European Trade Fairs Monitor

Thomas Lizzi
2025-11-24

Visualizing Event Concentration Across Europe

The Problem: Data Visibility

The Challenge: Stakeholders and event organizers often have lists of hundreds of trade fairs stored in Excel spreadsheets. It is difficult to:

  • Visualize where events are concentrated.
  • Compare event density between different years.
  • Quickly access details for specific locations without scrolling through rows of data.

The Solution: The European Trade Fairs Monitor is a Shiny application that transforms raw data into an interactive, geographical insight tool.

App Architecture: The Interface

The User Interface (UI) is designed for simplicity:

1. The Sidebar (Control Panel):

  • Year Selector: Filters the entire dataset instantly.
  • Size Slider: Allows the user to scale the visual impact of the bubbles based on event count.

2. The Main Panel:

  • Dynamic Header: Displays the total count of events and the “Top Location” for that year.
  • Interactive Map: A full-width Leaflet map that supports zooming, panning, and clicking.

App Architecture: The Logic

To prevent map clutter (thousands of dots on top of each other), the app performs Smart Aggregation:

  1. Grouping: The server groups raw data by City and Country.
  2. Averaging: It calculates the mean Latitude/Longitude for the city to center the marker.
  3. Counting: It counts the number of events to determine the bubble radius.
    • Formula: \( Radius = 4 + (Count \times Multiplier) \)
  4. Popup Generation: It compiles all event names into a single HTML list inside the popup.

The Data Structure

The application utilizes a dataset of European trade fairs. The data is pre-processed to geocode city names into coordinates.

Here is a live sample of the data structure:

# Embedded R Code: Generating a sample view of the data structure
# This code runs when the slides are compiled
sample_data <- data.frame(
  Year = c(2024, 2024, 2025),
  City = c("Milan", "Paris", "Berlin"),
  Event = c("Salone del Mobile", "Fashion Week", "IFA Tech"),
  Lat = c(45.4642, 48.8566, 52.5200)
)

print(sample_data)
  Year   City             Event     Lat
1 2024  Milan Salone del Mobile 45.4642
2 2024  Paris      Fashion Week 48.8566
3 2025 Berlin          IFA Tech 52.5200