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linkeR: Effortless Linked Views for ‘shiny’ Applications

Create synchronized, interactive dashboards where one click updates multiple components

linkeR makes it effortless to create linked views in ‘shiny’ applications. When users interact with one component (like clicking a map marker), all related components (tables, charts, other maps) automatically update to show corresponding information.

What linkeR Does

Bidirectional Linking: Click a map marker → table row highlights. Click table row → map zooms and shows popup.
One-Line Setup: Link multiple components with a single function call
Custom Behaviors: Define exactly what happens when users click different components
Multi-Component Support: Link maps, tables, charts, and more in complex dashboards
Zero Boilerplate: No manual observer setup or event handling required

Why Use linkeR?

Before linkeR (Manual Approach)

# Complex manual setup for each component pair
observeEvent(input$map_marker_click, {
  clicked_id <- input$map_marker_click$id
  # Find corresponding table row
  row_idx <- which(my_data()$id == clicked_id)
  # Update table selection
  dataTableProxy("my_table") %>% selectRows(row_idx)
  # Update map view
  leafletProxy("my_map") %>% setView(...)
  # Update any other components...
  # Repeat this for every component combination!
})

observeEvent(input$my_table_rows_selected, {
  # More boilerplate code...
  # Handle edge cases...
  # Ensure consistency...
})

With linkeR (Simple Approach)

# One line links everything!
link_plots(
  session,
  my_map = my_data,
  my_table = my_data,
  shared_id_column = "id"
)

Key Benefits

Manual Approach	linkeR Approach
50+ lines of observer code	1 function call
Easy to introduce bugs	Tested and reliable
Hard to maintain	Declarative and clear
Limited to 2 components	Unlimited components
No built-in customization	Rich customization options

Installation

# Install from CRAN (when available)
install.packages("linkeR")

# Or install development version from GitHub
# install.packages("devtools")
devtools::install_github("EpiForeSITE/linkeR")

Requirements

For linking to work, your setup needs:

Shared ID Column: All datasets must have a common identifier column
Matching Component IDs:
- Leaflet: Use layerId = ~your_id_column
- DT: Row numbers automatically map to data rows
Reactive Data: Wrap your data in reactive()

# Good: Proper setup
my_data <- reactive({
  data.frame(
    id = 1:10,           # ← Shared ID column
    name = paste("Item", 1:10),
    lat = runif(10), lng = runif(10)
  )
})

output$my_map <- renderLeaflet({
  leaflet(my_data()) %>%
    addMarkers(layerId = ~id)  # ← layerId matches shared_id_column
})

link_plots(session, my_map = my_data, shared_id_column = "id")

# Bad: Missing layerId
output$my_map <- renderLeaflet({
  leaflet(my_data()) %>%
    addMarkers()  # ← No layerId = no linking!
})

Supported Components

Component	Status	Notes
Leaflet Maps	✅ Full Support	Interactive maps with markers, circles, polygons
DT DataTables	✅ Full Support	Sortable, filterable tables
Plotly Charts	🔄 Partial	Requires manual event handling
Custom Components	🔄 Partial	Any ‘shiny’ component with click events, Requires manual event handling
Base R Plots	📋 Planned	Static plots with click detection
Mapbox	📋 Planned	Alternative mapping solution

Contributing

Contributions are welcome and encouraged! Follow best practice for github contributions.

Development Setup

# Clone and setup
git clone https://github.com/EpiForeSITE/linkeR.git
cd linkeR

# Install dependencies
devtools::install_deps()

# Run tests
devtools::test()

# Check package
devtools::check()

License

This project is licensed under the MIT License - see the LICENSE file for details.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.