diff --git a/CHANGELOG.md b/CHANGELOG.md
index 05380de..4e4f9cc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- Removed non-numeric/non-logical variable features from `shiny_modelbuilder` - [PR #341](https://github.com/4DModeller/fdmr/pull/341)
+- Updated documentation for all functions to reflect better the inputs and outputs - [PR #332](https://github.com/4DModeller/fdmr/pull/332)
+- Fixed an error in `model_viewer` description - [PR #331](https://github.com/4DModeller/fdmr/pull/331)
+- Added to `retrieve_tutorial_data` an option to save tutorial data at a user-specified location or in a temporary directory as default - [PR #330](https://github.com/4DModeller/fdmr/pull/330)
 - Fixed `model_viewer` app to work with random effect models - [PR #317](https://github.com/4DModeller/fdmr/pull/317)
 - Updated `plot_map_leaflet` to feature the same selection of basemap tiles as `mapview` and fix features not appearing - [PR #310](https://github.com/4DModeller/fdmr/pull/310)
 
diff --git a/DESCRIPTION b/DESCRIPTION
index 08d1088..4ebd2bf 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -16,7 +16,7 @@ BugReports: https://github.com/4DModeller/fdmr/issues
 License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
 Additional_repositories: https://inla.r-inla-download.org/R/testing
 Imports: 
     colorspace,
diff --git a/R/meshing.R b/R/meshing.R
index 9d4e704..9eb36c3 100644
--- a/R/meshing.R
+++ b/R/meshing.R
@@ -1,10 +1,10 @@
 # This function taken from https://groups.google.com/g/r-inla-discussion-group/c/z1n1exlZrKM/m/8vYNr2D8BwAJ
 #' Convert an INLA mesh to a SpatialPolygonsDataFrame
 #'
-#' @param mesh Mesh
-#' @param crs Coordinate Reference System as proj4string
+#' @param mesh Mesh object from INLA or fmesher (only R2 manifolds are valid)
+#' @param crs Coordinate Reference System as proj4string, does not support geocentric coordinates
 #'
-#' @return SpatialPolygonsDataFrame
+#' @return SpatialPolygonsDataFrame with mesh triangles
 #' @export
 mesh_to_spatial <- function(mesh, crs) {
   if (!is.character(crs)) {
diff --git a/R/meshing_checks.R b/R/meshing_checks.R
index 78271bb..5d2a5d3 100644
--- a/R/meshing_checks.R
+++ b/R/meshing_checks.R
@@ -3,8 +3,8 @@
 #' 2. A greater number of mesh triangles than observations
 #' 3. Isolated triangles in mesh
 #'
-#' @param mesh INLA mesh
-#' @param observations Observations data to be used woith model
+#' @param mesh INLA/fmesher mesh
+#' @param observations Observations data to be used with model (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
 #'
 #' @return list: Named list containing errors
 #' @export
diff --git a/R/model_parse.R b/R/model_parse.R
index 2e8a9a1..786523d 100644
--- a/R/model_parse.R
+++ b/R/model_parse.R
@@ -1,9 +1,9 @@
 #' Parses inlabru::bru model output to create a list of model parameters
 #'
 #' @param model_output Output from running inlabru::bru
-#' @param measurement_data Measurement data
+#' @param measurement_data Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
 #'
-#' @return list
+#' @return Creates a list of model outputs for the first timestep, including fitted mean and sd, mean of fixed effects, mean and sd of random effects, posterior hyperparameters, and DIC
 #' @keywords internal
 parse_model_output_bru <- function(model_output, measurement_data) {
   fitted_mean_post <- model_output$summary.fitted.values$mean[seq_len(nrow(measurement_data))]
@@ -33,11 +33,11 @@ parse_model_output_bru <- function(model_output, measurement_data) {
 
 #' Parse model output to create a list of model parameters
 #'
-#' @param model_output Data returned by model
-#' @param measurement_data Measurement data
-#' @param model_type Type of model, we currently support inlabru
+#' @param model_output Output returned by model (currently only from running inlabru::bru)
+#' @param measurement_data Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
+#' @param model_type Type of model, we currently only support inlabru
 #'
-#' @return list
+#' @return Creates a list of model outputs, including fitted mean and sd, mean of fixed effects, mean and sd of random effects, posterior hyperparameters, and DIC
 #' @export
 parse_model_output <- function(model_output, measurement_data, model_type = "inlabru") {
   if (model_type == "inlabru") {
@@ -48,13 +48,13 @@ parse_model_output <- function(model_output, measurement_data, model_type = "inl
 
 #' Create a prediction field from the parsed model output and the mesh
 #'
-#' @param mesh INLA mesh
-#' @param plot_type Type of plot to create, "predicted_mean_fields" etc
-#' @param data_dist Type of data, "poisson" etc
-#' @param var_a Data for variable a, required for "predicted_mean_fields" and "random_effect_fields"
-#' @param var_b Data for variable b, required for "predicted_mean_fields"
+#' @param mesh INLA/fmesher mesh
+#' @param plot_type Type of plot to create, "predicted_mean_fields" or "random_mean_fields"
+#' @param data_dist Type of data, "poisson" or "gaussian"
+#' @param var_a Data for variable a (numeric), required for "predicted_mean_fields" and "random_effect_fields"; normally, random effect field from "summary.random$f"
+#' @param var_b Data for variable b (numeric), required for "predicted_mean_fields"; normally, fixed effect from "summary.fixed"
 #'
-#' @return data.frame
+#' @return data.frame with mesh node latlong coordinates (x, y) and the selected field values at the mesh nodes (z)
 #' @export
 create_prediction_field <- function(mesh,
                                     plot_type = "predicted_mean_fields",
diff --git a/R/plot_graph.R b/R/plot_graph.R
index 5bc8beb..153abe2 100644
--- a/R/plot_graph.R
+++ b/R/plot_graph.R
@@ -1,9 +1,9 @@
 #' Plot a bar chart using ggplot2
 #'
-#' @param data Data to plot
-#' @param x x-axis data
+#' @param data Data to plot (all data types recognised by ggplot2::geom_bar() like data.frame)
+#' @param x x-axis data, must be a Date object
 #' @param y y-axis data
-#' @param breaks Break points
+#' @param breaks Break points, must be a sequence of dates
 #' @param x_label x-axis label
 #' @param y_label y-axis label
 #' @param fill Fill colour
@@ -47,10 +47,10 @@ plot_barchart <- function(data, x, y, breaks, x_label, y_label, fill = "pink", c
 
 #' Plot a boxplot using ggplot2
 #'
-#' @param data Data to plot
-#' @param x x-axis data
+#' @param data Data to plot (all data types recognised by ggplot2::geom_boxplot() like data.frame)
+#' @param x x-axis data, must be a Date object
 #' @param y y-axis data
-#' @param breaks Break points
+#' @param breaks Break points, must be a sequence of dates
 #' @param x_label x-axis label
 #' @param y_label y-axis label
 #'
@@ -82,10 +82,10 @@ plot_boxplot <- function(data, x, y, breaks, x_label, y_label) {
 
 #' Plot timeseries data
 #'
-#' @param data Data to plot
-#' @param x Name of column to plot on x-axis, should be datetime, will be converted to Dates using as.Date
+#' @param data Data to plot (data.frame with x-axis column a character convertible to Date)
+#' @param x Name of column to plot on x-axis
 #' @param y Name of column to plot on y-axis
-#' @param breaks Date break points
+#' @param breaks Date break points, must be a sequence of dates
 #' @param x_label x-axis label
 #' @param y_label y-axis label
 #' @param title Figure title
@@ -93,8 +93,8 @@ plot_boxplot <- function(data, x, y, breaks, x_label, y_label) {
 #' @param line_colour Line colour
 #' @param horizontal_y y-intercept for horizontal line
 #' @param vertical_x x-intercept for vertical line
-#' @param x_lim Limits for x-axis continous scale, vector passed to scale_x_continuous
-#' @param y_lim Limits for y-axis continuous scale, vector passed to scale_y_continous
+#' @param x_lim Limits for x-axis continuous scale, vector passed to scale_x_continuous
+#' @param y_lim Limits for y-axis continuous scale, vector passed to scale_y_continuous
 #'
 #' @return ggplot
 #' @export
@@ -172,12 +172,12 @@ plot_timeseries <- function(data,
 
 #' Create a line plot with a confidence interval.
 #'
-#' @param data Data to plot
-#' @param x x-axis data
+#' @param data Data to plot (all data types recognised by ggplot2::geom_line() like data.frame)
+#' @param x x-axis data, must be a Date object
 #' @param y1 y1 line data - solid
 #' @param y2 y2 line data - dashed
 #' @param y3 y3 line data - dashed
-#' @param breaks Breaks vector
+#' @param breaks Breaks vector, must be a sequence of dates
 #' @param x_label x-axis label
 #' @param y_label y-axis label
 #' @param y1_colour Colour for y1
diff --git a/R/plot_mapping.R b/R/plot_mapping.R
index bc79a9d..a9be946 100644
--- a/R/plot_mapping.R
+++ b/R/plot_mapping.R
@@ -6,10 +6,10 @@
 #' The leaflet backend will work for most use cases and is recommended.
 #' For plotting of maps with UTM coordinates, the mapview backend is recommended.
 #'
-#' @param polygon_data Polygon data
-#' @param raster_data Raster datas
-#' @param domain Domain data to be passed to leaflet::colorNumeric and leaflet::addLegend
-#' @param markers Markers to display on map. A named list with latitude, longitude and label names must be given.
+#' @param polygon_data Polygon data (SpatialPolygon or SpatialPolygonDataFrame)
+#' @param raster_data Raster data (RasterLayer or SpatialRaster)
+#' @param domain Domain data (numeric or factor) to be passed to leaflet::colorNumeric and leaflet::addLegend
+#' @param markers Markers to display on map. A named list or data.frame with latitude, longitude and label names must be given.
 #' @param palette Palette to be used for colours, defaults to viridis
 #' @param legend_title Title for legend
 #' @param add_scale_bar Add scale bar if TRUE
@@ -71,10 +71,10 @@ plot_map <- function(polygon_data = NULL,
 
 #' Create a simple Leaflet map from data
 #'
-#' @param polygon_data Polygon data
-#' @param raster_data Raster data
-#' @param domain Domain data to be passed to leaflet::colorNumeric and leaflet::addLegend
-#' @param markers Markers to display on map. A named list with latitude, longitude and label names must be given.
+#' @param polygon_data Polygon data (SpatialPolygon or SpatialPolygonDataFrame)
+#' @param raster_data Raster data (RasterLayer or SpatialRaster)
+#' @param domain Domain data (numeric or factor) to be passed to leaflet::colorNumeric and leaflet::addLegend
+#' @param markers Markers to display on map. A named list or data.frame with latitude, longitude and label names must be given.
 #' @param palette Palette to be used for colours, defaults to viridis
 #' @param legend_title Title for legend
 #' @param add_scale_bar Add scale bar if TRUE
diff --git a/R/plot_mesh.R b/R/plot_mesh.R
index 617ad9a..07fd6d5 100644
--- a/R/plot_mesh.R
+++ b/R/plot_mesh.R
@@ -1,14 +1,14 @@
 #' Plot a mesh on a Leaflet map
 #'
-#' @param mesh Mesh data
+#' @param mesh Mesh object from INLA or fmesher
 #' @param spatial_data Spatial data, either a SpatialPolygonsDataFrame, SpatialPointsDataFrame or an object
 #' that can be converted to a data.frame with longitude and latitude columns
-#' @param longitude_column Longitude column in spatial_data
-#' @param latitude_column Latitude column in spatial_data name
+#' @param longitude_column Longitude column name in spatial_data
+#' @param latitude_column Latitude column name in spatial_data
 #' @param markers Markers to display on top of mesh. A named list with latitude, longitude and label names must be given.
 #' Expects longitude name to be longitude, latitude name to be latitude, label name to be label.
 #'
-#' @return leaflet::leaflet
+#' @return leaflet::leaflet with mesh and markers
 #' @export
 plot_mesh <- function(mesh, spatial_data = NULL, longitude_column = "LONG", latitude_column = "LAT", markers = NULL) {
   expected_crs <- "+proj=longlat +datum=WGS84"
diff --git a/R/plot_priors.R b/R/plot_priors.R
index 7c8524a..d4312b8 100644
--- a/R/plot_priors.R
+++ b/R/plot_priors.R
@@ -1,10 +1,11 @@
 #' Plot line comparison for stdev etc
 #'
-#' @param data Parsed model output
+#' @param data List of parsed model outputs from "parse_model_output" (a list of lists)
 #' @param to_plot Type of data to plot, "Range for f" etc
+#' @param title Title of the plot, defaults to the value of "to_plot"
 #'
-#' @return ggplot2::ggplot
-plot_line_comparison <- function(data, to_plot, title) {
+#' @return ggplot2::ggplot of the selected hyperparameter posterior distribution
+plot_line_comparison <- function(data, to_plot, title = to_plot) {
   parsed_data <- purrr::map(data, function(x) as.data.frame(x$pars[[to_plot]]))
   single_df <- dplyr::bind_rows(parsed_data, .id = "Run")
   if (nrow(single_df) == 0) {
@@ -19,9 +20,9 @@ plot_line_comparison <- function(data, to_plot, title) {
 
 #' Create boxplots from priors run data
 #'
-#' @param data
+#' @param data A list of parsed model output from "parse_model_output" (a list of lists)
 #'
-#' @return graphics::boxplot
+#' @return graphics::boxplot of fitted values
 plot_priors_boxplot <- function(data) {
   # TODO - I'm sure this can be done in a nicer functional way
   fitted_mean_post <- purrr::map(data, function(x) x$fitted_mean_post)
@@ -34,10 +35,10 @@ plot_priors_boxplot <- function(data) {
 #' Plot density function
 #'
 #'
-#' @param data Parsed model outputs
-#' @param measurement_data Measurement data
+#' @param data List of parsed model outputs from "parse_model_output" (a list of lists)
+#' @param measurement_data Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
 #'
-#' @return ggplot2::ggplot
+#' @return ggplot2::ggplot of measurement density by value
 plot_priors_density <- function(data, measurement_data) {
   # Can this be done in a cleaner way? Just create a dataframe from the lists?
   fitted_values <- unlist(purrr::map(data, function(x) x$fitted_mean_post))
@@ -56,9 +57,9 @@ plot_priors_density <- function(data, measurement_data) {
 
 #' Plot Deviance Information Criterion (DIC) values
 #'
-#' @param data
+#' @param data List of parsed model outputs from "parse_model_output" (a list of lists)
 #'
-#' @return ggplot2::ggplot
+#' @return ggplot2::ggplot with DIC values shown as points
 plot_dic <- function(data) {
   infocri <- base::cbind.data.frame(
     priors = unlist(purrr::map(seq(1, length(data)), function(x) paste("Run", x))),
diff --git a/R/shiny_meshbuilder.R b/R/shiny_meshbuilder.R
index 8a22be0..7ce5ed9 100644
--- a/R/shiny_meshbuilder.R
+++ b/R/shiny_meshbuilder.R
@@ -1,6 +1,6 @@
 #' Mesh building shiny app
 #'
-#' @param spatial_data Spatial data
+#' @param spatial_data Spatial data (must be a data.frame, SpatialPointsDataFrame or SpatialPolygonsDataFrame)
 #' @param obs_data Measurement data
 #' @param crs CRS as a proj4string
 #' @param offset Specifies the size of the inner and outer extensions around data locations, passed to fmesher::fm_mesh_2d_inla
@@ -11,7 +11,7 @@
 #'
 #' @importFrom magrittr %>%
 #'
-#' @return shiny::app
+#' @return shiny::app with meshbuilder functionality
 #' @keywords internal
 meshbuilder_shiny <- function(
     spatial_data,
@@ -55,10 +55,10 @@ meshbuilder_shiny <- function(
     stop("Cannot read latitude and longitude data from spatial data. Please ensure given names are correct.")
   }
 
-  default_max_edge_min <- 0.01
-  default_max_edge_max <- 0.3
+  default_max_edge_min <- 0.9
+  default_max_edge_max <- 1.8
   default_offset_min <- 0.02
-  default_offset_max <- 0.2
+  default_offset_max <- 2
   default_cutoff <- 0.02
   # TODO - these defaults need changing?
   if (!is.null(max_edge)) {
@@ -234,7 +234,7 @@ meshbuilder_shiny <- function(
         spatial_data
       }
     })
-
+    
     output$map <- leaflet::renderLeaflet({
       map_tiles <- c("OpenStreetMap", "Esri.WorldImagery", "OpenTopoMap")
       m <- mapview::mapview(mesh_spatial(), layer.name = "Mesh", col.regions = "#548C2F", map.types = map_tiles) + mapview::mapview(spatial(), layer.name = "Spatial")
@@ -270,7 +270,7 @@ meshbuilder_shiny <- function(
 
 #' Mesh building shiny app. Creates and visualises a mesh from some spatial data.
 #'
-#' @param spatial_data Spatial data
+#' @param spatial_data Spatial data (must be a data.frame, SpatialPointsDataFrame or SpatialPolygonsDataFrame)
 #' @param obs_data Measurement data
 #' @param crs CRS as a proj4string
 #' @param offset Specifies the size of the inner and outer extensions around data locations, passed to fmesher::fm_mesh_2d_inla
@@ -279,7 +279,7 @@ meshbuilder_shiny <- function(
 #' @param y_coord Name of the latitude column in the spatial data
 #' @param x_coord Name of the longitude column in the spatial data
 #'
-#' @return shiny::app
+#' @return shiny::app with meshbuilder functionality
 #' @export
 mesh_builder <- function(spatial_data, obs_data = NULL, crs = NULL, max_edge = NULL, offset = NULL, cutoff = NULL, y_coord = "LAT", x_coord = "LONG") {
   shiny::runApp(meshbuilder_shiny(
diff --git a/R/shiny_modelbuilder.R b/R/shiny_modelbuilder.R
index fc395d3..577fcdd 100644
--- a/R/shiny_modelbuilder.R
+++ b/R/shiny_modelbuilder.R
@@ -1,15 +1,15 @@
 #' Interactively set and see the result of different priors
 #'
-#' @param spatial_data Spatial data
-#' @param measurement_data Measurement data
-#' @param time_variable Time variable in measurement_data
-#' @param mesh INLA mesh
+#' @param spatial_data Spatial data (must be SpatialPoints or SpatialPointsDataFrame)
+#' @param measurement_data Measurement data (SpatialPointsDataFrame, SpatialPolygonsDataFrame with a named time column and at least 1 named feature column with measurements)
+#' @param time_variable Time variable name in measurement_data
+#' @param mesh INLA/fmesher mesh
 #' @param data_distribution Data distribution, Poisson or Gaussian
-#' @param log_folder Folder to write out logs
+#' @param log_folder Folder to write out logs (character)
 #'
 #' @importFrom INLA f
 #'
-#' @return shiny::app
+#' @return shiny::app with model builder functionality
 #' @keywords internal
 model_builder_shiny <- function(spatial_data,
                                 measurement_data,
@@ -65,7 +65,7 @@ model_builder_shiny <- function(spatial_data,
   citation_control_group <- "Prior explanation text modified from https://www.paulamoraga.com/book-geospatial/sec-geostatisticaldataexamplest.html"
 
   initial_equation_val <- "formula <- model_var ~ 0 + Intercept(1)"
-  features <- names(measurement_data)
+  features <- names(measurement_data@data[base::sapply(measurement_data@data, is.numeric) | base::sapply(measurement_data@data, is.logical)])
   if (is.null(features)) {
     stop("We require the columns of measurement_data to have the names of the features to use in the model.")
   }
@@ -697,12 +697,12 @@ model_builder_shiny <- function(spatial_data,
 #' Interactively set and see the result of different priors
 #'
 #' @param spatial_data Spatial data
-#' @param measurement_data Measurement data
-#' @param time_variable Time variable in measurement_data
-#' @param mesh INLA mesh
-#' @param log_folder Folder to write logs to
+#' @param measurement_data Measurement data (SpatialPointsDataFrame, SpatialPolygonsDataFrame with a named time column and at least 1 named feature column with measurements)
+#' @param time_variable Time variable name in measurement_data
+#' @param mesh INLA/fmesher mesh
+#' @param log_folder Folder to write logs to (character)
 #'
-#' @return shiny::app
+#' @return shiny::app with model builder functionality
 #' @export
 model_builder <- function(spatial_data, measurement_data, time_variable, mesh, data_distribution = "Poisson", log_folder = NULL) {
   shiny::runApp(model_builder_shiny(spatial_data = spatial_data, measurement_data = measurement_data, time_variable = time_variable, mesh = mesh, data_distribution = data_distribution, log_folder = log_folder))
diff --git a/R/shiny_modelviewer.R b/R/shiny_modelviewer.R
index 1bb6a9e..d83b084 100644
--- a/R/shiny_modelviewer.R
+++ b/R/shiny_modelviewer.R
@@ -1,13 +1,13 @@
 #' Parse inlabru model output
 #'
-#' @param model_output INLA model output
-#' @param mesh INLA mesh
-#' @param measurement_data Measurement data
+#' @param model_output INLA/inlabru model output
+#' @param mesh INLA/fmesher mesh
+#' @param measurement_data Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
 #' @param data_distribution Type of data, Poisson or Gaussian
 #'
 #' @importFrom magrittr %>%
 #'
-#' @return shiny::app
+#' @return shiny::app with model viewer functionality
 #' @keywords internal
 model_viewer_shiny <- function(model_output, mesh, measurement_data, data_distribution) {
   busy_spinner <- get_busy_spinner()
@@ -295,14 +295,14 @@ model_viewer_shiny <- function(model_output, mesh, measurement_data, data_distri
   shiny::shinyApp(ui = ui, server = server)
 }
 
-#' Mesh building shiny app. Creates and visualises a mesh from some spatial data.
+#' Model viewing shiny app. Visualises INLA model output, plots the posterior distributions of model parameters and prediction statistics.
 #'
-#' @param model_output INLA model output
-#' @param mesh INLA mesh
-#' @param measurement_data Measurement data
-#' @param data_distribution Type of data, Poisson or Gaussian
+#' @param model_output INLA/inlabru model output
+#' @param mesh INLA/fmesher mesh used for the run
+#' @param measurement_data Measurement data used for the run (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)
+#' @param data_distribution Type of data, Poisson or Gaussian (character)
 #'
-#' @return shiny::app
+#' @return shiny::app with model viewer functionality
 #' @export
 model_viewer <- function(model_output, mesh, measurement_data, data_distribution = "Poisson") {
   shiny::runApp(model_viewer_shiny(model_output = model_output, mesh = mesh, measurement_data = measurement_data, data_distribution = data_distribution))
diff --git a/R/util_paths.R b/R/util_paths.R
index 5ccee5b..24c748f 100644
--- a/R/util_paths.R
+++ b/R/util_paths.R
@@ -2,11 +2,12 @@
 #'
 #' @param dataset Name of dataset
 #' @param filename Name of file
+#' @param saved Specify the location where user unpacked the data.
 #'
 #' @return fs::path Full filepath
 #' @export
-get_tutorial_datapath <- function(dataset, filename) {
-  tutorial_datapath <- fs::path(get_tutorial_cache_datapath(), dataset)
+get_tutorial_datapath <- function(dataset, filename, saved = FALSE) {
+  tutorial_datapath <- fs::path(get_tutorial_cache_datapath(saved), dataset)
 
   if (!fs::dir_exists(tutorial_datapath)) {
     stop("Unable to load data, the folder ", toString(tutorial_datapath), " does not exist. Have you run retrieve_tutorial_data?")
@@ -26,15 +27,16 @@ get_tutorial_datapath <- function(dataset, filename) {
 #'
 #' @param dataset Name of dataset
 #' @param filename Name of file
+#' @param saved Specify the location where user unpacked the data
 #'
 #' @return loaded object
 #' @export
-load_tutorial_data <- function(dataset, filename) {
+load_tutorial_data <- function(dataset, filename, saved = FALSE) {
   if (!tolower(fs::path_ext(filename)) == "rds") {
     stop("We can only load rds files.")
   }
 
-  fpath <- get_tutorial_datapath(dataset = dataset, filename = filename)
+  fpath <- get_tutorial_datapath(dataset = dataset, filename = filename, saved = saved)
   return(readRDS(fpath))
 }
 
@@ -62,30 +64,55 @@ clean_path <- function(path, check_exists = FALSE) {
   return(fpath)
 }
 
+
 #' Get path to tutorial data cache folder
+#' 
+#' @param saved Specify the location where user unpacked the data
 #'
 #' @return fs::path
 #' @keywords internal
-get_tutorial_cache_datapath <- function() {
-  fs::path(fs::path_home(), "fdmr", "tutorial_data")
+get_tutorial_cache_datapath <- function(saved) {
+  if (base::isTRUE(saved) | base::is.character(saved)){
+    if (base::is.character(saved)) {
+      save_path <- check_path(saved)
+      fs::path(save_path, "fdmr", "tutorial_data")
+    } else{
+      fs::path(fs::path_home(), "fdmr", "tutorial_data")
+    }
+  } else {
+    fs::path(fs::path_temp(), "fdmr", "tutorial_data")
+  }
 }
 
 #' Get path to downloaded archive cache folder
+#' 
+#' @param saved Specify the location where user unpacked the data
 #'
 #' @return fs::path
 #' @keywords internal
-get_archive_cache_datapath <- function() {
-  fs::path(fs::path_home(), "fdmr", "download_cache")
+get_archive_cache_datapath <- function(saved) {
+  if (base::isTRUE(saved) | base::is.character(saved)){
+    if (base::is.character(saved)) {
+      save_path <- check_path(saved)
+      fs::path(save_path, "fdmr", "download_cache")
+    } else{
+      fs::path(fs::path_home(), "fdmr", "download_cache")
+    }
+  } else {
+    fs::path(fs::path_temp(), "fdmr", "download_cache")
+  }
 }
 
 
 #' Clear both tutorial data and downloaded archive caches
 #'
+#' @param saved Specify the location where user unpacked the data
+#'
 #' @return NULL
 #' @export
-clear_caches <- function() {
-  tut_path <- get_tutorial_cache_datapath()
-  cache_path <- get_archive_cache_datapath()
+clear_caches <- function(saved = TRUE) {
+  tut_path <- get_tutorial_cache_datapath(saved)
+  cache_path <- get_archive_cache_datapath(saved)
   print(paste("Deleting ", tut_path, cache_path))
   fs::dir_delete(tut_path)
   fs::dir_delete(cache_path)
diff --git a/R/util_retrieve.R b/R/util_retrieve.R
index 7a284c2..1270756 100644
--- a/R/util_retrieve.R
+++ b/R/util_retrieve.R
@@ -1,14 +1,25 @@
-#' Retrieve a tutorial dataset and unpacks it to ~/fdmr/tutorial_data
+#' Retrieves a tutorial dataset and unpacks it to a place specified by the user (~/fdmr/tutorial_data)
 #'
 #' @param dataset Name of dataset to retrieve
 #' @param force_update Force retrieval of metadata and dataset
+#' @param save Unpack the dataset to where user specified (character), home directory (TRUE), session's temporary directory (FALSE: default).
 #'
 #' @return NULL
 #' @export
-retrieve_tutorial_data <- function(dataset, force_update = FALSE) {
+retrieve_tutorial_data <- function(dataset, force_update = FALSE, save = FALSE) {
   dataset <- base::tolower(dataset)
 
-  download_cache_folder <- fs::path(fs::path_home(), "fdmr", "download_cache")
+  if (base::isTRUE(save) | base::is.character(save)){
+    if (base::is.character(save)) {
+      save_path <- clean_path(save, check_exists = TRUE)
+      download_cache_folder <- fs::path(save_path, "fdmr", "download_cache")
+    } else{
+      download_cache_folder <- fs::path(fs::path_home(), "fdmr", "download_cache")
+    }
+  } else {
+    download_cache_folder <- fs::path(fs::path_temp(), "fdmr", "download_cache")
+    }
+
   if (!fs::dir_exists(download_cache_folder)) {
     fs::dir_create(download_cache_folder, recurse = TRUE)
   }
@@ -40,7 +51,17 @@ retrieve_tutorial_data <- function(dataset, force_update = FALSE) {
     jsonlite::write_json(retrieval_info, path = file_metadata_file)
   }
 
-  extract_path <- fs::path(fs::path_home(), "fdmr", "tutorial_data", dataset)
+  if (base::isTRUE(save) | base::is.character(save)){
+    if (base::is.character(save)){
+      save_path <- clean_path(save, check_exists = TRUE)
+      extract_path <- fs::path(save_path, "fdmr", "tutorial_data", dataset)
+    } else{
+      extract_path <- fs::path(fs::path_home(), "fdmr", "tutorial_data", dataset)
+    }
+  } else {
+    extract_path <- fs::path(fs::path_temp(), "fdmr", "tutorial_data", dataset)
+    }
+  
 
   if (!fs::dir_exists(extract_path)) {
     fs::dir_create(extract_path, recurse = TRUE)
@@ -72,4 +93,4 @@ retrieve_tutorial_data <- function(dataset, force_update = FALSE) {
   } else {
     stop("Invalid dataset, please see available datasets at https://github.com/4DModeller/fdmr_data")
   }
-}
+}
\ No newline at end of file
diff --git a/README.md b/README.md
index 7a25c95..e56157b 100644
--- a/README.md
+++ b/README.md
@@ -30,6 +30,7 @@ The easiest way to do this is to [install RStudio](https://posit.co/downloads/).
 Next start an R session and run
 
 ```R
+install.packages("INLA", repos=c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/testing"), dep=TRUE)
 install.packages("devtools")
 library(devtools)
 devtools::install_github("4DModeller/fdmr")
@@ -37,6 +38,8 @@ devtools::install_github("4DModeller/fdmr")
 
 You should now have `fdmr` and all its dependencies installed and you can continue on [one of our tutorials](https://4dmodeller.github.io/fdmr/articles/).
 
+If your installation of `INLA` fails, please consult the [R-INLA website](https://www.r-inla.org/download-install) for platform-specific instructions.
+
 ## Installation
 
 On most systems the commands above should get you up and running. On some Linux systems we've found the need to 
diff --git a/man/clear_caches.Rd b/man/clear_caches.Rd
index f5fb2f6..e05db3b 100644
--- a/man/clear_caches.Rd
+++ b/man/clear_caches.Rd
@@ -4,7 +4,10 @@
 \alias{clear_caches}
 \title{Clear both tutorial data and downloaded archive caches}
 \usage{
-clear_caches()
+clear_caches(saved = TRUE)
+}
+\arguments{
+\item{saved}{Specify the location where user unpacked the data}
 }
 \description{
 Clear both tutorial data and downloaded archive caches
diff --git a/man/create_prediction_field.Rd b/man/create_prediction_field.Rd
index aa3a115..cc3dd09 100644
--- a/man/create_prediction_field.Rd
+++ b/man/create_prediction_field.Rd
@@ -13,18 +13,18 @@ create_prediction_field(
 )
 }
 \arguments{
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh}
 
-\item{plot_type}{Type of plot to create, "predicted_mean_fields" etc}
+\item{plot_type}{Type of plot to create, "predicted_mean_fields" or "random_mean_fields"}
 
-\item{data_dist}{Type of data, "poisson" etc}
+\item{data_dist}{Type of data, "poisson" or "gaussian"}
 
-\item{var_a}{Data for variable a, required for "predicted_mean_fields" and "random_effect_fields"}
+\item{var_a}{Data for variable a (numeric), required for "predicted_mean_fields" and "random_effect_fields"; normally, random effect field from "summary.random$f"}
 
-\item{var_b}{Data for variable b, required for "predicted_mean_fields"}
+\item{var_b}{Data for variable b (numeric), required for "predicted_mean_fields"; normally, fixed effect from "summary.fixed"}
 }
 \value{
-data.frame
+data.frame with mesh node latlong coordinates (x, y) and the selected field values at the mesh nodes (z)
 }
 \description{
 Create a prediction field from the parsed model output and the mesh
diff --git a/man/get_archive_cache_datapath.Rd b/man/get_archive_cache_datapath.Rd
index d41132d..153ab8f 100644
--- a/man/get_archive_cache_datapath.Rd
+++ b/man/get_archive_cache_datapath.Rd
@@ -4,7 +4,10 @@
 \alias{get_archive_cache_datapath}
 \title{Get path to downloaded archive cache folder}
 \usage{
-get_archive_cache_datapath()
+get_archive_cache_datapath(saved)
+}
+\arguments{
+\item{saved}{Specify the location where user unpacked the data}
 }
 \value{
 fs::path
diff --git a/man/get_tutorial_cache_datapath.Rd b/man/get_tutorial_cache_datapath.Rd
index 2fa2e8a..fa6370a 100644
--- a/man/get_tutorial_cache_datapath.Rd
+++ b/man/get_tutorial_cache_datapath.Rd
@@ -4,7 +4,10 @@
 \alias{get_tutorial_cache_datapath}
 \title{Get path to tutorial data cache folder}
 \usage{
-get_tutorial_cache_datapath()
+get_tutorial_cache_datapath(saved)
+}
+\arguments{
+\item{saved}{Specify the location where user unpacked the data}
 }
 \value{
 fs::path
diff --git a/man/get_tutorial_datapath.Rd b/man/get_tutorial_datapath.Rd
index b7776a8..598ceba 100644
--- a/man/get_tutorial_datapath.Rd
+++ b/man/get_tutorial_datapath.Rd
@@ -4,12 +4,14 @@
 \alias{get_tutorial_datapath}
 \title{Return the filepath for a tutorial data file.}
 \usage{
-get_tutorial_datapath(dataset, filename)
+get_tutorial_datapath(dataset, filename, saved = FALSE)
 }
 \arguments{
 \item{dataset}{Name of dataset}
 
 \item{filename}{Name of file}
+
+\item{saved}{Specify the location where user unpacked the data.}
 }
 \value{
 fs::path Full filepath
diff --git a/man/load_tutorial_data.Rd b/man/load_tutorial_data.Rd
index 0f8a576..74a494f 100644
--- a/man/load_tutorial_data.Rd
+++ b/man/load_tutorial_data.Rd
@@ -4,12 +4,14 @@
 \alias{load_tutorial_data}
 \title{Load data from the tutorial data store}
 \usage{
-load_tutorial_data(dataset, filename)
+load_tutorial_data(dataset, filename, saved = FALSE)
 }
 \arguments{
 \item{dataset}{Name of dataset}
 
 \item{filename}{Name of file}
+
+\item{saved}{Specify the location where user unpacked the data}
 }
 \value{
 loaded object
diff --git a/man/mesh_builder.Rd b/man/mesh_builder.Rd
index b8b00ee..dc88467 100644
--- a/man/mesh_builder.Rd
+++ b/man/mesh_builder.Rd
@@ -16,7 +16,7 @@ mesh_builder(
 )
 }
 \arguments{
-\item{spatial_data}{Spatial data}
+\item{spatial_data}{Spatial data (must be a data.frame, SpatialPointsDataFrame or SpatialPolygonsDataFrame)}
 
 \item{obs_data}{Measurement data}
 
@@ -33,7 +33,7 @@ mesh_builder(
 \item{x_coord}{Name of the longitude column in the spatial data}
 }
 \value{
-shiny::app
+shiny::app with meshbuilder functionality
 }
 \description{
 Mesh building shiny app. Creates and visualises a mesh from some spatial data.
diff --git a/man/mesh_checker.Rd b/man/mesh_checker.Rd
index 186009f..0300b0d 100644
--- a/man/mesh_checker.Rd
+++ b/man/mesh_checker.Rd
@@ -12,9 +12,9 @@
 mesh_checker(mesh, observations)
 }
 \arguments{
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh}
 
-\item{observations}{Observations data to be used woith model}
+\item{observations}{Observations data to be used with model (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 }
 \value{
 list: Named list containing errors
diff --git a/man/mesh_to_spatial.Rd b/man/mesh_to_spatial.Rd
index d5b8481..160b0ec 100644
--- a/man/mesh_to_spatial.Rd
+++ b/man/mesh_to_spatial.Rd
@@ -7,12 +7,12 @@
 mesh_to_spatial(mesh, crs)
 }
 \arguments{
-\item{mesh}{Mesh}
+\item{mesh}{Mesh object from INLA or fmesher (only R2 manifolds are valid)}
 
-\item{crs}{Coordinate Reference System as proj4string}
+\item{crs}{Coordinate Reference System as proj4string, does not support geocentric coordinates}
 }
 \value{
-SpatialPolygonsDataFrame
+SpatialPolygonsDataFrame with mesh triangles
 }
 \description{
 Convert an INLA mesh to a SpatialPolygonsDataFrame
diff --git a/man/meshbuilder_shiny.Rd b/man/meshbuilder_shiny.Rd
index 27656e2..b8d5f40 100644
--- a/man/meshbuilder_shiny.Rd
+++ b/man/meshbuilder_shiny.Rd
@@ -17,7 +17,7 @@ meshbuilder_shiny(
 )
 }
 \arguments{
-\item{spatial_data}{Spatial data}
+\item{spatial_data}{Spatial data (must be a data.frame, SpatialPointsDataFrame or SpatialPolygonsDataFrame)}
 
 \item{obs_data}{Measurement data}
 
@@ -34,7 +34,7 @@ meshbuilder_shiny(
 \item{x_coord}{Name of the longitude column in the spatial data}
 }
 \value{
-shiny::app
+shiny::app with meshbuilder functionality
 }
 \description{
 Mesh building shiny app
diff --git a/man/model_builder.Rd b/man/model_builder.Rd
index c9f43df..d8b8374 100644
--- a/man/model_builder.Rd
+++ b/man/model_builder.Rd
@@ -16,16 +16,16 @@ model_builder(
 \arguments{
 \item{spatial_data}{Spatial data}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (SpatialPointsDataFrame, SpatialPolygonsDataFrame with a named time column and at least 1 named feature column with measurements)}
 
-\item{time_variable}{Time variable in measurement_data}
+\item{time_variable}{Time variable name in measurement_data}
 
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh}
 
-\item{log_folder}{Folder to write logs to}
+\item{log_folder}{Folder to write logs to (character)}
 }
 \value{
-shiny::app
+shiny::app with model builder functionality
 }
 \description{
 Interactively set and see the result of different priors
diff --git a/man/model_builder_shiny.Rd b/man/model_builder_shiny.Rd
index e48b033..e728197 100644
--- a/man/model_builder_shiny.Rd
+++ b/man/model_builder_shiny.Rd
@@ -14,20 +14,20 @@ model_builder_shiny(
 )
 }
 \arguments{
-\item{spatial_data}{Spatial data}
+\item{spatial_data}{Spatial data (must be SpatialPoints or SpatialPointsDataFrame)}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (SpatialPointsDataFrame, SpatialPolygonsDataFrame with a named time column and at least 1 named feature column with measurements)}
 
-\item{time_variable}{Time variable in measurement_data}
+\item{time_variable}{Time variable name in measurement_data}
 
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh}
 
 \item{data_distribution}{Data distribution, Poisson or Gaussian}
 
-\item{log_folder}{Folder to write out logs}
+\item{log_folder}{Folder to write out logs (character)}
 }
 \value{
-shiny::app
+shiny::app with model builder functionality
 }
 \description{
 Interactively set and see the result of different priors
diff --git a/man/model_viewer.Rd b/man/model_viewer.Rd
index 8ea96f7..48e9e43 100644
--- a/man/model_viewer.Rd
+++ b/man/model_viewer.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/shiny_modelviewer.R
 \name{model_viewer}
 \alias{model_viewer}
-\title{Mesh building shiny app. Creates and visualises a mesh from some spatial data.}
+\title{Model viewing shiny app. Visualises INLA model output, plots the posterior distributions of model parameters and prediction statistics.}
 \usage{
 model_viewer(
   model_output,
@@ -12,17 +12,17 @@ model_viewer(
 )
 }
 \arguments{
-\item{model_output}{INLA model output}
+\item{model_output}{INLA/inlabru model output}
 
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh used for the run}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data used for the run (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 
-\item{data_distribution}{Type of data, Poisson or Gaussian}
+\item{data_distribution}{Type of data, Poisson or Gaussian (character)}
 }
 \value{
-shiny::app
+shiny::app with model viewer functionality
 }
 \description{
-Mesh building shiny app. Creates and visualises a mesh from some spatial data.
+Model viewing shiny app. Visualises INLA model output, plots the posterior distributions of model parameters and prediction statistics.
 }
diff --git a/man/model_viewer_shiny.Rd b/man/model_viewer_shiny.Rd
index 1e0fbcb..471d154 100644
--- a/man/model_viewer_shiny.Rd
+++ b/man/model_viewer_shiny.Rd
@@ -7,16 +7,16 @@
 model_viewer_shiny(model_output, mesh, measurement_data, data_distribution)
 }
 \arguments{
-\item{model_output}{INLA model output}
+\item{model_output}{INLA/inlabru model output}
 
-\item{mesh}{INLA mesh}
+\item{mesh}{INLA/fmesher mesh}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 
 \item{data_distribution}{Type of data, Poisson or Gaussian}
 }
 \value{
-shiny::app
+shiny::app with model viewer functionality
 }
 \description{
 Parse inlabru model output
diff --git a/man/parse_model_output.Rd b/man/parse_model_output.Rd
index 9caa7b9..ca0fbee 100644
--- a/man/parse_model_output.Rd
+++ b/man/parse_model_output.Rd
@@ -7,14 +7,14 @@
 parse_model_output(model_output, measurement_data, model_type = "inlabru")
 }
 \arguments{
-\item{model_output}{Data returned by model}
+\item{model_output}{Output returned by model (currently only from running inlabru::bru)}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 
-\item{model_type}{Type of model, we currently support inlabru}
+\item{model_type}{Type of model, we currently only support inlabru}
 }
 \value{
-list
+Creates a list of model outputs, including fitted mean and sd, mean of fixed effects, mean and sd of random effects, posterior hyperparameters, and DIC
 }
 \description{
 Parse model output to create a list of model parameters
diff --git a/man/parse_model_output_bru.Rd b/man/parse_model_output_bru.Rd
index f5439ce..42fbb43 100644
--- a/man/parse_model_output_bru.Rd
+++ b/man/parse_model_output_bru.Rd
@@ -9,10 +9,10 @@ parse_model_output_bru(model_output, measurement_data)
 \arguments{
 \item{model_output}{Output from running inlabru::bru}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 }
 \value{
-list
+Creates a list of model outputs for the first timestep, including fitted mean and sd, mean of fixed effects, mean and sd of random effects, posterior hyperparameters, and DIC
 }
 \description{
 Parses inlabru::bru model output to create a list of model parameters
diff --git a/man/plot_barchart.Rd b/man/plot_barchart.Rd
index 27832e9..b02b021 100644
--- a/man/plot_barchart.Rd
+++ b/man/plot_barchart.Rd
@@ -16,13 +16,13 @@ plot_barchart(
 )
 }
 \arguments{
-\item{data}{Data to plot}
+\item{data}{Data to plot (all data types recognised by ggplot2::geom_bar() like data.frame)}
 
-\item{x}{x-axis data}
+\item{x}{x-axis data, must be a Date object}
 
 \item{y}{y-axis data}
 
-\item{breaks}{Break points}
+\item{breaks}{Break points, must be a sequence of dates}
 
 \item{x_label}{x-axis label}
 
diff --git a/man/plot_boxplot.Rd b/man/plot_boxplot.Rd
index 6e3477e..41398dc 100644
--- a/man/plot_boxplot.Rd
+++ b/man/plot_boxplot.Rd
@@ -7,13 +7,13 @@
 plot_boxplot(data, x, y, breaks, x_label, y_label)
 }
 \arguments{
-\item{data}{Data to plot}
+\item{data}{Data to plot (all data types recognised by ggplot2::geom_boxplot() like data.frame)}
 
-\item{x}{x-axis data}
+\item{x}{x-axis data, must be a Date object}
 
 \item{y}{y-axis data}
 
-\item{breaks}{Break points}
+\item{breaks}{Break points, must be a sequence of dates}
 
 \item{x_label}{x-axis label}
 
diff --git a/man/plot_dic.Rd b/man/plot_dic.Rd
index b92fa7d..631813e 100644
--- a/man/plot_dic.Rd
+++ b/man/plot_dic.Rd
@@ -7,10 +7,10 @@
 plot_dic(data)
 }
 \arguments{
-\item{data}{}
+\item{data}{List of parsed model outputs from "parse_model_output" (a list of lists)}
 }
 \value{
-ggplot2::ggplot
+ggplot2::ggplot with DIC values shown as points
 }
 \description{
 Plot Deviance Information Criterion (DIC) values
diff --git a/man/plot_line_average.Rd b/man/plot_line_average.Rd
index 778408f..d9ee39c 100644
--- a/man/plot_line_average.Rd
+++ b/man/plot_line_average.Rd
@@ -21,9 +21,9 @@ plot_line_average(
 )
 }
 \arguments{
-\item{data}{Data to plot}
+\item{data}{Data to plot (all data types recognised by ggplot2::geom_line() like data.frame)}
 
-\item{x}{x-axis data}
+\item{x}{x-axis data, must be a Date object}
 
 \item{y1}{y1 line data - solid}
 
@@ -31,7 +31,7 @@ plot_line_average(
 
 \item{y3}{y3 line data - dashed}
 
-\item{breaks}{Breaks vector}
+\item{breaks}{Breaks vector, must be a sequence of dates}
 
 \item{x_label}{x-axis label}
 
diff --git a/man/plot_line_comparison.Rd b/man/plot_line_comparison.Rd
index b185b7d..7846a69 100644
--- a/man/plot_line_comparison.Rd
+++ b/man/plot_line_comparison.Rd
@@ -4,15 +4,17 @@
 \alias{plot_line_comparison}
 \title{Plot line comparison for stdev etc}
 \usage{
-plot_line_comparison(data, to_plot, title)
+plot_line_comparison(data, to_plot, title = to_plot)
 }
 \arguments{
-\item{data}{Parsed model output}
+\item{data}{List of parsed model outputs from "parse_model_output" (a list of lists)}
 
 \item{to_plot}{Type of data to plot, "Range for f" etc}
+
+\item{title}{Title of the plot, defaults to the value of "to_plot"}
 }
 \value{
-ggplot2::ggplot
+ggplot2::ggplot of the selected hyperparameter posterior distribution
 }
 \description{
 Plot line comparison for stdev etc
diff --git a/man/plot_map.Rd b/man/plot_map.Rd
index 75c2f3d..5f039cf 100644
--- a/man/plot_map.Rd
+++ b/man/plot_map.Rd
@@ -22,13 +22,13 @@ plot_map(
 )
 }
 \arguments{
-\item{polygon_data}{Polygon data}
+\item{polygon_data}{Polygon data (SpatialPolygon or SpatialPolygonDataFrame)}
 
-\item{raster_data}{Raster datas}
+\item{raster_data}{Raster data (RasterLayer or SpatialRaster)}
 
-\item{domain}{Domain data to be passed to leaflet::colorNumeric and leaflet::addLegend}
+\item{domain}{Domain data (numeric or factor) to be passed to leaflet::colorNumeric and leaflet::addLegend}
 
-\item{markers}{Markers to display on map. A named list with latitude, longitude and label names must be given.}
+\item{markers}{Markers to display on map. A named list or data.frame with latitude, longitude and label names must be given.}
 
 \item{palette}{Palette to be used for colours, defaults to viridis}
 
diff --git a/man/plot_map_leaflet.Rd b/man/plot_map_leaflet.Rd
index b6e583c..cb07cfe 100644
--- a/man/plot_map_leaflet.Rd
+++ b/man/plot_map_leaflet.Rd
@@ -21,13 +21,13 @@ plot_map_leaflet(
 )
 }
 \arguments{
-\item{polygon_data}{Polygon data}
+\item{polygon_data}{Polygon data (SpatialPolygon or SpatialPolygonDataFrame)}
 
-\item{raster_data}{Raster data}
+\item{raster_data}{Raster data (RasterLayer or SpatialRaster)}
 
-\item{domain}{Domain data to be passed to leaflet::colorNumeric and leaflet::addLegend}
+\item{domain}{Domain data (numeric or factor) to be passed to leaflet::colorNumeric and leaflet::addLegend}
 
-\item{markers}{Markers to display on map. A named list with latitude, longitude and label names must be given.}
+\item{markers}{Markers to display on map. A named list or data.frame with latitude, longitude and label names must be given.}
 
 \item{palette}{Palette to be used for colours, defaults to viridis}
 
diff --git a/man/plot_mesh.Rd b/man/plot_mesh.Rd
index 9656973..0bf7e75 100644
--- a/man/plot_mesh.Rd
+++ b/man/plot_mesh.Rd
@@ -13,20 +13,20 @@ plot_mesh(
 )
 }
 \arguments{
-\item{mesh}{Mesh data}
+\item{mesh}{Mesh object from INLA or fmesher}
 
 \item{spatial_data}{Spatial data, either a SpatialPolygonsDataFrame, SpatialPointsDataFrame or an object
 that can be converted to a data.frame with longitude and latitude columns}
 
-\item{longitude_column}{Longitude column in spatial_data}
+\item{longitude_column}{Longitude column name in spatial_data}
 
-\item{latitude_column}{Latitude column in spatial_data name}
+\item{latitude_column}{Latitude column name in spatial_data}
 
 \item{markers}{Markers to display on top of mesh. A named list with latitude, longitude and label names must be given.
 Expects longitude name to be longitude, latitude name to be latitude, label name to be label.}
 }
 \value{
-leaflet::leaflet
+leaflet::leaflet with mesh and markers
 }
 \description{
 Plot a mesh on a Leaflet map
diff --git a/man/plot_priors_boxplot.Rd b/man/plot_priors_boxplot.Rd
index e7ee38d..b1d9178 100644
--- a/man/plot_priors_boxplot.Rd
+++ b/man/plot_priors_boxplot.Rd
@@ -7,10 +7,10 @@
 plot_priors_boxplot(data)
 }
 \arguments{
-\item{data}{}
+\item{data}{A list of parsed model output from "parse_model_output" (a list of lists)}
 }
 \value{
-graphics::boxplot
+graphics::boxplot of fitted values
 }
 \description{
 Create boxplots from priors run data
diff --git a/man/plot_priors_density.Rd b/man/plot_priors_density.Rd
index c840ab5..8b82701 100644
--- a/man/plot_priors_density.Rd
+++ b/man/plot_priors_density.Rd
@@ -7,12 +7,12 @@
 plot_priors_density(data, measurement_data)
 }
 \arguments{
-\item{data}{Parsed model outputs}
+\item{data}{List of parsed model outputs from "parse_model_output" (a list of lists)}
 
-\item{measurement_data}{Measurement data}
+\item{measurement_data}{Measurement data (can be data.frame, SpatialPoints/SpatialPointsDataFrame, or simple feature collection)}
 }
 \value{
-ggplot2::ggplot
+ggplot2::ggplot of measurement density by value
 }
 \description{
 Plot density function
diff --git a/man/plot_timeseries.Rd b/man/plot_timeseries.Rd
index 1c948b7..3cbb1a4 100644
--- a/man/plot_timeseries.Rd
+++ b/man/plot_timeseries.Rd
@@ -20,13 +20,13 @@ plot_timeseries(
 )
 }
 \arguments{
-\item{data}{Data to plot}
+\item{data}{Data to plot (data.frame with x-axis column a character convertible to Date)}
 
-\item{x}{Name of column to plot on x-axis, should be datetime, will be converted to Dates using as.Date}
+\item{x}{Name of column to plot on x-axis}
 
 \item{y}{Name of column to plot on y-axis}
 
-\item{breaks}{Date break points}
+\item{breaks}{Date break points, must be a sequence of dates}
 
 \item{x_label}{x-axis label}
 
@@ -40,9 +40,9 @@ plot_timeseries(
 
 \item{vertical_x}{x-intercept for vertical line}
 
-\item{x_lim}{Limits for x-axis continous scale, vector passed to scale_x_continuous}
+\item{x_lim}{Limits for x-axis continuous scale, vector passed to scale_x_continuous}
 
-\item{y_lim}{Limits for y-axis continuous scale, vector passed to scale_y_continous}
+\item{y_lim}{Limits for y-axis continuous scale, vector passed to scale_y_continuous}
 
 \item{line_width}{Line width}
 }
diff --git a/man/retrieve_tutorial_data.Rd b/man/retrieve_tutorial_data.Rd
index 07c6d2a..d6006fb 100644
--- a/man/retrieve_tutorial_data.Rd
+++ b/man/retrieve_tutorial_data.Rd
@@ -2,15 +2,17 @@
 % Please edit documentation in R/util_retrieve.R
 \name{retrieve_tutorial_data}
 \alias{retrieve_tutorial_data}
-\title{Retrieve a tutorial dataset and unpacks it to ~/fdmr/tutorial_data}
+\title{Retrieves a tutorial dataset and unpacks it to a place specified by the user (~/fdmr/tutorial_data)}
 \usage{
-retrieve_tutorial_data(dataset, force_update = FALSE)
+retrieve_tutorial_data(dataset, force_update = FALSE, save = FALSE)
 }
 \arguments{
 \item{dataset}{Name of dataset to retrieve}
 
 \item{force_update}{Force retrieval of metadata and dataset}
+
+\item{save}{Unpack the dataset to where user specified (character), home directory (TRUE), session's temporary directory (FALSE: default).}
 }
 \description{
-Retrieve a tutorial dataset and unpacks it to ~/fdmr/tutorial_data
+Retrieves a tutorial dataset and unpacks it to a place specified by the user (~/fdmr/tutorial_data)
 }
diff --git a/vignettes/expected_data_structure.Rmd b/vignettes/expected_data_structure.Rmd
index 8a1f1ec..a0a6084 100644
--- a/vignettes/expected_data_structure.Rmd
+++ b/vignettes/expected_data_structure.Rmd
@@ -18,6 +18,7 @@ In this tutorial, we will show the expected data structure for running the Bayes
 In the [COVID-19 tutorial](https://4dmodeller.github.io/fdmr/articles/covid.html), we aim to fit a Bayesian spatio-temporal model to predict the COVID-19 infection rates across mainland England over space and time, and investigate the impacts of socioeconomic, demographic and environmental factors on COVID-19 infection. We load the dataset `covid19_data` and the type of this object is a `data.frame`. 
 
 ```{r classcovidat}
+fdmr::retrieve_tutorial_data(dataset = "covid")
 covid19_data <- fdmr::load_tutorial_data(dataset = "covid", filename = "covid19_data.rds")
 class(covid19_data)
 ```
diff --git a/vignettes/meshbuilder.Rmd b/vignettes/meshbuilder.Rmd
index 7a02978..0b586d5 100644
--- a/vignettes/meshbuilder.Rmd
+++ b/vignettes/meshbuilder.Rmd
@@ -54,7 +54,7 @@ sp_data <- fdmr::load_tutorial_data(dataset = "covid", filename = "spatial_data.
 head(sp_data)
 ```
 
-The `sp_data` object is a `SpatialPolygonsDataFrame` containing 6789 features for areas of England. This object contains all the  contains all the values we
+The `sp_data` object is a `SpatialPolygonsDataFrame` containing 6789 features for areas of England. This object contains all the values we need to build a mesh.
 We can build a mesh by passing `sp_data` to the `mesh_builder` function.
 
 ```{r eval=FALSE}