diff --git a/data-raw/ae.R b/data-raw/ae.R
index fb1433f..f49094d 100644
--- a/data-raw/ae.R
+++ b/data-raw/ae.R
@@ -1,14 +1,22 @@
-# from CDISC pilot study ----
+# Datasets: ae, suppae
+# Description: Standard AE, SUPPAE datasets from CDISC pilot study
+
+# Load libraries -----
 library(dplyr)
 library(metatools)
 library(haven)
 library(admiral)
 
+# Create ae, suppae ----
 raw_ae <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/ae.xpt?raw=true") # nolint
 raw_suppae <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/suppae.xpt?raw=true") # nolint
 ae <- convert_blanks_to_na(raw_ae)
 suppae <- convert_blanks_to_na(raw_suppae)
 
-# Save dataset ----
-save(ae, file = "data/ae.rda", compress = "bzip2")
+# Label dataset ----
+attr(ae, "label") <- "Adverse Events"
+attr(suppae, "label") <- "Supplemental Qualifiers for AE"
+
+# Save datasets ----
+usethis::use_data(ae, overwrite = TRUE)
 usethis::use_data(suppae, overwrite = TRUE)
diff --git a/data-raw/ae_ophtha.R b/data-raw/ae_ophtha.R
index c7ddd90..84e9d4c 100644
--- a/data-raw/ae_ophtha.R
+++ b/data-raw/ae_ophtha.R
@@ -1,18 +1,22 @@
-# Update AE by adding AELAT variable for admiralophtha package
+# Dataset: ae_ophtha
+# Description: Add ophtha-specific AELAT variable to existing AE dataset
+
+# Load libraries -----
 library(dplyr)
 library(admiral)
 library(metatools)
 library(haven)
 
+# Create ae_ophtha ----
 # Start from standard AE dataset from this package - this should be
 # in the environment already if devtools::load_all() has been run
 ae_ophtha <- ae
 
-# create possible AELAT values - as collected on CRF ----
+## Create possible AELAT values - as collected on CRF ----
 lat <- c("LEFT", "RIGHT", "BOTH")
 
-# create AELAT variable ----
-# with random assignment of lat values where AESOC is "EYE DISORDERS"
+## Create AELAT variable ----
+# Use random assignment of lat values where AESOC is "EYE DISORDERS"
 # Set seed so that result stays the same for each run
 set.seed(1)
 
@@ -24,7 +28,8 @@ ae_ophtha$AELAT <- if_else(ae_ophtha$AESOC == "EYE DISORDERS",
 ae_ophtha <- ae_ophtha %>%
   add_labels(AELAT = "Laterality")
 
+# Label dataset ----
 attr(ae_ophtha, "label") <- "Adverse Events"
 
 # Save dataset ----
-save(ae_ophtha, file = "data/ae_ophtha.rda", compress = "bzip2")
+usethis::use_data(ae_ophtha, overwrite = TRUE)
diff --git a/data-raw/cm.R b/data-raw/cm.R
index 2657e4e..eef48fe 100644
--- a/data-raw/cm.R
+++ b/data-raw/cm.R
@@ -1,7 +1,16 @@
-# from CDISC pilot study ----
+# Dataset: cm
+# Description: Standard CM dataset from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
+
+# Create cm ----
 raw_cm <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/cm.xpt?raw=true") # nolint
 cm <- convert_blanks_to_na(raw_cm)
 
+# Label dataset ----
+attr(cm, "label") <- "Concomitant Medications"
+
+# Save dataset ----
 usethis::use_data(cm, overwrite = TRUE)
diff --git a/data-raw/dm.R b/data-raw/dm.R
index e35f39f..a109253 100644
--- a/data-raw/dm.R
+++ b/data-raw/dm.R
@@ -1,11 +1,21 @@
-# from CDISC pilot study ----
+# Datasets: dm, suppdm
+# Description: Standard DM, SUPPDM datasets from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
+
+# Create dm, suppdm ----
 sdtm_path <- "https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/" # nolint
 raw_dm <- read_xpt(paste0(sdtm_path, "dm", ".xpt?raw=true"))
 raw_suppdm <- read_xpt(paste0(sdtm_path, "suppdm", ".xpt?raw=true"))
 dm <- convert_blanks_to_na(raw_dm)
 suppdm <- convert_blanks_to_na(raw_suppdm)
 
+# Label dataset ----
+attr(dm, "label") <- "Demographics"
+attr(suppdm, "label") <- "Supplemental Qualifiers for DM"
+
+# Save datasets ----
 usethis::use_data(dm, overwrite = TRUE)
 usethis::use_data(suppdm, overwrite = TRUE)
diff --git a/data-raw/ds.R b/data-raw/ds.R
index 1ba12ea..83c4466 100644
--- a/data-raw/ds.R
+++ b/data-raw/ds.R
@@ -1,5 +1,7 @@
-# Update DS by adding DSDECOD=RANDOMIZED rows
+# Datasets: ds, suppds
+# Description: Standard DS, SUPPDS datasets from CDISC pilot study with added DSDECOD = RANDOMIZED rows
 
+# Load libraries -----
 library(dplyr)
 library(tidyselect)
 library(labelled)
@@ -7,23 +9,26 @@ library(admiral)
 library(metatools)
 library(haven)
 
+# Create ds ----
 data("dm")
 sdtm_path <- "https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/" # nolint
 raw_ds <- read_xpt(paste0(sdtm_path, "ds", ".xpt?raw=true"))
 raw_suppds <- read_xpt(paste0(sdtm_path, "suppds", ".xpt?raw=true"))
 
-# Converting blank to NA
+## Converting blank to NA ----
 dm <- convert_blanks_to_na(dm)
 ds1a <- convert_blanks_to_na(raw_ds)
 suppds1a <- convert_blanks_to_na(raw_suppds)
 
-# Creating full DS data
+## Creating full DS data ----
 ds1a <- ds1a %>%
   mutate(DSSEQ = as.character(DSSEQ))
 ds1 <- combine_supp(ds1a, suppds1a) %>%
   mutate(DSSEQ = as.numeric(DSSEQ))
 
-# Creating RANDOMIZED records
+dsnames <- names(ds1a)
+
+## Creating RANDOMIZED records ----
 dm1 <- select(dm, c(STUDYID, USUBJID, RFSTDTC)) %>%
   filter(!is.na(RFSTDTC)) %>%
   mutate(
@@ -41,7 +46,7 @@ dm1 <- select(dm, c(STUDYID, USUBJID, RFSTDTC)) %>%
 
 ds2 <- bind_rows(ds1, select(dm1, -c(RFSTDTC)))
 
-# Adding labels
+## Adding labels ----
 dslab <- var_label(ds1a)
 var_label(ds2) <- dslab
 
@@ -56,7 +61,15 @@ ds3 <- ds2 %>%
   ) %>%
   ungroup()
 
-# Creating SUPPDS
+ds4 <- ds3 %>%
+  select(all_of(dsnames))
+
+## Label dataset ----
+attr(ds4, "label") <- "Disposition"
+
+ds <- ds4
+
+# Creating SUPPDS ----
 suppds1 <- select(ds3, c("STUDYID", "USUBJID", "DSSEQ", "DOMAIN", "ENTCRIT")) %>%
   filter(!is.na(ENTCRIT))
 
@@ -68,38 +81,28 @@ suppds2 <- rename(suppds1, "RDOMAIN" = "DOMAIN") %>%
     "QNAM" = "ENTCRIT",
     "QLABEL" = "PROTOCOL ENTRY CRITERIA NOT MET",
     "QORIG" = "CRF"
-  )
+  ) %>%
+  select(STUDYID, RDOMAIN, USUBJID, IDVAR, IDVARVAL, QNAM, QLABEL, QVAL, QORIG)
 
-suppds <- select(
-  suppds2,
-  c(
-    STUDYID, RDOMAIN, USUBJID,
-    IDVAR, IDVARVAL, QNAM, QLABEL,
-    QVAL, QORIG
+## Adding labels ----
+suppds3 <- suppds2 %>%
+  add_labels(
+    STUDYID = "Study Identifier",
+    RDOMAIN = "Related Domain Abbreviation",
+    USUBJID = "Unique Subject Identifier",
+    IDVAR = "Identifying Variable",
+    IDVARVAL = "Identifying Variable Value",
+    QNAM = "Qualifier Variable Name",
+    QLABEL = "Qualifier Variable Label",
+    QVAL = "Data Value",
+    QORIG = "Origin"
   )
-)
-
-admiral_suppds <- suppds %>% add_labels(
-  STUDYID = "Study Identifier",
-  RDOMAIN = "Related Domain Abbreviation",
-  USUBJID = "Unique Subject Identifier",
-  IDVAR = "Identifying Variable",
-  IDVARVAL = "Identifying Variable Value",
-  QNAM = "Qualifier Variable Name",
-  QLABEL = "Qualifier Variable Label",
-  QVAL = "Data Value",
-  QORIG = "Origin"
-)
-
-attr(admiral_suppds, "label") <- "Supplemental Disposition"
-
-# Creating DS
-dsnames <- names(ds1a)
-admiral_ds <- select(ds3, all_of(dsnames))
 
-attr(admiral_ds, "label") <- "Disposition"
+## Label dataset ----
+attr(suppds3, "label") <- "Supplemental Qualifiers for DS"
+
+suppds <- suppds3
 
-ds <- admiral_ds
-suppds <- admiral_suppds
-save(ds, file = "data/ds.rda", compress = "bzip2")
-save(suppds, file = "data/suppds.rda", compress = "bzip2")
+# Save datasets ----
+usethis::use_data(ds, overwrite = TRUE)
+usethis::use_data(suppds, overwrite = TRUE)
diff --git a/data-raw/ex.R b/data-raw/ex.R
index 20d31d1..67a2e6f 100644
--- a/data-raw/ex.R
+++ b/data-raw/ex.R
@@ -1,7 +1,16 @@
-# from CDISC pilot study ----
+# Dataset: ex
+# Description: Standard EX dataset from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
+
+# Create ex ----
 raw_ex <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/ex.xpt?raw=true") # nolint
 ex <- convert_blanks_to_na(raw_ex)
 
+# Label dataset ----
+attr(ex, "label") <- "Exposure"
+
+# Save dataset ----
 usethis::use_data(ex, overwrite = TRUE)
diff --git a/data-raw/ex_ophtha.R b/data-raw/ex_ophtha.R
index 7aaeaa2..1321e53 100644
--- a/data-raw/ex_ophtha.R
+++ b/data-raw/ex_ophtha.R
@@ -1,14 +1,20 @@
+# Dataset: ex_ophtha
+# Description: Add ophtha-specific EXLOC, EXLAT variables to existing EX dataset
+# and modify EXROUTE, EXDOSFRM, EXDOSFRQ to something eye-related
+
+# Load libraries -----
 library(dplyr)
 library(tidyselect)
+
+# Make ex_ophtha dataset
 data("dm")
 data("ex")
 
-# Make ex_ophtha dataset
 ex_ophtha <- dm %>%
-  # Start by merging on ophtha_dm to use the SUBJID variable
+  ## Merge on ophtha_dm to use the SUBJID variable ----
   select(USUBJID, SUBJID) %>%
   right_join(ex, by = c("USUBJID"), multiple = "all") %>%
-  # Create EXLOC & EXLAT, change EXROUTE & EXDOSFRM to something eye-related
+  ## Create EXLOC & EXLAT, change EXROUTE & EXDOSFRM ----
   mutate(
     EXLOC = "EYE",
     EXDOSFRM = "INJECTION",
@@ -24,12 +30,15 @@ ex_ophtha <- dm %>%
     "EXENDTC", "EXSTDY", "EXENDY"
   )
 
-# Label new variables
+## Label new variables ----
 attr(ex_ophtha$EXLOC, "label") <- "Location of Dose Administration"
 attr(ex_ophtha$EXLAT, "label") <- "Laterality"
 attr(ex_ophtha$EXROUTE, "label") <- "Route of Administration"
 attr(ex_ophtha$EXDOSFRM, "label") <- "Dose Form"
 attr(ex_ophtha$EXDOSFRQ, "label") <- "Dose Frequency per Interval"
 
-# Save Dataset
-save(ex_ophtha, file = file.path("data", "ex_ophtha.rda"), compress = "bzip2")
+# Label dataset ----
+attr(ex_ophtha, "label") <- "Exposure"
+
+# Save dataset ----
+usethis::use_data(ex_ophtha, overwrite = TRUE)
diff --git a/data-raw/lb.R b/data-raw/lb.R
index 5ceaa66..0317a43 100644
--- a/data-raw/lb.R
+++ b/data-raw/lb.R
@@ -1,19 +1,21 @@
-# Update LB by adding percentage differential lab test rows
+# Dataset: lb
+# Description: Standard LB dataset from CDISC pilot study with added percentage differential lab test rows
 
+# Load libraries -----
 library(dplyr)
 library(haven)
 library(admiral)
 
+# Create LB ----
 sdtm_path <- "https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/" # nolint
 raw_lb <- read_xpt(paste0(sdtm_path, "lb", ".xpt?raw=true"))
-lb <- raw_lb %>% convert_blanks_to_na()
+lb_orig <- raw_lb %>% convert_blanks_to_na()
 
-
-# Subset on differential lab tests
-lb_diff_abs <- lb %>%
+## Subset on differential lab tests ----
+lb_diff_abs <- lb_orig %>%
   filter(LBTESTCD %in% c("BASO", "EOS", "LYM", "MONO", "NEUT"))
 
-# Subset on a few patients and visits
+## Subset on a few patients and visits ----
 subject_sub <- lb_diff_abs %>%
   distinct(USUBJID) %>%
   head()
@@ -24,7 +26,7 @@ lb_sub <- lb_diff_abs %>%
     VISIT %in% c("SCREENING 1", "WEEK 2")
   )
 
-# Create dummy differential lab tests
+## Create dummy differential lab tests ----
 set.seed(1)
 rand_diff <- sample(seq(0, 0.5, by = 0.05), replace = T, nrow(lb_sub))
 
@@ -73,12 +75,13 @@ lb_diff <- lb_sub %>%
   )
 
 
-# Replace original rows with new records
-admiral_lb <- lb %>%
+## Replace original rows with new records ----
+lb <- lb_orig %>%
   anti_join(lb_diff, by = c("USUBJID", "VISIT", "LBSEQ")) %>%
   rbind(lb_diff)
 
-attr(admiral_lb, "label") <- "Laboratory Test Results"
+# Label dataset ----
+attr(lb, "label") <- "Laboratory Test Results"
 
-lb <- admiral_lb
-save(lb, file = "data/lb.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(lb, overwrite = TRUE)
diff --git a/data-raw/mh.R b/data-raw/mh.R
index 456869f..acd9e83 100644
--- a/data-raw/mh.R
+++ b/data-raw/mh.R
@@ -1,24 +1,31 @@
-# Add new variables to MH
+# Dataset: mh
+# Description: Standard MH dataset from CDISC pilot study with variables MENDTC, MHPRESP, MHOCCUR etc
+
+# Load libraries -----
 library(metatools)
 library(lubridate)
 library(haven)
 library(admiral)
 library(dplyr)
 
-data("dm")
+# CReate mh ----
 sdtm_path <- "https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/" # nolint
 raw_mh <- read_xpt(paste0(sdtm_path, "mh", ".xpt?raw=true"))
 
-# Convert blank to NA
+## Get dm ----
+data("dm")
+
+## Convert blank to NA ----
 dm <- convert_blanks_to_na(dm) %>%
   select(STUDYID, USUBJID, RFSTDTC, RFENDTC, RFXSTDTC, RFXENDTC)
-mh <- convert_blanks_to_na(raw_mh)
-# Set seed so that result stays the same for each run
+mh_orig <- convert_blanks_to_na(raw_mh)
+
+## Set seed so that result stays the same for each run ----
 set.seed(1)
 ran_int <- sample.int(400, nrow(raw_mh), replace = TRUE)
 
-
-admiral_mh <- mh %>%
+## Add new variables ----
+mh1 <- mh_orig %>%
   # Add MHENDTC
   mutate(MHENDTC = as.character(as.Date(MHSTDTC) + days(ran_int))) %>%
   # Add MHPRESP
@@ -72,6 +79,9 @@ admiral_mh <- mh %>%
     MHSTAT = "Completion Status"
   )
 
-attr(admiral_mh, "label") <- "Medical History"
-mh <- admiral_mh
-save(mh, file = "data/mh.rda", compress = "bzip2")
+# Label dataset ----
+attr(mh1, "label") <- "Medical History"
+mh <- mh1
+
+# Save dataset ----
+usethis::use_data(mh, overwrite = TRUE)
diff --git a/data-raw/oe_ophtha.R b/data-raw/oe_ophtha.R
index b7e23dd..68bb41f 100644
--- a/data-raw/oe_ophtha.R
+++ b/data-raw/oe_ophtha.R
@@ -1,19 +1,23 @@
-# OE
+# Dataset: oe
+# Description: Create OE test SDTM dataset for ophthalmology studies
 
+# Load libraries -----
 library(dplyr)
 library(metatools)
 library(tidyselect)
 library(admiral)
 
-# Read in data
+# Create OE ----
+
+## Read in data ----
 data("dm")
 data("sv")
 
-# Convert blank to NA
+## Convert blank to NA ----
 dm <- convert_blanks_to_na(dm)
 sv <- convert_blanks_to_na(sv)
 
-# set seed to get same results each run
+## set seed to get same results each run -----
 set.seed(999)
 
 oe1 <- select(sv, c(STUDYID, USUBJID, VISIT, VISITNUM, VISITDY, SVSTDTC)) %>%
@@ -24,7 +28,7 @@ oe2 <- merge(dm, oe1, by = c("STUDYID", "USUBJID"))
 
 oestat <- sample(1:100, nrow(oe2) * 2, replace = TRUE)
 
-# BCVA - Visual Acuity Score
+## BCVA - Visual Acuity Score ----
 oe31 <- bind_rows(
   (oe2 %>% mutate("OELAT" = "LEFT")),
   (oe2 %>% mutate("OELAT" = "RIGHT"))
@@ -40,7 +44,7 @@ oe31 <- bind_rows(
   "OEMETHOD" = "ETDRS EYE CHART"
 )
 
-# DRSS
+## DRSS -----
 oe32 <- bind_rows(
   (oe2 %>% mutate("OELAT" = "LEFT")),
   (oe2 %>% mutate("OELAT" = "RIGHT"))
@@ -58,7 +62,7 @@ oe32 <- bind_rows(
   "OEMETHOD" = "COLOR FUNDUS PHOTOGRAPH"
 )
 
-# IOP
+## IOP -----
 oe33 <- bind_rows(
   (oe2 %>% mutate("OELAT" = "LEFT")),
   (oe2 %>% mutate("OELAT" = "RIGHT"))
@@ -77,7 +81,7 @@ oe33 <- bind_rows(
   "OEMETHOD" = "APPLANATION TONOMETRY"
 )
 
-# CST - Central Subfield Thickness
+## CST - Central Subfield Thickness ----
 oe34 <- bind_rows(
   (oe2 %>% mutate("OELAT" = "LEFT")),
   (oe2 %>% mutate("OELAT" = "RIGHT"))
@@ -97,6 +101,7 @@ oe34 <- bind_rows(
   "OEMETHOD" = "SD-OCT"
 )
 
+## Bind all tests ----
 oe4 <- bind_rows(oe31, oe32, oe33, oe34) %>%
   arrange(STUDYID, USUBJID, VISITNUM, OEDTC, OETESTCD, OELAT) %>%
   group_by(STUDYID, USUBJID) %>%
@@ -108,6 +113,7 @@ oe4 <- bind_rows(oe31, oe32, oe33, oe34) %>%
     "OETPTNUM" = NA
   )
 
+## Select columns and add labels -----
 oe_ophtha <- oe4 %>%
   select(
     STUDYID, DOMAIN, USUBJID, OESEQ, OECAT, OESCAT, OEDTC, VISIT, VISITNUM, VISITDY,
@@ -144,5 +150,5 @@ oe_ophtha <- oe4 %>%
 
 attr(oe_ophtha, "label") <- "Ophthalmic Examinations"
 
-
-save(oe_ophtha, file = "data/oe_ophtha.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(oe_ophtha, overwrite = TRUE)
diff --git a/data-raw/pc.R b/data-raw/pc.R
index 4b7cd6c..413d630 100644
--- a/data-raw/pc.R
+++ b/data-raw/pc.R
@@ -1,25 +1,29 @@
-library(haven) # Load xpt
+# Dataset: PC
+# Description: Create PC test SDTM dataset
+
+# Load libraries ----
+library(haven)
 library(plyr)
-library(dplyr) # apply distincts
+library(dplyr)
 library(lubridate)
 library(labelled)
 library(admiral)
 
+# Create pc ----
 data("ex")
 data("dm")
 
-# set seed to get same results each run
+## set seed to get same results each run ----
 set.seed(999)
 
-# Remove screen failures, they will not make it to drug infusion
+## Remove screen failures, they will not make it to drug infusion ----
 dm1 <- dm %>%
   filter(ARMCD != "Scrnfail")
 
-# use subjects in both datasets (ex,dm1) to create pc
+## use subjects in both datasets (ex,dm1) to create pc ----
 dmex <- merge(dm1[, c(1, 3)], ex, by = c("STUDYID", "USUBJID"))
 
-# I'm going to calculate only PC on Baseline,
-# so going to filter only visit = BASELINE
+## Calculate only PC on Baseline, so filter only visit = BASELINE ----
 dmex1 <- dmex %>%
   filter(VISIT == "BASELINE")
 
@@ -39,7 +43,7 @@ noise <- runif(n = nrows, min = -0.05, max = 0.05)
 dmex1$K <- 0.7 + noise
 dmex1$V <- dmex1$EXDOSE / (dmex1$K)
 
-# init dataset
+## Start setting up dataset
 PC <- NULL
 for (t0 in t) {
   dmex1$t <- t0
@@ -68,7 +72,7 @@ for (t0 in t) {
   }
 }
 
-# Constant var
+## Constant vars ----
 PC$DOMAIN <- "PC"
 PC$PCTESTCD <- "XAN"
 PC$PCTEST <- "XANOMELINE"
@@ -79,36 +83,36 @@ PC$PCSPEC <- "PLASMA"
 PC$PCLLOQ <- 0.01
 PC$PCTPTNUM <- PC$t
 
-# PCSEQ;
+## PCSEQ; ----
 PC <- PC %>%
   group_by(STUDYID, USUBJID) %>%
   dplyr::mutate(PCSEQ = row_number())
 
-# Concentration related
-# Remove neg values due to pre-dose negative time
+## Concentration-related code ----
+### Remove neg values due to pre-dose negative time ----
 PC$Conc <- ifelse(PC$Conc < 0, 0, PC$Conc)
 
-
 PC$PCSTRESN <- PC$Conc
 
-# Usually as per SAP, only predose BLQ can be set to 0
+## Usually as per SAP, only predose BLQ can be set to 0 ----
 PC$PCSTRESN <- ifelse(PC$PCSTRESN < 0.01 & PC$t == -0.5, 0, PC$PCSTRESN)
 
 # otherwise set it to missing
 PC$PCSTRESN <- ifelse(PC$PCSTRESN < 0.01 & PC$t != -0.5, NA, PC$PCSTRESN)
 
-# set blqs if NA
+## set blqs if NA ----
 PC$Conc <- ifelse(PC$Conc < 0.01, "<BLQ", PC$Conc)
 PC$PCORRES <- PC$Conc
 PC$PCSTRESC <- PC$Conc
 
-# Probably can be done throw factors
+## PCTPT ----
 PC$PCTPT <- ifelse(PC$PCTPTNUM == -0.5, "Pre-dose",
   ifelse(PC$PCTPTNUM == 0.08, "5 Min Post-dose",
     ifelse(PC$PCTPTNUM == 0.5, "30 Min Post-dose", paste0(PC$PCTPTNUM, "h Post-dose"))
   )
 )
 
+## PCDTC ----
 PC$PCDTC <- format(as.Date(PC$EXSTDTC) + minutes(round(PC$t * 60)), "%Y-%m-%dT%H:%M:%S")
 PC$PCDY <- ifelse(PC$t == -0.5, -1,
   ifelse(PC$t == 48, 3,
@@ -116,16 +120,19 @@ PC$PCDY <- ifelse(PC$t == -0.5, -1,
   )
 )
 
+## Select vars of interest ----
 PC <- subset(PC, select = c(
   "STUDYID", "DOMAIN", "USUBJID", "PCSEQ", "PCTESTCD", "PCTEST",
   "PCORRES", "PCORRESU", "PCSTRESC", "PCSTRESN", "PCSTRESU",
   "PCNAM", "PCSPEC", "PCLLOQ", "VISIT", "VISITNUM", "PCDTC", "PCDY", "PCTPT", "PCTPTNUM"
 ))
+
+## Ungroup and sort ----
 pc <- PC %>%
   ungroup() %>%
   arrange(STUDYID, USUBJID, PCSEQ)
 
-# add labels
+## add labels ----
 pc <- pc %>%
   set_variable_labels(
     STUDYID = "Study Identifier",
@@ -150,7 +157,13 @@ pc <- pc %>%
     PCTPTNUM = "Planned Time Point Number"
   )
 
+## Test to look the overall figure ----
+plot <- ggplot(pc, aes(x = PCTPTNUM, y = PCSTRESN, group = USUBJID)) +
+  geom_line() +
+  geom_point()
 
+# Label dataset ----
+attr(pc, "label") <- "Pharmacokinetics Concentrations"
 
-# ---- Save output ----
-save(pc, file = "data/pc.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(pc, overwrite = TRUE)
diff --git a/data-raw/pp.R b/data-raw/pp.R
index c75c5f6..ed8ff7d 100644
--- a/data-raw/pp.R
+++ b/data-raw/pp.R
@@ -1,29 +1,34 @@
-library(haven) # Load xpt
-library(dplyr) # apply distincts
+# Dataset: PP
+# Description: Create PP test SDTM dataset
+
+# Load libraries ----
+library(haven)
+library(dplyr)
 library(lubridate)
 library(labelled)
 library(admiral)
 
+# Create pc ----
 data("pc")
 
-# Calculate subjects with all missing;
+## Calculate subjects with all missing ----
 blq_usubjid <- pc %>%
   ungroup() %>%
   group_by(STUDYID, DOMAIN, USUBJID) %>%
   summarise(PPORRES = max(PCSTRESN, na.rm = TRUE))
 
-# Remove from PC, subjects with all blq (placebos);
+## Remove from PC, subjects with all blq (placebos) ----
 remove_usubjid <- blq_usubjid %>% filter(PPORRES == 0)
 
 pc1 <- anti_join(pc, remove_usubjid, by = c("STUDYID", "DOMAIN", "USUBJID"))
 
 # PP usually only present values for applicable subjects;
-# Calculate Cmax;
+## Calculate Cmax ----
 pp_cmax <- pc1 %>%
   group_by(STUDYID, DOMAIN, USUBJID) %>%
   summarise(CMAX = max(PCSTRESN, na.rm = TRUE))
 
-# Calculate Tmax
+## Calculate Tmax ----
 pp_tmax <- pc1 %>%
   group_by(STUDYID, DOMAIN, USUBJID) %>%
   filter(PCSTRESN == max(PCSTRESN, na.rm = TRUE)) %>%
@@ -31,7 +36,7 @@ pp_tmax <- pc1 %>%
 pp_tmax$TMAX <- pp_tmax$PCTPTNUM
 pp_tmax <- subset(pp_tmax, select = c("STUDYID", "DOMAIN", "USUBJID", "TMAX"))
 
-# AUC 0_tlast
+## AUC 0_tlast ----
 pc2 <- pc1
 pc2$PCTPTNUM <- ifelse(pc1$PCTPTNUM == -0.5, 0, pc1$PCTPTNUM)
 pc2 <- pc2 %>%
@@ -60,7 +65,7 @@ pp_npts <- pc3 %>%
   group_by(STUDYID, DOMAIN, USUBJID) %>%
   summarise(npts = n())
 
-# Break up pc3 by usubjid, then fit the specified model to each piece and
+## Break up pc3 by usubjid, then fit the specified model to each piece ----
 # return a list
 models <- plyr::dlply(pc3, c("STUDYID", "DOMAIN", "USUBJID"), function(df) {
   lm(-log(PCSTRESN, base = exp(1)) ~ PCTPTNUM, data = df)
@@ -73,12 +78,12 @@ pp_Ke$Ke <- pp_Ke$PCTPTNUM
 pp_Ke <- subset(pp_Ke, select = c("STUDYID", "DOMAIN", "USUBJID", "Ke"))
 
 
-# Halflife
+## Halflife ----
 pp_lambda <- pp_Ke
 pp_lambda$lambda <- 0.693 / pp_lambda$Ke
 pp_lambda <- subset(pp_lambda, select = c("STUDYID", "DOMAIN", "USUBJID", "lambda"))
 
-# AUC_0_inf
+## AUC_0_inf ----
 pc4 <- pc3 %>%
   group_by(STUDYID, DOMAIN, USUBJID) %>%
   mutate(min = min(PCSTRESN, na.rm = TRUE))
@@ -93,8 +98,7 @@ pp_AUC_inf <- merge(pc5, pp_AUC, by = c("STUDYID", "DOMAIN", "USUBJID"))
 pp_AUC_inf$AUC_inf <- pp_AUC_inf$AUC + (pp_AUC_inf$min) / pp_AUC_inf$Ke
 pp_AUC_inf <- subset(pp_AUC_inf, select = c("STUDYID", "DOMAIN", "USUBJID", "AUC_inf"))
 
-# Add all require variables
-
+## Add all require variables -----
 pp_AUC$PPTESTCD <- "AUCLST"
 pp_AUC$PPTEST <- "AUC to Last Nonzero Conc"
 pp_AUC$PPORRESU <- "h*ug/ml"
@@ -136,7 +140,7 @@ pp_tmax$PPORRESU <- "h"
 pp_tmax$PPORRES <- pp_tmax$TMAX
 # R2ADJ	C85553	R Squared Adjusted
 
-# Join all data
+## Join all data ----
 PP <- bind_rows(pp_tmax, pp_npts, pp_lambda, pp_Ke, pp_cmax, pp_Clast, pp_AUC, pp_AUC_inf)
 
 # Constant variables
@@ -147,35 +151,36 @@ PP$PPSTRESU <- PP$PPORRESU
 PP$PPSPEC <- "PLASMA"
 PP$DOMAIN <- "PP"
 
-# Sort
+## Sort ----
 pp <- PP %>%
   arrange(STUDYID, USUBJID, PPTESTCD)
 
-# PPSEQ;
+## PPSEQ ----
 pp <- pp %>%
   group_by(STUDYID, USUBJID) %>%
   mutate(PPSEQ = row_number())
 
-# Load ex to add the reference time (EXSTDTC)
+## Load ex to add the reference time (EXSTDTC) ----
 data("ex")
 
-# we only used baseline
+## Only use baseline ----
 ex1 <- ex %>%
   filter(VISIT == "BASELINE")
 
-# Select needed vars
+## Select needed exvars ----
 ex2 <- subset(ex1, select = c("STUDYID", "USUBJID", "EXSTDTC"))
 
-# merge
+## Merge pp and ex ----
 pp <- merge(pp, ex2, by = c("STUDYID", "USUBJID"))
 pp$PPRFDTC <- pp$EXSTDTC
 
+## Subset pp vars -----
 pp <- subset(pp, select = c(
   "STUDYID", "DOMAIN", "USUBJID", "PPSEQ", "PPTESTCD", "PPTEST", "PPCAT",
   "PPORRES", "PPORRESU", "PPSTRESC", "PPSTRESN", "PPSTRESU", "PPSPEC", "PPRFDTC"
 ))
 
-# add labels
+# Label pp ----
 pp <- pp %>%
   set_variable_labels(
     STUDYID = "Study Identifier",
@@ -194,7 +199,8 @@ pp <- pp %>%
     PPRFDTC = "Date/Time of Reference Point"
   )
 
+# Label dataset ----
+attr(pp, "label") <- "Pharmacokinetics Parameters"
 
-
-# ---- Save output ----
-save(pp, file = "data/pp.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(pp, overwrite = TRUE)
diff --git a/data-raw/qs_ophtha.R b/data-raw/qs_ophtha.R
index d24df94..be4cea6 100644
--- a/data-raw/qs_ophtha.R
+++ b/data-raw/qs_ophtha.R
@@ -1,21 +1,23 @@
+# Dataset: qs
+# Description: Create QS test SDTM dataset with VFQ records for ophthalmology studies
+
+# Load libraries -----
 library(dplyr)
 library(stringr)
 library(metatools)
 library(haven)
 library(admiral)
 
-
-# from CDISC pilot study ----
+# Create qs_ophtha ----
+## Get qs from CDISC pilot study ----
 sdtm_path <- "https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/" # nolint
 raw_qs <- read_xpt(paste0(sdtm_path, "qs", ".xpt?raw=true")) %>%
   convert_blanks_to_na()
 
-
-# set seed to get same results each run
+## set seed to get same results each run ----
 set.seed(999)
 
-# add vfq data
-# create new QS data - keep standard variables from previous ADMIRAL project's QS ====
+## add VFQ data ----
 qs1 <- raw_qs %>%
   # select standard variables
   select(STUDYID, DOMAIN, USUBJID, QSBLFL, VISITNUM, VISIT, VISITDY, QSDTC, QSDY) %>%
@@ -23,7 +25,7 @@ qs1 <- raw_qs %>%
   group_by(USUBJID, VISITDY) %>%
   unique()
 
-# create dummy parameters and results ====
+#### create dummy parameters and results ----
 dummy_param <- data.frame(QSTEST = c(
   "Your Overall Health Is",
   "Eyesight Using Both Eyes Is",
@@ -61,7 +63,7 @@ dummy_param <- data.frame(QSTEST = c(
     QSSCAT = "Original Response"
   )
 
-# dummy answers
+### dummy answers ----
 
 # difficulty in performing tasks
 difficulty_res <- c(
@@ -90,7 +92,7 @@ yesno <- setNames(yn_res, yn_resn)
 answers <- c(difficulty_res, freq_res, qual_res, yn_res)
 answersn <- c(difficulty_resn, freq_resn, qual_resn, yn_resn)
 
-# assign answers to questions randomly for each subjects
+### assign answers to questions randomly for each subjects ----
 
 # take unique subjects
 subjects <- qs1 %>%
@@ -114,7 +116,7 @@ dummy_param_res_by_subj <- merge(subjects, dummy_param) %>%
     QSDRVFL = ""
   )
 
-# merge standard QS with parameters and result variables from temp QS data
+### Merge standard QS with parameters and result variables from ophtha QS data ----
 
 qs2 <- merge(qs1, dummy_param_res_by_subj, by = "USUBJID") %>%
   group_by(USUBJID) %>%
@@ -132,14 +134,12 @@ qs3 <- qs2 %>%
   ) %>%
   ungroup()
 
-# NOTE: the QS2 dataset made above should be stacked below the qs dataset.
-# output qs_ophtha.RDS
-# remove the original vfq part from admiral_qs
-admiral_qs_novfq <- raw_qs %>% filter(QSCAT != "NEI VFQ-25")
+## Keep only VFQ records ----
+qs_novfq <- raw_qs %>% filter(QSCAT != "NEI VFQ-25")
 
-qs_ophtha1 <- rbind(admiral_qs_novfq, qs3)
+qs_ophtha1 <- rbind(qs_novfq, qs3)
 
-# --SEQ and keep relevant variables;
+## xxSEQ and keep relevant variables ----
 qs_ophtha2 <- qs_ophtha1 %>%
   select(-QSSEQ) %>%
   arrange(STUDYID, USUBJID, QSCAT, QSTESTCD, QSDTC, VISITNUM)
@@ -155,9 +155,8 @@ qs_ophtha3 <- qs_ophtha2 %>%
 
 qs_ophtha <- qs_ophtha3
 
-# assign dataset label
+# Assign dataset label ----
 attr(qs_ophtha, "label") <- "Questionnaires"
 
-# ---- Save output for temporary usage ----
-# save(qs_ophtha, file = "data/qs_ophtha.rda", compress = "bzip2")
+# Save dataset ----
 usethis::use_data(qs_ophtha, overwrite = TRUE)
diff --git a/data-raw/query_databases.R b/data-raw/query_databases.R
index 8b99388..2f61e61 100644
--- a/data-raw/query_databases.R
+++ b/data-raw/query_databases.R
@@ -1,5 +1,10 @@
+# Dataset: sdg_db, smq_db
+# Description: Create example SDG, SMQ dataset
+
+# Load libraries ----
 library(dplyr)
 
+# Create smq dataset ----
 pregsmq <- tribble(
   ~termname, ~scope,
   "Achromotrichia congenital", "narrow",
@@ -65,9 +70,13 @@ smq_db <- bind_rows(pregsmq, bilismq) %>%
     termvar = "AEDECOD"
   )
 
-# admiral_smq_db <- smq_db
-save(smq_db, file = "data/smq_db.rda", compress = "bzip2")
+# Label dataset ----
+attr(smq_db, "label") <- "SMQ"
+
+# Save smq dataset ----
+usethis::use_data(smq_db, overwrite = TRUE)
 
+# Create sdg dataset ----
 sdg_db <- tribble(
   ~termname,
   "AMINOSALICYLIC ACID",
@@ -94,4 +103,8 @@ sdg_db <- tribble(
     version = "2019-09"
   )
 
-save(sdg_db, file = "data/sdg_db.rda", compress = "bzip2")
+# Label dataset ----
+attr(sdg_db, "label") <- "SDG"
+
+# Save sdg dataset ----
+usethis::use_data(sdg_db, overwrite = TRUE)
diff --git a/data-raw/rs_onco.R b/data-raw/rs_onco.R
index dae7c64..2a64bf8 100644
--- a/data-raw/rs_onco.R
+++ b/data-raw/rs_onco.R
@@ -1,15 +1,20 @@
-# RS
-# Please note that tr.R should run first
+# Dataset: rs
+# Description: RS test SDTM dataset for Oncology studies
 
+# Please note that tr_onco.R should run first
+
+# Load libraries -----
 library(dplyr)
 library(tidyselect)
 library(admiral)
 library(metatools)
 
-# Reading input data
+# Create rs ----
+
+## Read input data ----
 data("tr_onco")
 
-# Converting blank to NA
+## Convert blank to NA ----
 tr <- convert_blanks_to_na(tr_onco)
 
 keyvar <- c(
@@ -17,7 +22,7 @@ keyvar <- c(
   "TRDTC", "VISIT", "VISITNUM", "TRDY", "TRACPTFL"
 )
 
-# Deriving PCHG
+## Derive PCHG ----
 sumdiam1 <- tr %>%
   filter(TRTESTCD == "SUMDIAM") %>%
   select(., c(all_of(keyvar), TRLNKGRP, TRSTRESN, TRSTAT, TRREASND))
@@ -32,7 +37,7 @@ sumdiam <- left_join(sumdiam1, sumb,
 ) %>%
   mutate("PCHG" = (TRSTRESN - BASE) * 100 / BASE)
 
-# Dummy Data Nadir Not Used In PD Derivation (>5 mm and 20% increase from nadir)
+## Dummy Data Nadir Not Used In PD Derivation (>5 mm and 20% increase from nadir) ----
 trgresp <- sumdiam %>% mutate(
   "TRGRESP" = case_when(
     !is.na(PCHG) & PCHG <= -100 ~ "CR",
@@ -46,7 +51,7 @@ trgresp <- sumdiam %>% mutate(
   "TRTESTCD" = "TRGRESP"
 )
 
-# Select Non-target Response Per Visit
+## Select Non-target Response Per Visit ----
 ntar <- tr %>%
   filter(TRTESTCD == "TUMSTATE" & TRGRPID == "NON-TARGET") %>%
   select(., c(all_of(keyvar), TRORRES, TRREASND)) %>%
@@ -73,7 +78,7 @@ ntrgresp <- ntar %>% mutate(
   "TRTESTCD" = "NTRGRESP"
 )
 
-# Select New Lesions Per Visit
+## Select New Lesions Per Visit ----
 nle <- tr %>%
   filter(TRTESTCD == "TUMSTATE" & TRGRPID == "NEW") %>%
   select(., c(all_of(keyvar), TRORRES)) %>%
@@ -93,11 +98,11 @@ newlprog <- nle %>% mutate(
   "TRTESTCD" = "NEWLPROG"
 )
 
-# Merging All Visit Level Data
+## Merge  All Visit Level Data ----
 rs1 <- full_join(trgresp, ntrgresp, by = c(all_of(keyvar)))
 rs2 <- full_join(rs1, newlprog, by = c(all_of(keyvar)))
 
-# Deriving Overall Response
+## Derive Overall Response ----
 ovrlresp <- rs2 %>%
   filter(VISITNUM > 3) %>%
   mutate(
@@ -132,7 +137,7 @@ ovrlresp <- rs2 %>%
     )
   )
 
-# Setting All Data And Adding Other Variables
+## Set All Data And Add Other Variables ----
 rs5 <- bind_rows(
   select(trgresp, c(all_of(keyvar), "TRREASND", "TRTESTCD", "TRGRESP"))
   %>% rename("RSORRES" = "TRGRESP"),
@@ -170,7 +175,7 @@ rs5 <- bind_rows(
     "RSSTAT" = case_when(!is.na(RSREASND) ~ "NOT DONE")
   )
 
-# RSSEQ
+## RSSEQ ----
 rs6 <- rs5 %>%
   arrange(
     STUDYID, USUBJID, VISITNUM, RSDTC,
@@ -180,7 +185,7 @@ rs6 <- rs5 %>%
   mutate(RSSEQ = row_number()) %>%
   ungroup()
 
-# Creating RS
+## Create labels and final dataset ----
 rs <- select(rs6, c(
   STUDYID, DOMAIN, USUBJID, RSSEQ, RSLNKGRP, RSTESTCD,
   RSTEST, RSCAT, RSORRES, RSSTRESC,
@@ -210,6 +215,8 @@ rs_onco <- rs %>% add_labels(
   RSDY = "Study Day of Response Assessment"
 )
 
-attr(rs_onco, "label") <- "Disease Response"
+# Label dataset ----
+attr(rs_onco, "label") <- "Disease Response and Clin Classification"
 
-save(rs_onco, file = "data/rs_onco.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(rs_onco, overwrite = TRUE)
diff --git a/data-raw/sc_ophtha.R b/data-raw/sc_ophtha.R
index 5c11f9c..f2d599e 100644
--- a/data-raw/sc_ophtha.R
+++ b/data-raw/sc_ophtha.R
@@ -1,24 +1,26 @@
-# SC (ophthalmology)
+# Dataset: sc
+# Description: Create SC test SDTM dataset for ophthalmology studies
 
+# Load libraries -----
 library(dplyr)
 library(metatools)
 
+# Create sc ----
+## Load required datasets ----
 data("dm")
 data("sv")
 
-
-# Remove screen failures, they will not make it to drug infusion
+## Remove screen failures, they will not make it to drug infusion ---
 dm1 <- dm %>%
   filter(ARMCD != "Scrnfail")
 
-
-# Use subjects in DM  and info from SV  Screening 1 visit
+## Use subjects in DM  and info from SV Screening 1 visit ---
 sc <- merge(dm1[, c("STUDYID", "USUBJID", "SUBJID", "RFSTDTC")],
   sv[sv$VISIT == "SCREENING 1", c("STUDYID", "USUBJID", "SVSTDTC", "VISIT")],
   by = c("STUDYID", "USUBJID")
 )
 
-# Create SC domain var
+## Create SC domain vars ----
 sc$DOMAIN <- "SC"
 sc$SCCAT <- "STUDY EYE SELECTION"
 sc$SCTESTCD <- "FOCID"
@@ -30,8 +32,7 @@ sc$SCDY <- as.numeric(as.Date(sc$SCDTC) - as.Date(sc$RFSTDTC))
 sc$SCORRES <- if_else(as.integer(sc$SUBJID) %% 2 == 0, "Left Eye", "Right Eye")
 sc$SCSTRESC <- if_else(as.integer(sc$SUBJID) %% 2 == 0, "OS", "OD")
 
-
-# SCSEQ and keep relevant variables;
+## Create SCSEQ and keep relevant variables ----
 sc_seq <- sc %>%
   group_by(STUDYID, USUBJID) %>%
   mutate(SCSEQ = row_number()) %>%
@@ -40,6 +41,7 @@ sc_seq <- sc %>%
     "SCCAT", "SCORRES", "SCSTRESC", "EPOCH", "SCDTC", "SCDY"
   )
 
+## Sort and variable labels -----
 sc_ophtha <- sc_seq %>%
   ungroup() %>%
   # Sort data
@@ -60,9 +62,8 @@ sc_ophtha <- sc_seq %>%
     SCDY = "Study Day of Examination"
   )
 
-
-# assign dataset label
+# Dataset label ----
 attr(sc_ophtha, "label") <- "Subject Characteristic"
 
-# Save output
-save(sc_ophtha, file = "data/sc_ophtha.rda", compress = "bzip2")
+# Save dataset
+usethis::use_data(sc_ophtha, overwrite = TRUE)
diff --git a/data-raw/sv.R b/data-raw/sv.R
index 8313e0c..3a40165 100644
--- a/data-raw/sv.R
+++ b/data-raw/sv.R
@@ -1,7 +1,14 @@
-# from CDISC pilot study ----
+# Dataset: sv
+# Description: StandardSV dataset from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
 raw_sv <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/sv.xpt?raw=true") # nolint
 sv <- convert_blanks_to_na(raw_sv)
 
+# Label dataset ----
+attr(sv, "label") <- "Subject Visits"
+
+# Save dataset ----
 usethis::use_data(sv, overwrite = TRUE)
diff --git a/data-raw/tr_onco.R b/data-raw/tr_onco.R
index 1028fb4..44036b4 100644
--- a/data-raw/tr_onco.R
+++ b/data-raw/tr_onco.R
@@ -1,24 +1,29 @@
-# TR
+# Dataset: tr, supptr
+# Description: TR, SUPPTR test SDTM datasets for Oncology studies
 
+# Load libraries ----
 library(dplyr)
 library(tidyselect)
 library(metatools)
 library(admiral)
 library(metatools)
 
+# Create tr ----
+
+## Set seed to obtain reproducible results -----
 set.seed(1)
 
-# Reading input data ----
+## Read input data ----
 data("dm")
 data("suppdm")
 data("sv")
 
-# Converting blank to NA
+## Converting blank to NA ----
 dm <- convert_blanks_to_na(dm)
 suppdm <- convert_blanks_to_na(suppdm)
 sv <- convert_blanks_to_na(sv)
 
-# Creating data frame with visits ----
+## Create data frame with visits ----
 dm1 <- dm %>%
   combine_supp(suppdm)
 
@@ -30,7 +35,7 @@ tr1 <- select(sv, c(STUDYID, USUBJID, VISIT, VISITNUM, VISITDY, SVSTDTC)) %>%
 
 tr2 <- merge(dm2, tr1, by = c("STUDYID", "USUBJID"))
 
-# Creating dummy tumors ----
+## Create dummy tumors ----
 trloc <- c(
   "ABDOMINAL CAVITY", "ADRENAL GLAND", "LYMPH NODE", "BLADDER",
   "BODY", "BONE", "BREAST", "CHEST", "COLON",
@@ -44,13 +49,12 @@ trloc <- c(
 ttyped <- as.data.frame(trloc) %>% rename("TRLOC" = "trloc")
 ttyped$tar1 <- as.double(row.names(ttyped))
 
-# Adding records for TARGET, NON-TARGET and NEW LESIONS and
-# Selecting Tumor Locations Randomly
+## Add records for TARGET, NON-TARGET and NEW LESIONS and Select Tumor Locations Randomly ----
 nrows <- dim(tr2)[1]
 tar <- floor(runif(n = nrows, min = 1, max = 5))
 new <- floor(runif(n = nrows, min = 21, max = 22))
 
-# Target Tumors
+## Target Tumors ----
 tr3a <- bind_rows(
   (tr2 %>% mutate("tar1" = tar, "TRLNKID" = "T01")),
   (tr2 %>% mutate("tar1" = tar + 1, "TRLNKID" = "T02")),
@@ -95,7 +99,7 @@ tr3c <- bind_rows(
 tr3 <- bind_rows(tr3a, tr3b, tr3c) %>%
   left_join(ttyped, by = "tar1")
 
-# Adding Diameter Values Randomly ----
+## Adding Diameter Values Randomly ----
 trows <- dim(tr3)[1]
 diam <- floor((runif(n = trows, min = 5, max = 15)))
 
@@ -105,7 +109,7 @@ tr3 <- tr3 %>%
     SUBJNO = as.numeric(substr(USUBJID, 8, 12))
   )
 
-# Modifying Diameter Values To Get Some CR And NE In Target Response Data
+## Modifying Diameter Values To Get Some CR And NE In Target Response Data ----
 tr3 <- tr3 %>% mutate(
   "TRSTRESN" = case_when(
     floor(SUBJNO %% 5) == 0 & VISITNUM %in% c(9, 10.1) ~ 0,
@@ -127,7 +131,7 @@ tr3 <- tr3 %>% mutate(
   "TRTEST" = "Diameter"
 )
 
-# Adding LDIAM and LPERP ----
+## Adding LDIAM and LPERP ----
 tr3ldiam <- tr3 %>% mutate(
   TRSTRESN = if_else(
     TRLOC == "LYMPH NODE",
@@ -152,7 +156,7 @@ tr3lperp <- tr3 %>% mutate(
   TRTEST = "Longest Perpendicular"
 )
 
-# SUMDIAM ----
+## SUMDIAM ----
 tr3sum <- tr3 %>%
   group_by(
     STUDYID, USUBJID, VISITNUM, VISIT, TREVAL,
@@ -167,8 +171,7 @@ tr3sum <- tr3 %>%
     "TRSTRESC" = TRORRES
   )
 
-# Non-target Tumors ----
-
+## Non-target Tumors ----
 ntar <- floor(runif(n = nrows, min = 11, max = 15))
 ntr3a <- bind_rows(
   (tr2 %>% mutate("tar1" = ntar, "TRLNKID" = "NT01")),
@@ -207,7 +210,7 @@ ntr3c <- bind_rows(
 
 ntr3 <- bind_rows(ntr3a, ntr3b, ntr3c)
 
-# Adding Non Target Result Values Randomly
+## Adding Non Target Result Values Randomly ----
 ntrorresf <- c("NOT", "UNEQUIVOCAL", "ABSENT", "PRESENT")
 
 ntrespd <- tibble::tibble(ntrorresf)
@@ -231,14 +234,14 @@ ntr3 <- merge(ntr3, ntrespd, by = "ntresn") %>%
     "SUBJNO" = as.numeric(substr(USUBJID, 8, 12))
   )
 
-# Modifying Non-target Values To Get Some CR In Data
+## Modifying Non-target Values To Get Some CR In Data ----
 ntr3 <- ntr3 %>% mutate(
   "TRORRES" = ifelse(floor(SUBJNO %% 5) == 0 &
     VISITNUM %in% c(9, 10.1), "ABSENT", TRORRES),
   "TRSTRESC" = TRORRES
 )
 
-# New Lesions - assigning new lesions only on last visit
+## New Lesions - assigning new lesions only on last visit ----
 new <- floor(runif(n = nrows, min = 21, max = 22))
 new3a <- tr2 %>% mutate(
   "tar1" = new,
@@ -279,7 +282,7 @@ new3 <- bind_rows(new3a, new3b, new3c) %>%
   ) %>%
   filter(VISITNUM > 3 & (TRORRES != "NO"))
 
-# Setting All Tumor Data ----
+## Setting All Tumor Data ----
 tr <- bind_rows(
   tr3 %>% filter(EFFICACY == "Y" | (SAFETY == "Y" & VISITNUM == 3)),
   tr3ldiam %>% filter(EFFICACY == "Y" | (SAFETY == "Y" & VISITNUM == 3)),
@@ -296,7 +299,7 @@ tr <- bind_rows(
     VISITNUM == 12 ~ "A4"
   ))
 
-# TRSEQ and Other Variables ----
+## TRSEQ and Other Variables ----
 tr <- tr %>%
   arrange(STUDYID, USUBJID, VISITNUM, TRDTC, TRGRPID, TRLNKID) %>%
   group_by(STUDYID, USUBJID) %>%
@@ -354,9 +357,9 @@ supptr_onco <- supptr %>% add_labels(
   QORIG = "Origin"
 )
 
-attr(supptr_onco, "label") <- "Supplemental Tumor Results"
+attr(supptr_onco, "label") <- "Supplemental Qualifiers for TR"
 
-# Creating TR ----
+# Create final TR dataset ----
 tr <- select(tr, c(
   STUDYID, DOMAIN, USUBJID, TRSEQ, TRGRPID, TRLNKGRP,
   TRLNKID, TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESC,
@@ -391,8 +394,9 @@ tr_onco <- tr %>% add_labels(
   TRDY = "Study Day of Tumor Measurement"
 )
 
-attr(tr_onco, "label") <- "Tumor Results"
-
+# Label TR dataset ----
+attr(tr_onco, "label") <- "Tumor/Lesion Results"
 
-save(tr_onco, file = "data/tr_onco.rda", compress = "bzip2")
-save(supptr_onco, file = "data/supptr_onco.rda", compress = "bzip2")
+# Save datasets ----
+usethis::use_data(tr_onco, overwrite = TRUE)
+usethis::use_data(supptr_onco, overwrite = TRUE)
diff --git a/data-raw/ts.R b/data-raw/ts.R
index 284414e..ecd41ad 100644
--- a/data-raw/ts.R
+++ b/data-raw/ts.R
@@ -1,7 +1,14 @@
-# from CDISC pilot study ----
+# Datasets: ts
+# Description: Standard TS dataset from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
 raw_ts <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/ts.xpt?raw=true") # nolint
 ts <- convert_blanks_to_na(raw_ts)
 
+# Label dataset ----
+attr(ts, "label") <- "Trial Summary Information"
+
+# Save dataset -----
 usethis::use_data(ts, overwrite = TRUE)
diff --git a/data-raw/tu_onco.R b/data-raw/tu_onco.R
index 6eaeb4e..719c9c9 100644
--- a/data-raw/tu_onco.R
+++ b/data-raw/tu_onco.R
@@ -1,12 +1,17 @@
-# TU
-# Please note that tr.R should run first
+# Dataset: tu
+# Description: TU test SDTM dataset for Oncology studies
 
+# Please note that tr_onco.R should run first
+
+# Load libraries ----
 library(dplyr)
 library(tidyselect)
 library(admiral)
 library(metatools)
 
-# Reading input data  --  DUMMY DATA CREATED FROM TR data created from TR
+
+# Create tu ----
+## Read input data  --  DUMMY DATA CREATED FROM TR data created from TR ----
 data("tr_onco")
 data("supptr_onco")
 
@@ -19,7 +24,7 @@ supptr1 <- supptr %>%
 
 tr <- full_join(tr, supptr1, by = c("STUDYID", "USUBJID", "TRSEQ"))
 
-# Renaming And Adding TU Variables
+## Rename And Add TU Variables ----
 tu1 <- tr %>%
   filter((VISITNUM == 3 | (TRGRPID == "NEW" &
     !is.na(TRORRES) & TRORRES != "NO"))) %>%
@@ -43,14 +48,14 @@ tu1 <- tr %>%
     TUSTRESC = TUORRES
   )
 
-# TUSEQ
+## TUSEQ ----
 tu2 <- tu1 %>%
   arrange(STUDYID, USUBJID, VISITNUM, TUDTC, TULNKID) %>%
   group_by(STUDYID, USUBJID) %>%
   mutate(TUSEQ = row_number()) %>%
   ungroup()
 
-# Creating TU
+## Create TU ----
 tu <- select(tu2, c(
   STUDYID, DOMAIN, USUBJID, TUSEQ, TULNKID,
   TUTESTCD, TUTEST, TUORRES, TUSTRESC, TULOC,
@@ -79,6 +84,8 @@ tu_onco <- tu %>% add_labels(
   TUDY = "Study Day of Tumor Identification"
 )
 
-attr(tu_onco, "label") <- "Tumor Identification"
+# Label dataset ----
+attr(tu_onco, "label") <- "Tumor/Lesion Identification"
 
-save(tu_onco, file = "data/tu_onco.rda", compress = "bzip2")
+# Save dataset ----
+usethis::use_data(tu_onco, overwrite = TRUE)
diff --git a/data-raw/vs.R b/data-raw/vs.R
index 748cd25..b5d375f 100644
--- a/data-raw/vs.R
+++ b/data-raw/vs.R
@@ -1,7 +1,14 @@
-# from CDISC pilot study ----
+# Dataset: vs
+# Description: Standard VS dataset from CDISC pilot study
+
+# Load libraries -----
 library(haven)
 library(admiral)
 raw_vs <- read_xpt("https://github.com/cdisc-org/sdtm-adam-pilot-project/blob/master/updated-pilot-submission-package/900172/m5/datasets/cdiscpilot01/tabulations/sdtm/vs.xpt?raw=true") # nolint
 vs <- convert_blanks_to_na(raw_vs)
 
+# Label dataset ----
+attr(vs, "label") <- "Vital Signs"
+
+# Save dataset ----
 usethis::use_data(vs, overwrite = TRUE)
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