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🐦 SPI-Birds Hackathon — November 25–26, 2025

This repository was created during a hackathon aimed at developing an interactive Shiny App to visualize age distribution across different bird species and locations.
The objective was to build a simple tool to illustrate differences in life-history strategies, using long-term monitoring data in birds.

1. Repository Structure

1.1 data/ — datasets used in the project

  • individual_data.csv
  • site_codes.csv
  • species_codes.csv
  • nest_data.csv

▶️ Detailed data/ repository

(Click to expand)

📁 data repository (click)

This folder contains datasets used in app.R. Importing function is already embedded in app.R but it is possible to import files directly using read.csv() or readr::read_csv().

individual_data.csv

Simulated dataset containing counts of individuals by year, species, location, minimum age, and sex.

Variable Type Description
siteID character (3 letters) Study site identifier. No missing values.
speciesID character (6 letters) Species code (genus + species). No missing values.
captureYear integer (4 digits) Year of capture. No missing values.
minimumAge integer (1–2 digits) Real age when known; otherwise minimum possible age.
observedSex character (F/M/U/NA) Sex of the individual. Missing values allowed (NA).
n integer Sample size per population per year.

site_codes.csv

SPI-Birds table with information about site locations.
Current version available on the SPI-Birds pipeline repository.

Variable Type Description
siteID character (3 letters) Study site identifier. No missing values.
siteName character Name of the study site.
country character Country name. No missing values.
countryCode character (2 letters) Country ISO-like code. No missing values.
decimalLatitude numeric Latitude (WGS84). Missing values allowed.
decimalLongitude numeric Longitude (WGS84). Missing values allowed.
locationAccordingTo character Source of geographic information.

species_codes.csv

SPI-Birds table with species-related information.
Current version available on the SPI-Birds pipeline repository.

Variable Type Description
speciesCode numeric (6 digits) SPI-Birds species code. No missing values.
speciesID character (6 letters) SPI-Birds standard 1.0 species code. No missing values.
speciesEURINGcode integer European bird ringing code. Missing values allowed.
speciesCOLID alphanumeric Catalogue of Life identifier. Missing values allowed.
speciesEOLpageID integer Encyclopedia of Life identifier. No missing values.
kingdom / phylum / class / order / family character Taxonomic classification.
genus character Genus name.
specificEpithet character Species epithet.
scientificNameAuthorship character Reference describing the taxon concept.
vernacularName character English common name.

nest_data.csv

Dataset designed to provide an additional visualization related to breeding phenology.
Based on real data but should be modified for simulated data with more variation across species.

Variable Type Description
studyID alphanumeric (5 chars) Population where data were collected. No missing values.
speciesID character (6 letters) Species code. No missing values.
observedLayYear integer (4 digits) Estimated laying year. Missing values allowed (NA).
mean_clutch integer Rounded mean number of eggs per clutch. Missing values allowed.
min_clutch / max_clutch integer Minimum / maximum clutch size. Missing values allowed.
mean_brood integer Rounded mean number of hatched chicks. Missing values allowed.
min_brood / max_brood integer Minimum / maximum brood size. Missing values allowed.
mean_fledge integer Rounded mean number of fledglings. Missing values allowed.
min_fledge / max_fledge integer Minimum / maximum fledgling counts. Missing values allowed.
n_row integer Sample size per population per year.

2. Main Files

  • app.R
    Code required to run the Shiny application.

  • dataset_sim.R
    Script used to generate the simulated individual_data dataset.

  • getdata_function.R
    Function used to import and process data.

3. How to Run the App

You will need R and the Shiny package installed.

3.1 Install required packages

install.packages(c("shiny", "tidyverse"))