🐦 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.

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1. Repository Structure

1.1 data/ — datasets used in the project

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

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▶️ 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().

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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.

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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.

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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.

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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.

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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.

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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"))