor
+      * server_3: integer
+
+# .make_levels_message makes correct message
+
+    Code
+      .make_levels_message(level_conflicts)
+    Message
+      ! Warning: factor variables fac_col2, fac_col3, fac_col6, and fac_col9 do not have the same levels in all studies
+      i Would you like to:
+      1. Create the missing levels where they are not present
+      2. Do nothing
+      3. Cancel `ds.dataFrameFill` operation
+
+# .print_var_recode_message prints the correct message
+
+    Code
+      .print_var_recode_message(added_cols, "test_df")
+    Message
+      v The following variables have been added to test_df:
+      i sim1 --> col11
+      i sim2 --> col11
+      i sim3 --> col12
+      
+
+# .print_class_recode_message prints the correct message
+
+    Code
+      .print_class_recode_message(class_decisions, different_classes, "test_df")
+    Message
+      v The following classes have been set for all datasources in test_df: 
+      i fac_col4 --> factor
+      i fac_col5 --> logical
+
+# .print_levels_recode_message prints the correct message
+
+    Code
+      .print_levels_recode_message(unique_levs, "test_df")
+    Message
+      v The following levels have been set for all datasources in test_df: 
+      i fac_col2 --> Blue, Green, Red
+      i fac_col3 --> No, Yes
+      i fac_col6 --> Bird, Cat, Dog
+      i fac_col9 --> False, True
+
+# .print_out_messages prints the correct messages
+
+    Code
+      .print_out_messages(added_cols, class_decisions, different_classes, unique_levs,
+        level_conflicts, "1", "test_df")
+    Message
+      v The following variables have been added to test_df:
+      i sim1 --> col11
+      i sim2 --> col11
+      i sim3 --> col12
+      
+      v The following classes have been set for all datasources in test_df: 
+      i fac_col4 --> factor
+      i fac_col5 --> logical
+      
+      v The following levels have been set for all datasources in test_df: 
+      i fac_col2 --> Blue, Green, Red
+      i fac_col3 --> No, Yes
+      i fac_col6 --> Bird, Cat, Dog
+      i fac_col9 --> False, True
+
diff --git a/tests/testthat/connection_to_datasets/init_studies_datasets.R b/tests/testthat/connection_to_datasets/init_studies_datasets.R
index 0639aac61..b95ed48a1 100644
--- a/tests/testthat/connection_to_datasets/init_studies_datasets.R
+++ b/tests/testthat/connection_to_datasets/init_studies_datasets.R
@@ -1,85 +1,85 @@
 init.studies.dataset.cnsim <- function(variables)
 {
-    if (ds.test_env$secure_login_details)
+  if (ds.test_env$secure_login_details)
+  {
+    if (ds.test_env$driver == "OpalDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "CNSIM.CNSIM1", options=ds.test_env$options_1)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "CNSIM.CNSIM2", options=ds.test_env$options_2)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "CNSIM.CNSIM3", options=ds.test_env$options_3)
+      ds.test_env$login.data <- builder$build()
+    }
+    else if (ds.test_env$driver == "ArmadilloDriver")
     {
-      if (ds.test_env$driver == "OpalDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "CNSIM.CNSIM1", options=ds.test_env$options_1)
-        builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "CNSIM.CNSIM2", options=ds.test_env$options_2)
-        builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "CNSIM.CNSIM3", options=ds.test_env$options_3)
-        ds.test_env$login.data <- builder$build()
-      }
-      else if (ds.test_env$driver == "ArmadilloDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/cnsim/CNSIM1", driver = ds.test_env$driver)
-        builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/cnsim/CNSIM2", driver = ds.test_env$driver)
-        builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/cnsim/CNSIM3", driver = ds.test_env$driver)
-        ds.test_env$login.data <- builder$build()
-      }
-      else 
-      {
-         ds.test_env$login.data <- DSLite::setupCNSIMTest("dsBase", env = ds.test_env)
-      }
-      ds.test_env$stats.var <- variables
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/cnsim/CNSIM1", driver = ds.test_env$driver)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/cnsim/CNSIM2", driver = ds.test_env$driver)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/cnsim/CNSIM3", driver = ds.test_env$driver)
+      ds.test_env$login.data <- builder$build()
     }
+    else
+    {
+      ds.test_env$login.data <- DSLite::setupCNSIMTest("dsBase", env = ds.test_env)
+    }
+    ds.test_env$stats.var <- variables
+  }
 }
 
 init.studies.dataset.dasim <- function(variables)
 {
-    if (ds.test_env$secure_login_details)
+  if (ds.test_env$secure_login_details)
+  {
+    if (ds.test_env$driver == "OpalDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "DASIM.DASIM1", options=ds.test_env$options_1)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "DASIM.DASIM2", options=ds.test_env$options_2)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "DASIM.DASIM3", options=ds.test_env$options_3)
+      ds.test_env$login.data <- builder$build()
+    }
+    else if (ds.test_env$driver == "ArmadilloDriver")
     {
-      if (ds.test_env$driver == "OpalDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "DASIM.DASIM1", options=ds.test_env$options_1)
-        builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "DASIM.DASIM2", options=ds.test_env$options_2)
-        builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "DASIM.DASIM3", options=ds.test_env$options_3)
-        ds.test_env$login.data <- builder$build()
-      }
-      else if (ds.test_env$driver == "ArmadilloDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/dasim/DASIM1", driver = ds.test_env$driver)
-        builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/dasim/DASIM2", driver = ds.test_env$driver)
-        builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/dasim/DASIM3", driver = ds.test_env$driver)
-        ds.test_env$login.data <- builder$build()
-      }
-      else 
-      {
-        ds.test_env$login.data <- DSLite::setupDASIMTest("dsBase", env = ds.test_env)
-      }
-      ds.test_env$stats.var <- variables
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/dasim/DASIM1", driver = ds.test_env$driver)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/dasim/DASIM2", driver = ds.test_env$driver)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/dasim/DASIM3", driver = ds.test_env$driver)
+      ds.test_env$login.data <- builder$build()
     }
+    else
+    {
+      ds.test_env$login.data <- DSLite::setupDASIMTest("dsBase", env = ds.test_env)
+    }
+    ds.test_env$stats.var <- variables
+  }
 }
 
 init.studies.dataset.survival <- function(variables)
 {
-    if (ds.test_env$secure_login_details)
+  if (ds.test_env$secure_login_details)
+  {
+    if (ds.test_env$driver == "OpalDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "survival1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "SURVIVAL.EXPAND_WITH_MISSING1", options=ds.test_env$options_1)
+      builder$append(server = "survival2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "SURVIVAL.EXPAND_WITH_MISSING2", options=ds.test_env$options_2)
+      builder$append(server = "survival3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "SURVIVAL.EXPAND_WITH_MISSING3", options=ds.test_env$options_3)
+      ds.test_env$login.data <- builder$build()
+    }
+    else if (ds.test_env$driver == "ArmadilloDriver")
     {
-      if (ds.test_env$driver == "OpalDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "survival1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "SURVIVAL.EXPAND_WITH_MISSING1", options=ds.test_env$options_1)
-        builder$append(server = "survival2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "SURVIVAL.EXPAND_WITH_MISSING2", options=ds.test_env$options_2)
-        builder$append(server = "survival3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "SURVIVAL.EXPAND_WITH_MISSING3", options=ds.test_env$options_3)
-        ds.test_env$login.data <- builder$build()
-      }
-      else if (ds.test_env$driver == "ArmadilloDriver")
-      {
-        builder <- DSI::newDSLoginBuilder(.silent = TRUE)
-        builder$append(server = "survival1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/survival/EXPAND_WITH_MISSING1", driver = ds.test_env$driver)
-        builder$append(server = "survival2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/survival/EXPAND_WITH_MISSING2", driver = ds.test_env$driver)
-        builder$append(server = "survival3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/survival/EXPAND_WITH_MISSING3", driver = ds.test_env$driver)
-        ds.test_env$login.data <- builder$build()
-      }
-      else 
-      {
-        ds.test_env$login.data <- DSLite::setupSURVIVALTest("dsBase", env = ds.test_env)
-      }
-      ds.test_env$stats.var <- variables
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "survival1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/survival/EXPAND_WITH_MISSING1", driver = ds.test_env$driver)
+      builder$append(server = "survival2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/survival/EXPAND_WITH_MISSING2", driver = ds.test_env$driver)
+      builder$append(server = "survival3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/survival/EXPAND_WITH_MISSING3", driver = ds.test_env$driver)
+      ds.test_env$login.data <- builder$build()
     }
+    else
+    {
+      ds.test_env$login.data <- DSLite::setupSURVIVALTest("dsBase", env = ds.test_env)
+    }
+    ds.test_env$stats.var <- variables
+  }
 }
 
 init.studies.dataset.cluster.int <- function(variables)
@@ -107,7 +107,7 @@ init.studies.dataset.cluster.int <- function(variables)
       builder$append(server = "cluster.int3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/cluster/CLUSTER_INT3", driver = ds.test_env$driver)
       ds.test_env$login.data <- builder$build()
     }
-    else 
+    else
     {
       #to do
       #ds.test_env$login.data <- DSLite::setupCLUSTERTest("dsBase", env = ds.test_env)
@@ -141,7 +141,7 @@ init.studies.dataset.cluster.slo <- function(variables)
       builder$append(server = "cluster.slo3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/cluster/CLUSTER_SLO3", driver = ds.test_env$driver)
       ds.test_env$login.data <- builder$build()
     }
-    else 
+    else
     {
       #to do
       #ds.test_env$login.data <- DSLite::setupCLUSTERTest("dsBase", env = ds.test_env)
@@ -176,7 +176,7 @@ init.studies.dataset.anthro <- function(variables)
       builder$append(server = "study3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/anthro/anthro3", driver = ds.test_env$driver)
       ds.test_env$login.data <- builder$build()
     }
-    else 
+    else
     {
       #to do
       #ds.test_env$login.data <- DSLite::setupCLUSTERTest("dsBase", env = ds.test_env)
@@ -211,39 +211,95 @@ init.studies.dataset.gamlss <- function(variables)
       builder$append(server = "study3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/gamlss/gamlss3", driver = ds.test_env$driver)
       ds.test_env$login.data <- builder$build()
     }
-    else 
+    else
     {
       #to do
       #ds.test_env$login.data <- DSLite::setupCLUSTERTest("dsBase", env = ds.test_env)
     }
     ds.test_env$stats.var <- variables
-    
+
+  }
+}
+
+init.studies.dataset.stand <- function(variables)
+{
+  if (ds.test_env$secure_login_details)
+  {
+    if (ds.test_env$driver == "OpalDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "STANDARDISE.std_1", options=ds.test_env$options_1)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "STANDARDISE.std_1", options=ds.test_env$options_2)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "STANDARDISE.std_1", options=ds.test_env$options_3)
+      ds.test_env$login.data <- builder$build()
+    }
+    else if (ds.test_env$driver == "ArmadilloDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/standardise/std_1", driver = ds.test_env$driver)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/standardise/std_2", driver = ds.test_env$driver)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/standardise/std_3", driver = ds.test_env$driver)
+      ds.test_env$login.data <- builder$build()
+    }
+    else
+    {
+      ds.test_env$login.data <- DSLite::setupCNSIMTest("dsBase", env = ds.test_env)
+    }
+    ds.test_env$stats.var <- variables
+  }
+}
+
+init.studies.dataset.stand_disclosure <- function(variables)
+{
+  if (ds.test_env$secure_login_details)
+  {
+    if (ds.test_env$driver == "OpalDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "STANDARDISE.std_1_d", options=ds.test_env$options_1)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "STANDARDISE.std_2_d", options=ds.test_env$options_2)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "STANDARDISE.std_3_d", options=ds.test_env$options_3)
+      ds.test_env$login.data <- builder$build()
+    }
+    else if (ds.test_env$driver == "ArmadilloDriver")
+    {
+      builder <- DSI::newDSLoginBuilder(.silent = TRUE)
+      builder$append(server = "sim1", url = ds.test_env$ip_address_1, user = ds.test_env$user_1, password = ds.test_env$password_1, table = "datashield/standardise/std_1_d", driver = ds.test_env$driver)
+      builder$append(server = "sim2", url = ds.test_env$ip_address_2, user = ds.test_env$user_2, password = ds.test_env$password_2, table = "datashield/standardise/std_2_d", driver = ds.test_env$driver)
+      builder$append(server = "sim3", url = ds.test_env$ip_address_3, user = ds.test_env$user_3, password = ds.test_env$password_3, table = "datashield/standardise/std_3_d", driver = ds.test_env$driver)
+      ds.test_env$login.data <- builder$build()
+    }
+    else
+    {
+      ds.test_env$login.data <- DSLite::setupCNSIMTest("dsBase", env = ds.test_env)
+    }
+    ds.test_env$stats.var <- variables
   }
 }
 
 
 connect.studies.dataset.cnsim <- function(variables)
 {
-    log.out.data.server()
-    source("connection_to_datasets/login_details.R")
-    init.studies.dataset.cnsim(variables)
-    log.in.data.server()
+  log.out.data.server()
+  source("connection_to_datasets/login_details.R")
+  init.studies.dataset.cnsim(variables)
+  log.in.data.server()
 }
 
 connect.studies.dataset.dasim <- function(variables)
 {
-    log.out.data.server()
-    source("connection_to_datasets/login_details.R")
-    init.studies.dataset.dasim(variables)
-    log.in.data.server()
+  log.out.data.server()
+  source("connection_to_datasets/login_details.R")
+  init.studies.dataset.dasim(variables)
+  log.in.data.server()
 }
 
 connect.studies.dataset.survival <- function(variables)
 {
-    log.out.data.server()
-    source("connection_to_datasets/login_details.R")
-    init.studies.dataset.survival(variables)
-    log.in.data.server()
+  log.out.data.server()
+  source("connection_to_datasets/login_details.R")
+  init.studies.dataset.survival(variables)
+  log.in.data.server()
 }
 
 connect.studies.dataset.cluster.int <- function(variables)
@@ -278,19 +334,35 @@ connect.studies.dataset.gamlss <- function(variables)
   log.in.data.server()
 }
 
+connect.studies.dataset.stand <- function(variables)
+{
+  log.out.data.server()
+  source("connection_to_datasets/login_details.R")
+  init.studies.dataset.stand(variables)
+  log.in.data.server()
+}
+
+connect.studies.dataset.stand_disclosure <- function(variables)
+{
+  log.out.data.server()
+  source("connection_to_datasets/login_details.R")
+  init.studies.dataset.stand_disclosure(variables)
+  log.in.data.server()
+}
+
 disconnect.studies.dataset.cnsim <- function()
 {
-    log.out.data.server()
+  log.out.data.server()
 }
 
 disconnect.studies.dataset.dasim <- function()
 {
-    log.out.data.server()
+  log.out.data.server()
 }
 
 disconnect.studies.dataset.survival <- function()
 {
-    log.out.data.server()
+  log.out.data.server()
 }
 
 disconnect.studies.dataset.cluster.int <- function()
@@ -312,3 +384,8 @@ disconnect.studies.dataset.gamlss <- function()
 {
   log.out.data.server()
 }
+
+disconnect.studies.dataset.stand <- function()
+{
+  log.out.data.server()
+}
diff --git a/tests/testthat/data_files/STANDARDISE/std_1.csv b/tests/testthat/data_files/STANDARDISE/std_1.csv
new file mode 100644
index 000000000..328909592
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_1.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,fac_col6,fac_col9,col12,col15,col18
+High,Blue,Yes,3,NA,Bird,True,28.757752012461424,31,TRUE
+High,Blue,Yes,3,NA,Bird,True,78.83051354438066,79,TRUE
+High,Blue,Yes,3,NA,Bird,True,40.89769218116999,51,TRUE
+Medium,Green,No,2,NA,Dog,False,88.301740400493145,14,FALSE
+High,Blue,Yes,3,NA,Bird,True,94.04672842938453,67,TRUE
+Medium,Green,No,2,NA,Dog,False,4.555649938993156,42,FALSE
+Medium,Green,No,2,NA,Dog,False,52.810548804700375,50,FALSE
+Medium,Green,No,2,NA,Dog,False,89.2419044394046,43,FALSE
+High,Blue,Yes,3,NA,Bird,True,55.14350144658238,14,TRUE
+Low,NA,Yes,1,NA,Cat,True,45.661473530344665,25,TRUE
+Medium,Green,No,2,NA,Dog,False,95.68333453498781,90,FALSE
+Medium,Green,No,2,NA,Dog,False,45.33341561909765,91,FALSE
+Low,NA,No,1,NA,Cat,False,67.75706354528666,69,FALSE
+Medium,Green,Yes,2,NA,Dog,True,57.26334019564092,91,TRUE
+High,Blue,No,3,NA,Bird,False,10.292468266561627,57,FALSE
+Low,NA,Yes,1,NA,Cat,True,89.98249704018235,92,TRUE
+High,Blue,No,3,NA,Bird,False,24.60877343546599,9,FALSE
+High,Blue,Yes,3,NA,Bird,True,4.205953353084624,93,TRUE
+Low,NA,Yes,1,NA,Cat,True,32.79207192827016,99,TRUE
+Low,NA,Yes,1,NA,Cat,True,95.45036491472274,72,TRUE
+Low,NA,Yes,1,NA,Cat,True,88.95393160637468,26,TRUE
+Low,NA,No,1,NA,Cat,False,69.28034061565995,7,FALSE
+High,Blue,Yes,3,NA,Bird,True,64.05068137682974,42,TRUE
+Medium,Green,Yes,2,NA,Dog,True,99.42697766236961,9,TRUE
+High,Blue,Yes,3,NA,Bird,True,65.57057991158217,83,TRUE
+Medium,Green,Yes,2,NA,Dog,True,70.85304681677371,36,TRUE
+Low,NA,No,1,NA,Cat,False,54.40660247113556,78,FALSE
+Medium,Green,No,2,NA,Dog,False,59.41420204471797,81,FALSE
+High,Blue,Yes,3,NA,Bird,True,28.91597372945398,43,TRUE
+Medium,Green,No,2,NA,Dog,False,14.711364731192589,76,FALSE
+Low,NA,Yes,1,NA,Cat,True,96.30242325365543,15,TRUE
+High,Blue,No,3,NA,Bird,False,90.22990451194346,32,FALSE
+High,Blue,Yes,3,NA,Bird,True,69.07052784226835,7,TRUE
+Low,NA,No,1,NA,Cat,False,79.54674176871777,9,FALSE
+High,Blue,No,3,NA,Bird,False,2.461368450894952,41,FALSE
+Medium,Green,Yes,2,NA,Dog,True,47.77959710918367,74,TRUE
+Low,NA,Yes,1,NA,Cat,True,75.84595375228673,23,TRUE
+High,Blue,Yes,3,NA,Bird,True,21.640793583355844,27,TRUE
+Low,NA,Yes,1,NA,Cat,True,31.818100763484836,60,TRUE
+Low,NA,No,1,NA,Cat,False,23.16257853526622,53,FALSE
+Medium,Green,Yes,2,NA,Dog,True,14.280002238228917,7,TRUE
+High,Blue,No,3,NA,Bird,False,41.45463358145207,53,FALSE
+High,Blue,No,3,NA,Bird,False,41.372432629577816,27,FALSE
+Low,NA,Yes,1,NA,Cat,True,36.884545092470944,96,TRUE
+High,Blue,Yes,3,NA,Bird,True,15.244474774226546,38,TRUE
+Low,NA,Yes,1,NA,Cat,True,13.880606344901025,89,TRUE
+High,Blue,Yes,3,NA,Bird,True,23.303409945219755,34,TRUE
+Medium,Green,No,2,NA,Dog,False,46.59624502528459,93,FALSE
+Low,NA,Yes,1,NA,Cat,True,26.597264036536217,69,TRUE
+Medium,Green,Yes,2,NA,Dog,True,85.78277153428644,72,TRUE
+Low,NA,No,1,NA,Cat,False,4.583116667345166,76,FALSE
+Low,NA,Yes,1,NA,Cat,True,44.220007420517504,63,TRUE
+High,Blue,Yes,3,NA,Bird,True,79.89248456433415,13,TRUE
+Low,NA,Yes,1,NA,Cat,True,12.189925997518003,82,TRUE
+Medium,Green,Yes,2,NA,Dog,True,56.094798375852406,97,TRUE
+Low,NA,No,1,NA,Cat,False,20.65313896164298,91,FALSE
+Low,NA,No,1,NA,Cat,False,12.753165024332702,25,FALSE
+High,Blue,Yes,3,NA,Bird,True,75.33078643027693,38,TRUE
+Low,NA,No,1,NA,Cat,False,89.50453591533005,21,FALSE
+Medium,Green,Yes,2,NA,Dog,True,37.44627758860588,79,TRUE
+Low,NA,Yes,1,NA,Cat,True,66.51151946280152,41,TRUE
+High,Blue,No,3,NA,Bird,False,9.484066092409194,47,FALSE
+Low,NA,No,1,NA,Cat,False,38.39696377981454,90,FALSE
+High,Blue,Yes,3,NA,Bird,True,27.43836445733905,60,TRUE
+Medium,Green,Yes,2,NA,Dog,True,81.46400388795882,95,TRUE
+High,Blue,No,3,NA,Bird,False,44.851634139195085,16,FALSE
+Medium,Green,Yes,2,NA,Dog,True,81.00643530488014,94,TRUE
+Medium,Green,Yes,2,NA,Dog,True,81.23895095195621,6,TRUE
+High,Blue,Yes,3,NA,Bird,True,79.43423211108893,72,TRUE
+Medium,Green,Yes,2,NA,Dog,True,43.983168760314584,86,TRUE
+Medium,Green,No,2,NA,Dog,False,75.44751586392522,86,FALSE
+High,Blue,Yes,3,NA,Bird,True,62.922113155946136,39,TRUE
+High,Blue,Yes,3,NA,Bird,True,71.01824013516307,31,TRUE
+Low,NA,Yes,1,NA,Cat,True,0.062477332539856434,81,TRUE
+Medium,Green,Yes,2,NA,Dog,True,47.53165740985423,50,TRUE
+Medium,Green,No,2,NA,Dog,False,22.011888516135514,34,FALSE
+Low,NA,No,1,NA,Cat,False,37.98165377229452,4,FALSE
+Medium,Green,Yes,2,NA,Dog,True,61.277100327424705,13,TRUE
+Low,NA,No,1,NA,Cat,False,35.179790924303234,69,FALSE
+Low,NA,No,1,NA,Cat,False,11.113542434759438,25,FALSE
+Medium,Green,No,2,NA,Dog,False,24.361947271972895,52,FALSE
+High,Blue,No,3,NA,Bird,False,66.80555874481797,22,FALSE
+High,Blue,Yes,3,NA,Bird,True,41.764677967876196,89,TRUE
+Low,NA,No,1,NA,Cat,False,78.81958340294659,32,FALSE
+Medium,Green,No,2,NA,Dog,False,10.286464425735176,25,FALSE
+Low,NA,No,1,NA,Cat,False,43.489274149760604,87,FALSE
+Medium,Green,Yes,2,NA,Dog,True,98.49569799844176,35,TRUE
+Low,NA,Yes,1,NA,Cat,True,89.30511143989861,40,TRUE
+High,Blue,No,3,NA,Bird,False,88.64690607879311,30,FALSE
+High,Blue,Yes,3,NA,Bird,True,17.505265027284622,12,TRUE
+Medium,Green,No,2,NA,Dog,False,13.069569156505167,31,FALSE
+High,Blue,No,3,NA,Bird,False,65.31019250396639,30,FALSE
+Low,NA,Yes,1,NA,Cat,True,34.3516472261399,64,TRUE
+Medium,Green,No,2,NA,Dog,False,65.67581279668957,99,FALSE
+Medium,Green,No,2,NA,Dog,False,32.03732424881309,14,FALSE
+High,Blue,Yes,3,NA,Bird,True,18.769111926667392,93,TRUE
+Medium,Green,Yes,2,NA,Dog,True,78.22943013161421,96,TRUE
+Low,NA,No,1,NA,Cat,False,9.359498671256006,71,FALSE
+High,Blue,Yes,3,NA,Bird,True,46.677904156968,67,TRUE
+High,Blue,Yes,3,NA,Bird,True,51.15054599009454,23,TRUE
diff --git a/tests/testthat/data_files/STANDARDISE/std_1.rda b/tests/testthat/data_files/STANDARDISE/std_1.rda
new file mode 100644
index 000000000..df5a8854f
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_1.rda differ
diff --git a/tests/testthat/data_files/STANDARDISE/std_1_d.csv b/tests/testthat/data_files/STANDARDISE/std_1_d.csv
new file mode 100644
index 000000000..9fe7462f6
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_1_d.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,fac_col6,fac_col9,col12,col15,col18
+High,Blue,Yes,3,NA,Bird,True,28.7577520124614,31,TRUE
+High,Blue,Yes,3,NA,Bird,True,78.8305135443807,79,TRUE
+High,Blue,Yes,3,NA,Bird,True,40.89769218117,51,TRUE
+Medium,Green,No,2,NA,Dog,False,88.3017404004931,14,FALSE
+High,Blue,Yes,3,NA,Bird,True,94.0467284293845,67,TRUE
+Medium,Green,No,2,NA,Dog,False,4.55564993899316,42,FALSE
+Medium,Green,No,2,NA,Dog,False,52.8105488047004,50,FALSE
+Medium,Green,No,2,NA,Dog,False,89.2419044394046,43,FALSE
+High,Blue,Yes,3,NA,Bird,True,55.1435014465824,14,TRUE
+Low,NA,Yes,1,NA,Cat,True,45.6614735303447,25,TRUE
+Medium,Green,No,2,NA,Dog,False,95.6833345349878,90,FALSE
+Medium,Green,No,2,NA,Dog,False,45.3334156190977,91,FALSE
+Low,NA,No,1,NA,Cat,False,67.7570635452867,69,FALSE
+Medium,Green,Yes,2,NA,Dog,True,57.2633401956409,91,TRUE
+High,Blue,No,3,NA,Bird,False,10.2924682665616,57,FALSE
+Low,NA,Yes,1,NA,Cat,True,89.9824970401824,92,TRUE
+High,Blue,No,3,NA,Bird,False,24.608773435466,9,FALSE
+High,Blue,Yes,3,NA,Bird,True,4.20595335308462,93,TRUE
+Low,NA,Yes,1,NA,Cat,True,32.7920719282702,99,TRUE
+Low,NA,Yes,1,NA,Cat,True,95.4503649147227,72,TRUE
+Low,NA,Yes,1,NA,Cat,True,88.9539316063747,26,TRUE
+Low,NA,No,1,NA,Cat,False,69.28034061566,7,FALSE
+High,Blue,Yes,3,NA,Bird,True,64.0506813768297,42,TRUE
+Medium,Green,Yes,2,NA,Dog,True,99.4269776623696,9,TRUE
+High,Blue,Yes,3,NA,Bird,True,65.5705799115822,83,TRUE
+Medium,Green,Yes,2,NA,Dog,True,70.8530468167737,36,TRUE
+Low,NA,No,1,NA,Cat,False,54.4066024711356,78,FALSE
+Medium,Green,No,2,NA,Dog,False,59.414202044718,81,FALSE
+High,Blue,Yes,3,NA,Bird,True,28.915973729454,43,TRUE
+Medium,Green,No,2,NA,Dog,False,14.7113647311926,76,FALSE
+Low,NA,Yes,1,NA,Cat,True,96.3024232536554,15,TRUE
+High,Blue,No,3,NA,Bird,False,90.2299045119435,32,FALSE
+High,Blue,Yes,3,NA,Bird,True,69.0705278422683,7,TRUE
+Low,NA,No,1,NA,Cat,False,79.5467417687178,9,FALSE
+High,Blue,No,3,NA,Bird,False,2.46136845089495,41,FALSE
+Medium,Green,Yes,2,NA,Dog,True,47.7795971091837,74,TRUE
+Low,NA,Yes,1,NA,Cat,True,75.8459537522867,23,TRUE
+High,Blue,Yes,3,NA,Bird,True,21.6407935833558,27,TRUE
+Low,NA,Yes,1,NA,Cat,True,31.8181007634848,60,TRUE
+Low,NA,No,1,NA,Cat,False,23.1625785352662,53,FALSE
+Medium,Green,Yes,2,NA,Dog,True,14.2800022382289,7,TRUE
+High,Blue,No,3,NA,Bird,False,41.4546335814521,53,FALSE
+High,Blue,No,3,NA,Bird,False,41.3724326295778,27,FALSE
+Low,NA,Yes,1,NA,Cat,True,36.8845450924709,96,TRUE
+High,Blue,Yes,3,NA,Bird,True,15.2444747742265,38,TRUE
+Low,NA,Yes,1,NA,Cat,True,13.880606344901,89,TRUE
+High,Blue,Yes,3,NA,Bird,True,23.3034099452198,34,TRUE
+Medium,Green,No,2,NA,Dog,False,46.5962450252846,93,FALSE
+Low,NA,Yes,1,NA,Cat,True,26.5972640365362,69,TRUE
+Medium,Green,Yes,2,NA,Dog,True,85.7827715342864,72,TRUE
+Low,NA,No,1,NA,Cat,False,4.58311666734517,76,FALSE
+Low,NA,Yes,1,NA,Cat,True,44.2200074205175,63,TRUE
+High,Blue,Yes,3,NA,Bird,True,79.8924845643342,13,TRUE
+Low,NA,Yes,1,NA,Cat,True,12.189925997518,82,TRUE
+Medium,Green,Yes,2,NA,Dog,True,56.0947983758524,97,TRUE
+Low,NA,No,1,NA,Cat,False,20.653138961643,91,FALSE
+Low,NA,No,1,NA,Cat,False,12.7531650243327,25,FALSE
+High,Blue,Yes,3,NA,Bird,True,75.3307864302769,38,TRUE
+Low,NA,No,1,NA,Cat,False,89.50453591533,21,FALSE
+Medium,Green,Yes,2,NA,Dog,True,37.4462775886059,79,TRUE
+Low,NA,Yes,1,NA,Cat,True,66.5115194628015,41,TRUE
+High,Blue,No,3,NA,Bird,False,9.48406609240919,47,FALSE
+Low,NA,No,1,NA,Cat,False,38.3969637798145,90,FALSE
+High,Blue,Yes,3,NA,Bird,True,27.438364457339,60,TRUE
+Medium,Green,Yes,2,NA,Dog,True,81.4640038879588,95,TRUE
+High,Blue,No,3,NA,Bird,False,44.8516341391951,16,FALSE
+Medium,Green,Yes,2,NA,Dog,True,81.0064353048801,94,TRUE
+Medium,Green,Yes,2,NA,Dog,True,81.2389509519562,6,TRUE
+High,Blue,Yes,3,NA,Bird,True,79.4342321110889,72,TRUE
+Medium,Green,Yes,2,NA,Dog,True,43.9831687603146,86,TRUE
+Medium,Green,No,2,NA,Dog,False,75.4475158639252,86,FALSE
+High,Blue,Yes,3,NA,Bird,True,62.9221131559461,39,TRUE
+High,Blue,Yes,3,NA,Bird,True,71.0182401351631,31,TRUE
+Low,NA,Yes,1,NA,Cat,True,0.0624773325398564,81,TRUE
+Medium,Green,Yes,2,NA,Dog,True,47.5316574098542,50,TRUE
+Medium,Green,No,2,NA,Dog,False,22.0118885161355,34,FALSE
+Low,NA,No,1,NA,Cat,False,37.9816537722945,4,FALSE
+Medium,Green,Yes,2,NA,Dog,True,61.2771003274247,13,TRUE
+Low,NA,No,1,NA,Cat,False,35.1797909243032,69,FALSE
+Low,NA,No,1,NA,Cat,False,11.1135424347594,25,FALSE
+Medium,Green,No,2,NA,Dog,False,24.3619472719729,52,FALSE
+High,Blue,No,3,NA,Bird,False,66.805558744818,22,FALSE
+High,Blue,Yes,3,NA,Bird,True,41.7646779678762,89,TRUE
+Low,NA,No,1,NA,Cat,False,78.8195834029466,32,FALSE
+Medium,Green,No,2,NA,Dog,False,10.2864644257352,25,FALSE
+Low,NA,No,1,NA,Cat,False,43.4892741497606,87,FALSE
+Medium,Green,Yes,2,NA,Dog,True,98.4956979984418,35,TRUE
+Low,NA,Yes,1,NA,Cat,True,89.3051114398986,40,TRUE
+High,Blue,No,3,NA,Bird,False,88.6469060787931,30,FALSE
+High,Blue,Yes,3,NA,Bird,True,17.5052650272846,12,TRUE
+Medium,Green,No,2,NA,Dog,False,13.0695691565052,31,FALSE
+High,Blue,No,3,NA,Bird,False,65.3101925039664,30,FALSE
+Low,NA,Yes,1,NA,Cat,True,34.3516472261399,64,TRUE
+Medium,Green,No,2,NA,Dog,False,65.6758127966896,99,FALSE
+Medium,Green,No,2,NA,Dog,False,32.0373242488131,14,FALSE
+High,Blue,Yes,3,NA,Bird,True,18.7691119266674,93,TRUE
+Medium,Green,Yes,2,NA,Dog,True,78.2294301316142,96,TRUE
+Low,NA,No,1,NA,Cat,False,9.35949867125601,71,FALSE
+High,Blue,Yes,3,NA,Bird,True,46.677904156968,67,TRUE
+High,Blue,Yes,3,NA,Bird,True,51.1505459900945,23,TRUE
diff --git a/tests/testthat/data_files/STANDARDISE/std_1_d.rda b/tests/testthat/data_files/STANDARDISE/std_1_d.rda
new file mode 100644
index 000000000..4387f72b8
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_1_d.rda differ
diff --git a/tests/testthat/data_files/STANDARDISE/std_2.csv b/tests/testthat/data_files/STANDARDISE/std_2.csv
new file mode 100644
index 000000000..9c20866c4
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_2.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,fac_col7,fac_col10,col13,col16,col19
+High,NA,NA,C,2,Large,Left,o,28.757752012461424,31
+High,NA,NA,C,2,Large,Left,s,78.83051354438066,79
+High,NA,NA,C,2,Large,Left,n,40.89769218116999,51
+Medium,Green,No,B,3,Medium,Right,c,88.301740400493145,14
+High,NA,NA,C,2,Large,Left,j,94.04672842938453,67
+Medium,Green,No,B,3,Medium,Right,r,4.555649938993156,42
+Medium,Green,No,B,3,Medium,Right,v,52.810548804700375,50
+Medium,Green,No,B,3,Medium,Right,k,89.2419044394046,43
+High,NA,NA,C,2,Large,Left,e,55.14350144658238,14
+Low,Red,NA,A,1,Small,Left,t,45.661473530344665,25
+Medium,Green,No,B,3,Medium,Right,n,95.68333453498781,90
+Medium,Green,No,B,3,Medium,Right,v,45.33341561909765,91
+Low,Red,No,A,1,Small,Right,y,67.75706354528666,69
+Medium,Green,NA,B,3,Medium,Left,z,57.26334019564092,91
+High,NA,No,C,2,Large,Right,e,10.292468266561627,57
+Low,Red,NA,A,1,Small,Left,s,89.98249704018235,92
+High,NA,No,C,2,Large,Right,y,24.60877343546599,9
+High,NA,NA,C,2,Large,Left,y,4.205953353084624,93
+Low,Red,NA,A,1,Small,Left,i,32.79207192827016,99
+Low,Red,NA,A,1,Small,Left,c,95.45036491472274,72
+Low,Red,NA,A,1,Small,Left,h,88.95393160637468,26
+Low,Red,No,A,1,Small,Right,z,69.28034061565995,7
+High,NA,NA,C,2,Large,Left,g,64.05068137682974,42
+Medium,Green,NA,B,3,Medium,Left,j,99.42697766236961,9
+High,NA,NA,C,2,Large,Left,i,65.57057991158217,83
+Medium,Green,NA,B,3,Medium,Left,s,70.85304681677371,36
+Low,Red,No,A,1,Small,Right,d,54.40660247113556,78
+Medium,Green,No,B,3,Medium,Right,n,59.41420204471797,81
+High,NA,NA,C,2,Large,Left,q,28.91597372945398,43
+Medium,Green,No,B,3,Medium,Right,k,14.711364731192589,76
+Low,Red,NA,A,1,Small,Left,g,96.30242325365543,15
+High,NA,No,C,2,Large,Right,u,90.22990451194346,32
+High,NA,NA,C,2,Large,Left,l,69.07052784226835,7
+Low,Red,No,A,1,Small,Right,o,79.54674176871777,9
+High,NA,No,C,2,Large,Right,j,2.461368450894952,41
+Medium,Green,NA,B,3,Medium,Left,m,47.77959710918367,74
+Low,Red,NA,A,1,Small,Left,g,75.84595375228673,23
+High,NA,NA,C,2,Large,Left,i,21.640793583355844,27
+Low,Red,NA,A,1,Small,Left,i,31.818100763484836,60
+Low,Red,No,A,1,Small,Right,j,23.16257853526622,53
+Medium,Green,NA,B,3,Medium,Left,w,14.280002238228917,7
+High,NA,No,C,2,Large,Right,u,41.45463358145207,53
+High,NA,No,C,2,Large,Right,g,41.372432629577816,27
+Low,Red,NA,A,1,Small,Left,u,36.884545092470944,96
+High,NA,NA,C,2,Large,Left,f,15.244474774226546,38
+Low,Red,NA,A,1,Small,Left,y,13.880606344901025,89
+High,NA,NA,C,2,Large,Left,b,23.303409945219755,34
+Medium,Green,No,B,3,Medium,Right,e,46.59624502528459,93
+Low,Red,NA,A,1,Small,Left,h,26.597264036536217,69
+Medium,Green,NA,B,3,Medium,Left,l,85.78277153428644,72
+Low,Red,No,A,1,Small,Right,m,4.583116667345166,76
+Low,Red,NA,A,1,Small,Left,r,44.220007420517504,63
+High,NA,NA,C,2,Large,Left,a,79.89248456433415,13
+Low,Red,NA,A,1,Small,Left,y,12.189925997518003,82
+Medium,Green,NA,B,3,Medium,Left,y,56.094798375852406,97
+Low,Red,No,A,1,Small,Right,f,20.65313896164298,91
+Low,Red,No,A,1,Small,Right,u,12.753165024332702,25
+High,NA,NA,C,2,Large,Left,o,75.33078643027693,38
+Low,Red,No,A,1,Small,Right,i,89.50453591533005,21
+Medium,Green,NA,B,3,Medium,Left,o,37.44627758860588,79
+Low,Red,NA,A,1,Small,Left,z,66.51151946280152,41
+High,NA,No,C,2,Large,Right,p,9.484066092409194,47
+Low,Red,No,A,1,Small,Right,t,38.39696377981454,90
+High,NA,NA,C,2,Large,Left,f,27.43836445733905,60
+Medium,Green,NA,B,3,Medium,Left,k,81.46400388795882,95
+High,NA,No,C,2,Large,Right,h,44.851634139195085,16
+Medium,Green,NA,B,3,Medium,Left,v,81.00643530488014,94
+Medium,Green,NA,B,3,Medium,Left,v,81.23895095195621,6
+High,NA,NA,C,2,Large,Left,g,79.43423211108893,72
+Medium,Green,NA,B,3,Medium,Left,p,43.983168760314584,86
+Medium,Green,No,B,3,Medium,Right,q,75.44751586392522,86
+High,NA,NA,C,2,Large,Left,v,62.922113155946136,39
+High,NA,NA,C,2,Large,Left,r,71.01824013516307,31
+Low,Red,NA,A,1,Small,Left,q,0.062477332539856434,81
+Medium,Green,NA,B,3,Medium,Left,b,47.53165740985423,50
+Medium,Green,No,B,3,Medium,Right,d,22.011888516135514,34
+Low,Red,No,A,1,Small,Right,m,37.98165377229452,4
+Medium,Green,NA,B,3,Medium,Left,e,61.277100327424705,13
+Low,Red,No,A,1,Small,Right,v,35.179790924303234,69
+Low,Red,No,A,1,Small,Right,s,11.113542434759438,25
+Medium,Green,No,B,3,Medium,Right,y,24.361947271972895,52
+High,NA,No,C,2,Large,Right,t,66.80555874481797,22
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+Low,Red,No,A,1,Small,Right,y,78.81958340294659,32
+Medium,Green,No,B,3,Medium,Right,n,10.286464425735176,25
+Low,Red,No,A,1,Small,Right,y,43.489274149760604,87
+Medium,Green,NA,B,3,Medium,Left,w,98.49569799844176,35
+Low,Red,NA,A,1,Small,Left,c,89.30511143989861,40
+High,NA,No,C,2,Large,Right,h,88.64690607879311,30
+High,NA,NA,C,2,Large,Left,p,17.505265027284622,12
+Medium,Green,No,B,3,Medium,Right,l,13.069569156505167,31
+High,NA,No,C,2,Large,Right,y,65.31019250396639,30
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+Medium,Green,No,B,3,Medium,Right,c,65.67581279668957,99
+Medium,Green,No,B,3,Medium,Right,n,32.03732424881309,14
+High,NA,NA,C,2,Large,Left,g,18.769111926667392,93
+Medium,Green,NA,B,3,Medium,Left,c,78.22943013161421,96
+Low,Red,No,A,1,Small,Right,w,9.359498671256006,71
+High,NA,NA,C,2,Large,Left,v,46.677904156968,67
+High,NA,NA,C,2,Large,Left,z,51.15054599009454,23
diff --git a/tests/testthat/data_files/STANDARDISE/std_2.rda b/tests/testthat/data_files/STANDARDISE/std_2.rda
new file mode 100644
index 000000000..cbe3d2791
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_2.rda differ
diff --git a/tests/testthat/data_files/STANDARDISE/std_2_d.csv b/tests/testthat/data_files/STANDARDISE/std_2_d.csv
new file mode 100644
index 000000000..0a5a46eba
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_2_d.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,fac_col7,fac_col10,col13,col16,col19
+High,NA,NA,C,2,Large,Left,o,28.7577520124614,31
+High,NA,NA,C,2,Large,Left,s,78.8305135443807,79
+High,NA,NA,C,2,Large,Left,n,40.89769218117,51
+Medium,Green,No,B,3,Medium,Right,c,88.3017404004931,14
+High,NA,NA,C,2,Large,Left,j,94.0467284293845,67
+Medium,Green,No,B,3,Medium,Right,r,4.55564993899316,42
+Medium,Green,No,B,3,Medium,Right,v,52.8105488047004,50
+Medium,Green,No,B,3,Medium,Right,k,89.2419044394046,43
+High,NA,NA,C,2,Large,Left,e,55.1435014465824,14
+Low,Red,NA,A,1,Small,Left,t,45.6614735303447,25
+Medium,Green,No,B,3,Medium,Right,n,95.6833345349878,90
+Medium,Green,No,B,3,Medium,Right,v,45.3334156190977,91
+Low,Red,No,A,1,Small,Right,y,67.7570635452867,69
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+Low,Red,NA,A,1,Small,Left,c,95.4503649147227,72
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+Medium,Green,NA,B,3,Medium,Left,s,70.8530468167737,36
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+High,NA,NA,C,2,Large,Left,l,69.0705278422683,7
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+Low,Red,NA,A,1,Small,Left,i,31.8181007634848,60
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+High,NA,No,C,2,Large,Right,g,41.3724326295778,27
+Low,Red,NA,A,1,Small,Left,u,36.8845450924709,96
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+Low,Red,NA,A,1,Small,Left,y,13.880606344901,89
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diff --git a/tests/testthat/data_files/STANDARDISE/std_2_d.rda b/tests/testthat/data_files/STANDARDISE/std_2_d.rda
new file mode 100644
index 000000000..cad2198a2
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_2_d.rda differ
diff --git a/tests/testthat/data_files/STANDARDISE/std_3.csv b/tests/testthat/data_files/STANDARDISE/std_3.csv
new file mode 100644
index 000000000..583c9a22e
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_3.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,col11,col14,col17,col20
+High,Blue,Yes,C,Three,31,TRUE,o,28.757752012461424
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+Medium,NA,Yes,B,Two,94,TRUE,v,81.00643530488014
+Medium,NA,Yes,B,Two,6,TRUE,v,81.23895095195621
+High,Blue,Yes,C,Three,72,TRUE,g,79.43423211108893
+Medium,NA,Yes,B,Two,86,TRUE,p,43.983168760314584
+Medium,NA,NA,B,Two,86,FALSE,q,75.44751586392522
+High,Blue,Yes,C,Three,39,TRUE,v,62.922113155946136
+High,Blue,Yes,C,Three,31,TRUE,r,71.01824013516307
+Low,NA,Yes,A,One,81,TRUE,q,0.062477332539856434
+Medium,NA,Yes,B,Two,50,TRUE,b,47.53165740985423
+Medium,NA,NA,B,Two,34,FALSE,d,22.011888516135514
+Low,NA,NA,A,One,4,FALSE,m,37.98165377229452
+Medium,NA,Yes,B,Two,13,TRUE,e,61.277100327424705
+Low,NA,NA,A,One,69,FALSE,v,35.179790924303234
+Low,NA,NA,A,One,25,FALSE,s,11.113542434759438
+Medium,NA,NA,B,Two,52,FALSE,y,24.361947271972895
+High,Blue,NA,C,Three,22,FALSE,t,66.80555874481797
+High,Blue,Yes,C,Three,89,TRUE,v,41.764677967876196
+Low,NA,NA,A,One,32,FALSE,y,78.81958340294659
+Medium,NA,NA,B,Two,25,FALSE,n,10.286464425735176
+Low,NA,NA,A,One,87,FALSE,y,43.489274149760604
+Medium,NA,Yes,B,Two,35,TRUE,w,98.49569799844176
+Low,NA,Yes,A,One,40,TRUE,c,89.30511143989861
+High,Blue,NA,C,Three,30,FALSE,h,88.64690607879311
+High,Blue,Yes,C,Three,12,TRUE,p,17.505265027284622
+Medium,NA,NA,B,Two,31,FALSE,l,13.069569156505167
+High,Blue,NA,C,Three,30,FALSE,y,65.31019250396639
+Low,NA,Yes,A,One,64,TRUE,n,34.3516472261399
+Medium,NA,NA,B,Two,99,FALSE,c,65.67581279668957
+Medium,NA,NA,B,Two,14,FALSE,n,32.03732424881309
+High,Blue,Yes,C,Three,93,TRUE,g,18.769111926667392
+Medium,NA,Yes,B,Two,96,TRUE,c,78.22943013161421
+Low,NA,NA,A,One,71,FALSE,w,9.359498671256006
+High,Blue,Yes,C,Three,67,TRUE,v,46.677904156968
+High,Blue,Yes,C,Three,23,TRUE,z,51.15054599009454
diff --git a/tests/testthat/data_files/STANDARDISE/std_3.rda b/tests/testthat/data_files/STANDARDISE/std_3.rda
new file mode 100644
index 000000000..803626748
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_3.rda differ
diff --git a/tests/testthat/data_files/STANDARDISE/std_3_d.csv b/tests/testthat/data_files/STANDARDISE/std_3_d.csv
new file mode 100644
index 000000000..5dfce08f8
--- /dev/null
+++ b/tests/testthat/data_files/STANDARDISE/std_3_d.csv
@@ -0,0 +1,101 @@
+fac_col1,fac_col2,fac_col3,fac_col4,fac_col5,col11,col14,col17,col20
+High,Blue,Yes,C,Three,31,TRUE,o,28.7577520124614
+High,Blue,Yes,C,Three,79,TRUE,s,78.8305135443807
+High,Blue,Yes,C,Three,51,TRUE,n,40.89769218117
+Medium,NA,NA,B,Two,14,FALSE,c,88.3017404004931
+High,Blue,Yes,C,Three,67,TRUE,j,94.0467284293845
+Medium,NA,NA,B,Two,42,FALSE,r,4.55564993899316
+Medium,NA,NA,B,Two,50,FALSE,v,52.8105488047004
+Medium,NA,NA,B,Two,43,FALSE,k,89.2419044394046
+High,Blue,Yes,C,Three,14,TRUE,e,55.1435014465824
+Low,NA,Yes,A,One,25,TRUE,t,45.6614735303447
+Medium,NA,NA,B,Two,90,FALSE,n,95.6833345349878
+Medium,NA,NA,B,Two,91,FALSE,v,45.3334156190977
+Low,NA,NA,A,One,69,FALSE,y,67.7570635452867
+Medium,NA,Yes,B,Two,91,TRUE,z,57.2633401956409
+High,Blue,NA,C,Three,57,FALSE,e,10.2924682665616
+Low,NA,Yes,A,One,92,TRUE,s,89.9824970401824
+High,Blue,NA,C,Three,9,FALSE,y,24.608773435466
+High,Blue,Yes,C,Three,93,TRUE,y,4.20595335308462
+Low,NA,Yes,A,One,99,TRUE,i,32.7920719282702
+Low,NA,Yes,A,One,72,TRUE,c,95.4503649147227
+Low,NA,Yes,A,One,26,TRUE,h,88.9539316063747
+Low,NA,NA,A,One,7,FALSE,z,69.28034061566
+High,Blue,Yes,C,Three,42,TRUE,g,64.0506813768297
+Medium,NA,Yes,B,Two,9,TRUE,j,99.4269776623696
+High,Blue,Yes,C,Three,83,TRUE,i,65.5705799115822
+Medium,NA,Yes,B,Two,36,TRUE,s,70.8530468167737
+Low,NA,NA,A,One,78,FALSE,d,54.4066024711356
+Medium,NA,NA,B,Two,81,FALSE,n,59.414202044718
+High,Blue,Yes,C,Three,43,TRUE,q,28.915973729454
+Medium,NA,NA,B,Two,76,FALSE,k,14.7113647311926
+Low,NA,Yes,A,One,15,TRUE,g,96.3024232536554
+High,Blue,NA,C,Three,32,FALSE,u,90.2299045119435
+High,Blue,Yes,C,Three,7,TRUE,l,69.0705278422683
+Low,NA,NA,A,One,9,FALSE,o,79.5467417687178
+High,Blue,NA,C,Three,41,FALSE,j,2.46136845089495
+Medium,NA,Yes,B,Two,74,TRUE,m,47.7795971091837
+Low,NA,Yes,A,One,23,TRUE,g,75.8459537522867
+High,Blue,Yes,C,Three,27,TRUE,i,21.6407935833558
+Low,NA,Yes,A,One,60,TRUE,i,31.8181007634848
+Low,NA,NA,A,One,53,FALSE,j,23.1625785352662
+Medium,NA,Yes,B,Two,7,TRUE,w,14.2800022382289
+High,Blue,NA,C,Three,53,FALSE,u,41.4546335814521
+High,Blue,NA,C,Three,27,FALSE,g,41.3724326295778
+Low,NA,Yes,A,One,96,TRUE,u,36.8845450924709
+High,Blue,Yes,C,Three,38,TRUE,f,15.2444747742265
+Low,NA,Yes,A,One,89,TRUE,y,13.880606344901
+High,Blue,Yes,C,Three,34,TRUE,b,23.3034099452198
+Medium,NA,NA,B,Two,93,FALSE,e,46.5962450252846
+Low,NA,Yes,A,One,69,TRUE,h,26.5972640365362
+Medium,NA,Yes,B,Two,72,TRUE,l,85.7827715342864
+Low,NA,NA,A,One,76,FALSE,m,4.58311666734517
+Low,NA,Yes,A,One,63,TRUE,r,44.2200074205175
+High,Blue,Yes,C,Three,13,TRUE,a,79.8924845643342
+Low,NA,Yes,A,One,82,TRUE,y,12.189925997518
+Medium,NA,Yes,B,Two,97,TRUE,y,56.0947983758524
+Low,NA,NA,A,One,91,FALSE,f,20.653138961643
+Low,NA,NA,A,One,25,FALSE,u,12.7531650243327
+High,Blue,Yes,C,Three,38,TRUE,o,75.3307864302769
+Low,NA,NA,A,One,21,FALSE,i,89.50453591533
+Medium,NA,Yes,B,Two,79,TRUE,o,37.4462775886059
+Low,NA,Yes,A,One,41,TRUE,z,66.5115194628015
+High,Blue,NA,C,Three,47,FALSE,p,9.48406609240919
+Low,NA,NA,A,One,90,FALSE,t,38.3969637798145
+High,Blue,Yes,C,Three,60,TRUE,f,27.438364457339
+Medium,NA,Yes,B,Two,95,TRUE,k,81.4640038879588
+High,Blue,NA,C,Three,16,FALSE,h,44.8516341391951
+Medium,NA,Yes,B,Two,94,TRUE,v,81.0064353048801
+Medium,NA,Yes,B,Two,6,TRUE,v,81.2389509519562
+High,Blue,Yes,C,Three,72,TRUE,g,79.4342321110889
+Medium,NA,Yes,B,Two,86,TRUE,p,43.9831687603146
+Medium,NA,NA,B,Two,86,FALSE,q,75.4475158639252
+High,Blue,Yes,C,Three,39,TRUE,v,62.9221131559461
+High,Blue,Yes,C,Three,31,TRUE,r,71.0182401351631
+Low,NA,Yes,A,One,81,TRUE,q,0.0624773325398564
+Medium,NA,Yes,B,Two,50,TRUE,b,47.5316574098542
+Medium,NA,NA,B,Two,34,FALSE,d,22.0118885161355
+Low,NA,NA,A,One,4,FALSE,m,37.9816537722945
+Medium,NA,Yes,B,Two,13,TRUE,e,61.2771003274247
+Low,NA,NA,A,One,69,FALSE,v,35.1797909243032
+Low,NA,NA,A,One,25,FALSE,s,11.1135424347594
+Medium,NA,NA,B,Two,52,FALSE,y,24.3619472719729
+High,Blue,NA,C,Three,22,FALSE,t,66.805558744818
+High,Blue,Yes,C,Three,89,TRUE,v,41.7646779678762
+Low,NA,NA,A,One,32,FALSE,y,78.8195834029466
+Medium,NA,NA,B,Two,25,FALSE,n,10.2864644257352
+Low,NA,NA,A,One,87,FALSE,y,43.4892741497606
+Medium,NA,Yes,B,Two,35,TRUE,w,98.4956979984418
+Low,NA,Yes,A,One,40,TRUE,c,89.3051114398986
+High,Blue,NA,C,Three,30,FALSE,h,88.6469060787931
+High,Blue,Yes,C,Three,12,TRUE,p,17.5052650272846
+Medium,NA,NA,B,Two,31,FALSE,l,13.0695691565052
+High,Blue,NA,C,Three,30,FALSE,y,65.3101925039664
+Low,NA,Yes,A,One,64,TRUE,n,34.3516472261399
+Medium,NA,NA,B,Two,99,FALSE,c,65.6758127966896
+Medium,NA,NA,B,Two,14,FALSE,n,32.0373242488131
+High,Blue,Yes,C,Three,93,TRUE,g,18.7691119266674
+Medium,NA,Yes,B,Two,96,TRUE,c,78.2294301316142
+Low,NA,NA,A,One,71,FALSE,w,9.35949867125601
+High,Blue,Yes,C,Three,67,TRUE,v,46.677904156968
+High,Blue,Yes,C,Three,23,TRUE,z,51.1505459900945
diff --git a/tests/testthat/data_files/STANDARDISE/std_3_d.rda b/tests/testthat/data_files/STANDARDISE/std_3_d.rda
new file mode 100644
index 000000000..4165f0983
Binary files /dev/null and b/tests/testthat/data_files/STANDARDISE/std_3_d.rda differ
diff --git a/tests/testthat/data_files/molgenis_armadillo-upload_testing_datasets.R b/tests/testthat/data_files/molgenis_armadillo-upload_testing_datasets.R
index 9e1299710..e6dac369f 100644
--- a/tests/testthat/data_files/molgenis_armadillo-upload_testing_datasets.R
+++ b/tests/testthat/data_files/molgenis_armadillo-upload_testing_datasets.R
@@ -1,4 +1,4 @@
-# 
+#
 # Molgenis' Armadillo - Upload Testing Datasets
 #
 
@@ -15,7 +15,7 @@ upload_testing_dataset_table <- function(project_name, folder_name, table_name,
 MolgenisArmadillo::armadillo.login_basic(armadillo = 'http://127.0.0.1:8080', username = "admin", password = "admin")
 
 if (! 'datashield' %in% MolgenisArmadillo::armadillo.list_projects())
-    MolgenisArmadillo::armadillo.create_project('datashield')
+    MolgenisArmadillo::armadillo.create_project('datashield', overwrite_existing = "no")
 
 upload_testing_dataset_table('datashield', 'anthro', 'anthro1', 'ANTHRO/anthro1.rda')
 upload_testing_dataset_table('datashield', 'anthro', 'anthro2', 'ANTHRO/anthro2.rda')
@@ -69,4 +69,12 @@ upload_testing_dataset_table('datashield', 'testing', 'DATASET1', 'TESTING/DATAS
 upload_testing_dataset_table('datashield', 'testing', 'DATASET2', 'TESTING/DATASET2.rda')
 upload_testing_dataset_table('datashield', 'testing', 'DATASET3', 'TESTING/DATASET3.rda')
 
+upload_testing_dataset_table('datashield', 'standardise', 'std_1', 'STANDARDISE/std_1.rda')
+upload_testing_dataset_table('datashield', 'standardise', 'std_2', 'STANDARDISE/std_2.rda')
+upload_testing_dataset_table('datashield', 'standardise', 'std_3', 'STANDARDISE/std_3.rda')
+
+upload_testing_dataset_table('datashield', 'standardise', 'std_1_d', 'STANDARDISE/std_1.rda')
+upload_testing_dataset_table('datashield', 'standardise', 'std_2_d', 'STANDARDISE/std_2.rda')
+upload_testing_dataset_table('datashield', 'standardise', 'std_3_d', 'STANDARDISE/std_3.rda')
+
 print(MolgenisArmadillo::armadillo.list_tables('datashield'))
diff --git a/tests/testthat/data_files/obiba_opal-upload_testing_datasets.R b/tests/testthat/data_files/obiba_opal-upload_testing_datasets.R
index ae79d2e62..1fce513b3 100644
--- a/tests/testthat/data_files/obiba_opal-upload_testing_datasets.R
+++ b/tests/testthat/data_files/obiba_opal-upload_testing_datasets.R
@@ -1,4 +1,4 @@
-# 
+#
 # Obiba's Opal - Upload Testing Datasets
 #
 
@@ -9,11 +9,11 @@ library(tibble)
 upload_testing_dataset_table <- function(opal, project_name, table_name, local_file_path) {
     if (! opal.project_exists(opal, project_name))
         opal.project_create(opal, project_name, database = "mongodb")
-  
+
     dataset_name <- load(file = local_file_path)
     dataset      <- eval(as.symbol(dataset_name))
     data         <- as_tibble(dataset, rownames = '_row_id_')
-  
+
     opal.table_save(opal, data, project_name, table_name, id.name = "_row_id_", force = TRUE)
 }
 
@@ -72,4 +72,14 @@ upload_testing_dataset_table(opal, 'TESTING', 'DATASET1', 'TESTING/DATASET1.rda'
 upload_testing_dataset_table(opal, 'TESTING', 'DATASET2', 'TESTING/DATASET2.rda')
 upload_testing_dataset_table(opal, 'TESTING', 'DATASET3', 'TESTING/DATASET3.rda')
 
+upload_testing_dataset_table('STANDARDISE', 'std_1', 'STANDARDISE/std_1.rda')
+upload_testing_dataset_table('STANDARDISE', 'std_2', 'STANDARDISE/std_2.rda')
+upload_testing_dataset_table('STANDARDISE', 'std_3', 'STANDARDISE/std_3.rda')
+
+upload_testing_dataset_table('STANDARDISE', 'std_1_d', 'STANDARDISE/std_1_d.rda')
+upload_testing_dataset_table('STANDARDISE', 'std_2_d', 'STANDARDISE/std_2_d.rda')
+upload_testing_dataset_table('STANDARDISE', 'std_3_d', 'STANDARDISE/std_3_d.rda')
+
+
+
 opal.logout(opal)
diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R
index 4c55c6e74..1b0f9b8a6 100644
--- a/tests/testthat/setup.R
+++ b/tests/testthat/setup.R
@@ -24,6 +24,7 @@ library(DescTools)
 library(DSOpal)
 library(DSMolgenisArmadillo)
 library(DSLite)
+library(dsBase)
 
 source("dstest_functions/ds_expect_variables.R")
 source("perf_tests/perf_rate.R")
diff --git a/tests/testthat/test-smk-standardiseDf.R b/tests/testthat/test-smk-standardiseDf.R
new file mode 100644
index 000000000..d557c325b
--- /dev/null
+++ b/tests/testthat/test-smk-standardiseDf.R
@@ -0,0 +1,712 @@
+#
+# Set up
+#
+context("ds.standardiseDf::smk::setup")
+options(datashield.errors.print = TRUE)
+
+connect.studies.dataset.stand(
+  c(
+    "fac_col1", "fac_col2", "fac_col3", "fac_col4", "fac_col5", "fac_col6", "fac_col7", "fac_col9",
+    "fac_col10", "col11", "col12", "col13", "col14", "col15", "col16", "col17", "col18", "col19",
+    "col20")
+  )
+
+test_that("setup", {
+  ds_expect_variables(c("D"))
+})
+
+#
+# Tests
+#
+
+####################################################################################################
+# Code that will be used in multiple tests
+####################################################################################################
+var_class <- .get_var_classes("D", datasources = ds.test_env$connections)
+
+class_conflicts <- .identify_class_conflicts(var_class)
+
+different_classes <- c("fac_col4", "fac_col5")
+
+class_decisions <- c("1", "5")
+
+.fix_classes(
+  df.name = "D",
+  different_classes = different_classes,
+  class_decisions = class_decisions,
+  newobj = "new_classes",
+  datasources = ds.test_env$connections)
+
+cols_to_set <- c(
+  "fac_col1", "fac_col2", "fac_col3", "fac_col4", "fac_col5", "fac_col6", "fac_col9", "col12",
+  "col15", "col18", "fac_col7", "fac_col10", "col13", "col16", "col19", "col11", "col14", "col17",
+  "col20")
+
+.add_missing_cols_to_df(
+  df.name = "D",
+  cols_to_add_if_missing = cols_to_set,
+  newobj = "with_new_cols",
+  datasources = ds.test_env$connections)
+
+old_cols <- ds.colnames("D")
+
+new_cols <- c("col11", "col12", "col13", "col14", "col15", "col16", "col17", "col18", "col19",
+              "col20", "fac_col1", "fac_col10", "fac_col2", "fac_col3", "fac_col4", "fac_col5",
+              "fac_col6", "fac_col7", "fac_col9")
+
+new_cols_servers <- list(
+  server_1 = new_cols,
+  server_2 = new_cols,
+  server_3 = new_cols
+)
+
+added_cols <- .get_added_cols(old_cols, new_cols_servers)
+
+var_class_fact <- .get_var_classes("with_new_cols", datasources = ds.test_env$connections)
+
+fac_vars <- .identify_factor_vars(var_class_fact)
+
+fac_levels <- .get_factor_levels("with_new_cols", fac_vars, ds.test_env$connections)
+
+level_conflicts <- .identify_level_conflicts(fac_levels)
+
+unique_levs <- .get_unique_levels(fac_levels, level_conflicts)
+
+####################################################################################################
+# Tests
+####################################################################################################
+test_that(".stop_if_cols_identical throws error if columns are identical", {
+
+  identical_cols <- list(
+    c("col1", "col2", "col3"),
+    c("col1", "col2", "col3"),
+    c("col1", "col2", "col3")
+  )
+
+  expect_error(
+    .stop_if_cols_identical(identical_cols),
+    "Columns are identical in all data frames: nothing to fill"
+  )
+
+})
+
+test_that(".stop_if_cols_identical doesn't throw error if data frames have different columns", {
+
+  different_cols <- list(
+    c("col1", "col2", "col3"),
+    c("col1", "col2", "col4"),
+    c("col1", "col5", "col3")
+  )
+
+  expect_silent(
+    .stop_if_cols_identical(different_cols)
+  )
+
+})
+
+test_that(".get_var_classes returns correct output", {
+
+  expected <- tibble(
+    server = c("sim1", "sim2", "sim3"),
+    fac_col1 = c("factor", "factor", "factor"),
+    fac_col2 = c("factor", "factor", "factor"),
+    fac_col3 = c("factor", "factor", "factor"),
+    fac_col4 = c("numeric", "character", "factor"),
+    fac_col5 = c("logical", "integer", "factor"),
+    fac_col6 = c("factor", NA, NA),
+    fac_col9 = c("factor", NA, NA),
+    col12 = c("numeric", NA, NA),
+    col15 = c("integer", NA, NA),
+    col18 = c("logical", NA, NA),
+    fac_col7 = c(NA, "factor", NA),
+    fac_col10 = c(NA, "factor", NA),
+    col13 = c(NA, "character", NA),
+    col16 = c(NA, "numeric", NA),
+    col19 = c(NA, "integer", NA),
+    col11 = c(NA, NA, "integer"),
+    col14 = c(NA, NA, "logical"),
+    col17 = c(NA, NA, "character"),
+    col20 = c(NA, NA, "numeric")
+  )
+
+  expect_equal(var_class, expected)
+
+})
+
+test_that(".identify_class_conflicts returns correct output", {
+  expected <- list(
+    fac_col4 = c("numeric", "character", "factor"),
+    fac_col5 = c("logical", "integer", "factor")
+  )
+
+  expect_equal(class_conflicts, expected)
+
+})
+
+test_that("ask_question displays the correct prompt", {
+  expect_snapshot(ask_question_class("my_var"))
+})
+
+test_that("ask_question_wait_response_class continues with valid response", {
+  expect_equal(
+    with_mocked_bindings(
+      ask_question_wait_response_class("a variable"),
+      ask_question_class = function(var) "A question",
+      readline = function() "1"
+    ), "1"
+  )
+})
+
+test_that("ask_question_wait_response_class throws error if option 6 selected", {
+  expect_error(
+    with_mocked_bindings(
+      ask_question_wait_response_class("a variable"),
+      ask_question_class = function(var) "A question",
+      readline = function() "6")
+  )
+})
+
+test_that("print_all_classes prints the correct message", {
+  expect_snapshot(
+    print_all_classes(
+      c("server_1", "server_2", "server_3"),
+      c("numeric", "factor", "integer")
+    )
+  )
+})
+
+test_that("prompt_user_class_decision function properly", {
+  expect_message(
+    with_mocked_bindings(
+      prompt_user_class_decision(
+        var = "test_col",
+        servers = c("sim2", "sim2", "sim3"),
+        classes = c("numeric", "character", "factor"),
+        newobj = "test_df",
+        datasources = datasources),
+      ask_question_wait_response_class = function(var, newobj, datasources) "test_col"
+    )
+  )
+
+  expect_equal(
+    with_mocked_bindings(
+      prompt_user_class_decision(
+        var = "test_col",
+        servers = c("sim2", "sim2", "sim3"),
+        classes = c("numeric", "character", "factor"),
+        newobj = "test_df",
+        datasources = datasources),
+      ask_question_wait_response_class = function(var, newobj, datasources) "test_col"
+    ),
+    "test_col"
+  )
+})
+
+test_that("prompt_user_class_decision_all_vars returns correct value", {
+  expect_equal(
+    with_mocked_bindings(
+      prompt_user_class_decision_all_vars(
+        vars = c("test_var_1", "test_var_2"),
+        all_servers = c("sim2", "sim2", "sim3"),
+        all_classes = tibble(
+          test_var_1 = c("numeric", "character", "factor"),
+          test_var_2 = c("logical", "integer", "factor")
+        ),
+        "test_df",
+        conns),
+      prompt_user_class_decision = function(var, server, classes, newobj, datasources) "1"
+    ),
+    c("1", "1")
+  )
+})
+
+test_that(".fix_classes sets the correct classes in serverside data frame", {
+
+  expect_equal(
+    unname(unlist(ds.class("D$fac_col4"))),
+    c("numeric", "character", "factor")
+  )
+
+  expect_equal(
+    unname(unlist(ds.class("D$fac_col5"))),
+    c("logical", "integer", "factor")
+  )
+
+  expect_equal(
+    unname(unlist(ds.class("new_classes$fac_col4"))),
+    rep("factor", 3)
+  )
+
+  expect_equal(
+    unname(unlist(ds.class("new_classes$fac_col5"))),
+    rep("logical", 3)
+  )
+
+})
+
+test_that(".get_unique_cols extracts unique names from a list", {
+  expect_equal(
+    .get_unique_cols(
+      list(
+        server_1 = c("col_1", "col_2", "col_3"),
+        server_1 = c("col_1", "col_2", "col_4"),
+        server_1 = c("col_2", "col_3", "col_3", "col_5")
+      )
+    ),
+    c("col_1", "col_2", "col_3", "col_4", "col_5")
+  )
+})
+
+test_that(".add_missing_cols_to_df correctly creates missing columns", {
+
+  new_cols <- c("col11", "col12", "col13", "col14", "col15", "col16", "col17", "col18", "col19",
+                "col20", "fac_col1", "fac_col10", "fac_col2", "fac_col3", "fac_col4", "fac_col5",
+                "fac_col6", "fac_col7", "fac_col9")
+
+  observed <- ds.colnames("with_new_cols")
+
+  expected <- list(
+    sim1 = new_cols,
+    sim2 = new_cols,
+    sim3 = new_cols
+  )
+
+  expect_equal(observed, expected)
+})
+
+test_that(".get_added_cols correctly identifies newly added columns", {
+
+  expect_equal(
+    added_cols,
+    list(
+      sim1 = c("col11", "col13", "col14", "col16", "col17", "col19", "col20", "fac_col10", "fac_col7"),
+      sim2 = c("col11", "col12", "col14", "col15", "col17", "col18", "col20", "fac_col6", "fac_col9"),
+      sim3 = c("col12", "col13", "col15", "col16", "col18", "col19", "fac_col10", "fac_col6", "fac_col7", "fac_col9")
+    )
+  )
+})
+
+test_that(".identify_factor_vars correctly identifies factor variables", {
+
+
+
+  var_class_fact <- var_class |> dplyr::select(server: col18)
+  expect_equal(
+    names(fac_vars),
+    c("fac_col1", "fac_col2", "fac_col3", "fac_col6", "fac_col9")
+  )
+})
+
+test_that(".get_factor_levels correctly identifies factor levels", {
+  expected <- list(
+    sim1 = list(
+      fac_col1 = c("High", "Low", "Medium"),
+      fac_col2 = c("Blue", "Green"),
+      fac_col3 = c("No", "Yes"),
+      fac_col6 = c("Bird", "Cat", "Dog"),
+      fac_col9 = c("False", "True")
+    ),
+    sim2 = list(
+      fac_col1 = c("High", "Low", "Medium"),
+      fac_col2 = c("Green", "Red"),
+      fac_col3 = c("No"),
+      fac_col6 = NULL,
+      fac_col9 = NULL
+    ),
+    sim3 = list(
+      fac_col1 = c("High", "Low", "Medium"),
+      fac_col2 = c("Blue"),
+      fac_col3 = c("Yes"),
+      fac_col6 = NULL,
+      fac_col9 = NULL
+    )
+  )
+
+  expect_equal(fac_levels, expected)
+})
+
+test_that(".identify_level_conflicts correctly factor columns with different levels", {
+  expect_equal(
+    .identify_level_conflicts(fac_levels),
+    c("fac_col2", "fac_col3", "fac_col6", "fac_col9")
+  )
+
+})
+
+test_that("ask_question_wait_response_levels continues with valid response", {
+  expect_equal(
+    with_mocked_bindings(
+      suppressWarnings(ask_question_wait_response_levels("test variable", "test_obj", conns)),
+      readline = function() "1"
+    ), "1"
+  )
+
+  expect_equal(
+    with_mocked_bindings(
+      suppressWarnings(ask_question_wait_response_levels("test variable", "test_obj", conns)),
+      readline = function() "1"
+    ), "1"
+  )
+
+})
+
+test_that("ask_question_wait_response_levels aborts with response of 3", {
+  expect_error(
+    with_mocked_bindings(
+      suppressWarnings(ask_question_wait_response_levels("test variable", "test_obj", conns)),
+      readline = function() "3")
+  )
+})
+
+test_that(".make_levels_message makes correct message", {
+  expect_snapshot(.make_levels_message(level_conflicts))
+})
+
+test_that(".get_unique_levels extracts all possible levels", {
+
+  expected <- list(
+    fac_col2 = c("Blue", "Green", "Red"),
+    fac_col3 = c("No", "Yes"),
+    fac_col6 = c("Bird", "Cat", "Dog"),
+    fac_col9 = c("False", "True")
+  )
+
+  expect_equal(unique_levs, expected)
+
+})
+
+test_that(".set_factor_levels sets levels correctly", {
+  .set_factor_levels("with_new_cols", unique_levs,  ds.test_env$connections)
+
+  expect_equal(
+    ds.levels("with_new_cols$fac_col2") |> map(~.x[[1]]),
+    list(
+      sim1 = c("Blue", "Green", "Red"),
+      sim2 = c("Blue", "Green", "Red"),
+      sim3 = c("Blue", "Green", "Red")
+    )
+  )
+
+  expect_equal(
+    ds.levels("with_new_cols$fac_col3") |> map(~.x[[1]]),
+    list(
+      sim1 = c("No", "Yes"),
+      sim2 = c("No", "Yes"),
+      sim3 = c("No", "Yes")
+    )
+  )
+
+  expect_equal(
+    ds.levels("with_new_cols$fac_col6") |> map(~.x[[1]]),
+    list(
+      sim1 = c("Bird", "Cat", "Dog"),
+      sim2 = c("Bird", "Cat", "Dog"),
+      sim3 = c("Bird", "Cat", "Dog")
+    )
+  )
+
+  expect_equal(
+    ds.levels("with_new_cols$fac_col9") |> map(~.x[[1]]),
+    list(
+      sim1 = c("False", "True"),
+      sim2 = c("False", "True"),
+      sim3 = c("False", "True")
+    )
+  )
+
+})
+
+test_that(".print_var_recode_message prints the correct message", {
+  expect_snapshot(.print_var_recode_message(added_cols, "test_df"))
+})
+
+test_that(".print_class_recode_message prints the correct message", {
+  expect_snapshot(
+    .print_class_recode_message(class_decisions, different_classes, "test_df")
+  )
+})
+
+test_that(".print_levels_recode_message prints the correct message", {
+  expect_snapshot(
+    .print_levels_recode_message(unique_levs, "test_df")
+  )
+})
+
+test_that(".make_levels_recode_message prints the correct message", {
+  expect_equal(
+    .make_levels_recode_message(unique_levs),
+    list(
+      "fac_col2 --> Blue, Green, Red",
+      "fac_col3 --> No, Yes",
+      "fac_col6 --> Bird, Cat, Dog",
+      "fac_col9 --> False, True"
+    )
+  )
+})
+
+test_that(".print_out_messages prints the correct messages", {
+  expect_snapshot(
+    .print_out_messages(
+      added_cols, class_decisions, different_classes, unique_levs, level_conflicts, "1", "test_df"
+    )
+  )
+})
+
+test_that(".change_choice_to_string converts numeric class codes to strings correctly", {
+  expect_equal(.change_choice_to_string("1"), "factor")
+  expect_equal(.change_choice_to_string("2"), "integer")
+  expect_equal(.change_choice_to_string("3"), "numeric")
+  expect_equal(.change_choice_to_string("4"), "character")
+  expect_equal(.change_choice_to_string("5"), "logical")
+})
+
+test_that("ds.standardiseDf doesn't run if dataframes are identical", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+      ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) "1",
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+    )
+
+  expect_error(
+    ds.standardiseDf(
+      df = "test_fill",
+      newobj = "shouldn't_exist"),
+    "Columns are identical"
+    )
+  })
+
+test_that("ds.standardiseDf works when called directly and class conversion is factor", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) "1",
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col4")[[1]],
+    "factor"
+  )
+})
+
+test_that("ds.standardiseDf returns warning when called directly and class conversion is integer", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("2", "2"),
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col4")[[1]],
+    "integer"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col5")[[1]],
+    "integer"
+  )
+})
+
+test_that("ds.standardiseDf returns warning when called directly and class conversion is numeric", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("3", "3"),
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col4")[[1]],
+    "numeric"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col5")[[1]],
+    "numeric"
+  )
+})
+
+test_that("ds.standardiseDf returns warning when called directly and class conversion is character", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("4", "4"),
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col4")[[1]],
+    "character"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col5")[[1]],
+    "character"
+  )
+})
+
+test_that("ds.standardiseDf returns warning when called directly and class conversion is logical", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("5", "5"),
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col4")[[1]],
+    "logical"
+  )
+
+  expect_equal(
+    ds.class("test_fill$fac_col5")[[1]],
+    "logical"
+  )
+})
+
+test_that("ds.standardiseDf changes levels if this option is selected", {
+  with_mocked_bindings(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "test_fill"
+    ),
+    prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("1", "1"),
+    ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "1"
+  )
+
+  levels_2 <- ds.levels("test_fill$fac_col2") %>% map(~.$Levels)
+  levels_3 <- ds.levels("test_fill$fac_col3") %>% map(~.$Levels)
+  levels_4 <- ds.levels("test_fill$fac_col4") %>% map(~.$Levels)
+  levels_5 <- ds.levels("test_fill$fac_col5") %>% map(~.$Levels)
+  levels_6 <- ds.levels("test_fill$fac_col6") %>% map(~.$Levels)
+  levels_9 <- ds.levels("test_fill$fac_col9") %>% map(~.$Levels)
+
+  expect_equal(
+    levels_2,
+    list(
+      sim1 = c("Blue", "Green", "Red"),
+      sim2 = c("Blue", "Green", "Red"),
+      sim3 = c("Blue", "Green", "Red")
+    )
+  )
+
+  expect_equal(
+    levels_3,
+    list(
+      sim1 = c("No", "Yes"),
+      sim2 = c("No", "Yes"),
+      sim3 = c("No", "Yes")
+    )
+  )
+
+  expect_equal(
+    levels_4,
+    list(
+      sim1 = c("1", "2", "3", "A", "B", "C"),
+      sim2 = c("1", "2", "3", "A", "B", "C"),
+      sim3 = c("1", "2", "3", "A", "B", "C")
+    )
+  )
+
+  expect_equal(
+    levels_5,
+    list(
+      sim1 = c("1", "2", "3", "One", "Three", "Two"),
+      sim2 = c("1", "2", "3", "One", "Three", "Two"),
+      sim3 = c("1", "2", "3", "One", "Three", "Two")
+    )
+  )
+
+  expect_equal(
+    levels_6,
+    list(
+      sim1 = c("Bird", "Cat", "Dog"),
+      sim2 = c("Bird", "Cat", "Dog"),
+      sim3 = c("Bird", "Cat", "Dog")
+    )
+  )
+
+  expect_equal(
+    levels_9,
+    list(
+      sim1 = c("False", "True"),
+      sim2 = c("False", "True"),
+      sim3 = c("False", "True")
+    )
+  )
+
+})
+
+test_that("ds.standardiseDf doesn't run if classes are not identical and fix_class is no", {
+  expect_error(
+    ds.standardiseDf(
+      df = "D",
+      newobj = "shouldnt_exist",
+      fix_class = "no"
+    ),
+    "Variables do not have the same class in all studies"
+  )
+
+  expect_equal(
+    ds.exists("shouldnt_exist")[[1]],
+    FALSE
+  )
+})
+
+test_that("ds.standardiseDf doesn't run if levels are not identical and fix_class is no", {
+  expect_error(
+    with_mocked_bindings(
+      ds.standardiseDf(
+        df = "D",
+        newobj = "shouldnt_exist",
+        fix_levels = "no"
+      ),
+      prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) c("1", "1")
+    ),
+    "Factor variables do not have the same levels in all studies"
+  )
+
+  expect_equal(
+    ds.exists("shouldnt_exist")[[1]],
+    FALSE
+  )
+})
+
+test_that("ds.standardiseDf doesn't run if a factor variable has too many levels", {
+  connect.studies.dataset.stand_disclosure(
+    c(
+      "fac_col1", "fac_col2", "fac_col3", "fac_col4", "fac_col5", "fac_col6", "fac_col7", "fac_col9",
+      "fac_col10", "col11", "col12", "col13", "col14", "col15", "col16", "col17", "col18", "col19",
+      "col20")
+  )
+
+  expect_error(
+    with_mocked_bindings(
+      ds.standardiseDf(
+        df = "D",
+        newobj = "test_fill"
+        ),
+      prompt_user_class_decision_all_vars = function(var, server, classes, newobj, datasources) "1",
+      ask_question_wait_response_levels = function(levels_conflict, newobj, datasources) "2"
+      )
+  )
+
+})
+
+disconnect.studies.dataset.stand()
+
+context("ds.standardiseDf::smk::done")