useR 2025: Presentations and Sessions

The lineup of presentations scheduled at useR! 2025, categorized by session and date.

About the Data

This week’s dataset comes from the useR! 2025 conference, an annual gathering of R users, developers, and enthusiasts hosted by Duke University in Durham, NC, USA, from August 8–10, 2025 (with a virtual event on August 1). The data, curated by Mine Çetinkaya-Rundel, includes the full schedule of sessions—talks, tutorials, posters, and more—sourced from the conference’s submission portal. It contains metadata such as session titles, speakers, abstracts, room locations, and whether a video recording will be available. The dataset, available via the tidytuesdayR R package or directly from GitHub, invites exploration of themes, trends, and opportunities at the conference. Full program details for both virtual and in-person formats are available on the useR! 2025 website. Participants are encouraged to share their analyses using the hashtag #useR2025.

Figure 1: This graphic displays the lineup of presentations scheduled at useR! 2025, categorized by session and date. Each session is color-coded, with individual talk titles aligned along the y-axis. Horizontal markers group presentations under their respective sessions, while vertical labels indicate the conference dates. Annotations and spacing help highlight the structure of the event, giving a clear visual summary of when and where each talk is taking place.

How I made this graphic?

To visualize the schedule of presentations at useR! 2025, I first loaded and wrangled the session data using packages from the tidyverse ecosystem, including dplyr for data manipulation and ggplot2 for plotting. I utilized showtext to enable the use of custom Google Fonts and ggtext for styled markdown in text elements. fontawesome icons were embedded to add social media logos in the caption. The session metadata was then arranged using grouping and summarisation to calculate vertical spacing and alignment. I used patchwork for potential compositional flexibility (though not shown here), and magick along with ggimage to include the conference logo directly on the plot. Color palettes were selected with help from colorspace and cols4all. The final plot features titles, sessions, and dates placed precisely along the x-axis, using customized axes, fonts, and layout controls. Everything was neatly saved using ggsave() with background color and precise dimensions for clarity in publication or sharing.

Loading required libraries

pacman::p_load(
  tidyverse,            # All things tidy
  
  scales,               # Nice Scales for ggplot2
  fontawesome,          # Icons display in ggplot2
  ggtext,               # Markdown text support for ggplot2
  showtext,             # Display fonts in ggplot2
  colorspace,           # Lighten and Darken colours
  
  magick,               # Download images and edit them
  ggimage,              # Display images in ggplot2
  patchwork,            # Composing Plots
  ggbrace               # Drawing Curly braces in ggplot2
)

# Option 2: Read directly from GitHub

user2025 <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-04-29/user2025.csv')

user_logo <- image_read("https://user2025.r-project.org/img/logo.png")

Visualization Parameters

# Font for titles
font_add_google("Saira",
  family = "title_font"
) 

# Font for the caption
font_add_google("Saira Extra Condensed",
  family = "caption_font"
) 

# Font for plot text
font_add_google("Saira Condensed",
  family = "body_font"
) 

showtext_auto()

# cols4all::c4a_gui()

mypal <- c("#2165B6", "#B3B3B3")

# A base Colour
bg_col <- "white"
seecolor::print_color(bg_col)

# Colour for highlighted text
text_hil <- "grey40"
seecolor::print_color(text_hil)

# Colour for the text
text_col <- "grey40"
seecolor::print_color(text_col)

line_col <- "grey40"

# Define Base Text Size
bts <- 90

# Caption stuff for the plot
sysfonts::font_add(
  family = "Font Awesome 6 Brands",
  regular = here::here("docs", "Font Awesome 6 Brands-Regular-400.otf")
)
github <- "&#xf09b"
github_username <- "aditya-dahiya"
xtwitter <- "&#xe61b"
xtwitter_username <- "@adityadahiyaias"
social_caption_1 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{github};</span> <span style='color: {text_hil}'>{github_username}  </span>")
social_caption_2 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{xtwitter};</span> <span style='color: {text_hil}'>{xtwitter_username}</span>")
plot_caption <- paste0(
  "**Data:**  Mine Çetinkaya-Rundel, PositPBC", 
  " |  **Code:** ", 
  social_caption_1, 
  " |  **Graphics:** ", 
  social_caption_2
  )
rm(github, github_username, xtwitter, 
   xtwitter_username, social_caption_1, 
   social_caption_2)

# Add text to plot-------------------------------------------------
plot_subtitle <- "Presentations scheduled in useR! 2025 at Duke University"

Exploratory Data Analysis and Wrangling

pacman::p_load(summarytools)
user2025 |> 
  dfSummary() |> 
  view()

user2025 |> 
  select(title)

user2025 |> 
  count(session, sort = T) |> View()

pacman::p_load(tidytext)

user2025 |> 
  select(keywords) |> 
  unnest_tokens(word, keywords) |> 
  count(word, sort = T)

df1 <- user2025 |> 
  select(date, session, title, speakers) |> 
  arrange(desc(date), session) |> 
  mutate(
    online = date == as_date("2025-08-01")
  ) |> 
  mutate(
    y_var = row_number()
  )

df2 <- df1 |> 
  group_by(date) |> 
  summarise(
    y_mean = mean(y_var),
    y_min = min(y_var),
    y_max = max(y_var)
  ) |> 
  mutate(date = paste(day(date), month(date, label = TRUE, abbr = FALSE)))

df3 <- df1 |> 
  group_by(date, session) |> 
  summarise(
    y_mean = mean(y_var),
    y_min = min(y_var),
    y_max = max(y_var)
  )

# Get colour palette from {cols4all}
# cols4all::c4a_gui()
mypal2 <- c("#2E91E5", "#E15F99", "#1CA71C", "#FB0D0D", "#DA16FF", "#222A2A", "#B68100", "#750D86", "#EB663B", "#511CFB", "#00A08B", "#FB00D1", "#FC0080", "#B2828D", "#6C7C32", "#778AAE", "#862A16", "#A777F1", "#620042", "#1616A7", "#DA60CA", "#6C4516", "#0D2A63")

The Plot

g <- df1 |> 
  ggplot(
    mapping = aes(
      y = y_var
    )
  ) +
  geom_text(
    mapping = aes(
      label = title,
      colour = session,
      group = session,
      x = -0.05
    ),
    family = "title_font",
    size = bts / 10,
    hjust = 1
  ) +
  
  # SESSION -----------------------------------
  geom_text(
    data = df3,
    mapping = aes(
      label = session,
      y = y_mean,
      x = 0.005,
      colour = session
    ),
    angle = 0,
    family = "caption_font",
    size = bts / 4,
    hjust = 0
  ) +
  geom_errorbar(
    data = df3,
    mapping = aes(
      x = 0,
      ymin = y_min,
      ymax = y_max,
      y = y_mean,
      colour = session
    ),
    linetype = 1,
    width = 0.01
  ) +
  
  # DATE -----------------------------------
  geom_text(
    data = df2,
    mapping = aes(
      label = date,
      y = y_mean,
      x = 0.25
    ),
    angle = -90,
    family = "body_font",
    colour = text_hil,
    size = bts / 2
  ) +
  geom_errorbar(
    data = df2,
    mapping = aes(
      x = 0.22,
      ymin = y_min,
      ymax = y_max,
      y = y_mean
    ),
    colour = text_col,
    linetype = 1,
    width = 0.05
  ) +
  
  # ADD LOGO ------------------------------------------------------
  annotation_custom(
    grid::rasterGrob(user_logo),
    xmin = -0.83, xmax = -0.38, 
    ymin = 105, ymax = 130
  ) +
  
  annotate(
    geom = "text",
    label = plot_subtitle,
    angle = 90,
    x = -0.7,
    y = 55,
    family = "body_font",
    size = bts / 1.45,
    # fontface = "bold",
    hjust = 0.5,
    vjust = 1,
    colour = text_hil
  ) +
  # stat_brace(
  #   mapping = aes(
  #     colour = session,
  #     group = session,
  #     x = -0.5
  #   ),
  #   rotate = -90,
  #   width = 0.2
  # ) +
  # stat_bracetext(
  #   mapping = aes(
  #     colour = session,
  #     group = session,
  #     label = session,
  #     x = -0.8
  #   ),
  #   rotate = -90,
  #   family = "caption_font",
  #   hjust = 0
  # ) +
  scale_y_continuous(
    expand = expansion(0)
  ) +
  scale_x_continuous(
    limits = c(-0.8, 0.28),
    expand = expansion(0)
  ) +
  scale_colour_manual(values = mypal2) +
  coord_cartesian(clip = "off") +
  theme(
    legend.position = "none"
  ) +
  labs(
    caption = plot_caption,
    x = NULL,
    y = NULL
  ) +
  theme_void(
    base_family = "body_font",
    base_size = bts
  ) +
  theme(
    
    # Overall
    plot.margin = margin(5,5,5,5, "mm"),
    legend.position = "none",
    plot.title.position = "plot",
    panel.background = element_rect(
      fill = NA, colour = NA
    ),
    
    text = element_text(
      colour = text_col,
      lineheight = 0.3,
      hjust = 0.5
    ),
    
    # Labels and Strip Text
    plot.subtitle = element_text(
      colour = text_hil,
      margin = margin(5,0,5,0, "mm"),
      size = bts,
      lineheight = 0.3,
      hjust = 0.5
    ),
    plot.caption = element_textbox(
      margin = margin(5,0,0,0, "mm"),
      hjust = 0.5,
      colour = text_hil,
      size = 0.6 * bts,
      family = "caption_font"
    ),
    plot.caption.position = "plot"
  )

ggsave(
  filename = here::here(
    "data_vizs",
    "tidy_useR_2025.png"
  ),
  plot = g,
  width = 400,
  height = 520,
  units = "mm",
  bg = bg_col
)

Savings the thumbnail for the webpage

# Saving a thumbnail

library(magick)

# Saving a thumbnail for the webpage
image_read(here::here("data_vizs", 
                      "tidy_useR_2025.png")) |> 
  image_resize(geometry = "x400") |> 
  image_write(
    here::here(
      "data_vizs", 
      "thumbnails", 
      "tidy_useR_2025.png"
    )
  )

Session Info

pacman::p_load(
  tidyverse,            # All things tidy
  
  scales,               # Nice Scales for ggplot2
  fontawesome,          # Icons display in ggplot2
  ggtext,               # Markdown text support for ggplot2
  showtext,             # Display fonts in ggplot2
  colorspace,           # Lighten and Darken colours
  
  magick,               # Download images and edit them
  ggimage,              # Display images in ggplot2
  patchwork,            # Composing Plots
  ggbrace               # Drawing Curly braces in ggplot2
)

sessioninfo::session_info()$packages |> 
  as_tibble() |> 
  select(package, 
         version = loadedversion, 
         date, source) |> 
  arrange(package) |> 
  janitor::clean_names(
    case = "title"
  ) |> 
  gt::gt() |> 
  gt::opt_interactive(
    use_search = TRUE
  ) |> 
  gtExtras::gt_theme_espn()

Table 1: R Packages and their versions used in the creation of this page and graphics