DOI: 10.6084/m9.figshare.20170082
title: The iratebirds Citizen Science Project: a Dataset on Birds’ Visual Aesthetic Attractiveness to Humans

description: The iratebirds database contains comprehensive visual aesthetic attractiveness, as seen by humans, data for bird taxonomic units (following the eBird/Clements integrated checklist v. 2019). The data were collected with the iratebirds.app -website citizen science project, where users rated the appearance of birds on a linear scale from 1-10. The rating were based on photographs of the birds available from the Macaulay Library database. Each rating score of a bird species or subspecies is based on several photographs of the same bird species. The application code is openly available on GitHub: https://github.com/luomus/iratebirds The application was spread during August 2020 – April 2021, globally, to as wide audiences as possible using social media, traditional media, collaborators and email-lists.<br> The iratebirds database is based on 408 207 ratings from 6 212 users. It consists of raw visual aesthetic attractiveness rating data as well as complementary data from an online survey that sourced demographic information from a subset of 2 785 users who scored the birds. The online survey gives information on these users’ birding skills, nature connectedness, profession, home country, age and gender. On top of these, the data scores for birds’ visual aesthetic attractiveness to humans have been modelled with hierarchical models to obtain overall average scores for the bird species and subspecies. More details on the data are found in this file’s section “Methodological information” as well as in the publication Haukka, A. et al. (2023), The iratebirds Citizen Science Project: a Dataset on Birds’ Visual Aesthetic Attractiveness to Humans, Scientific Data. The full database "iratebirds_raw_data_taxonomy_photoinfo_ratings_survey_251022.csv" includes all the data related to the photographs scored (e.g. place and location of the photograph, and its quality), the species and subspecies names (following the eBird/Clements integrated checklist v. 2019), the raw scores made by the users, details of the users (e.g. language used), and internal user ID, and for the users who took the online survey, also detailed information about their demography, e.g. home country and other information related to their knowledge of and connection to nature and birds. The modeled rating scores database "iratebirds_final_predictions_average_fullmodel_subsetmodel_151122.csv" includes visual aesthetic attractiveness of birds, as perceived by humans, calculated in three different ways. The most appropiate score can be chosen by the user according to the specific research needs, but in general we recommend using the scores from the full model (ii). The three different measures are i) raw visual aesthetic attractiveness for each bird species (or subspecies), ii) full model: visual aesthetic attractiveness corrected for language group of the scorer and the quality of the photo scored, iii) subset model: visual aesthetic attractiveness corrected as in ii) plus other user specific factors (related to bird and nature knowlegde and connections, home country, age. and gender). The file also gives information on how many photos were used for scoring each bird and how many users have scored the species. The latter subset model iii) represents only a subset of all the species. The data on visual aesthetic attractiveness are also available at the species and the sex within-species level, for the sexually dichromatic species, in the file "iratebirds_pred_ratings_species_and_sex_level_120123.csv". <br> All database files are given both as .csv- and .xlsx -files. The data and code to reproduce the analyses, figures and tables presented in Haukka et al. 2023 The iratebirds citizen science project: a dataset of birds’ visual aesthetic attractiveness to humans (Scientific Data doi: https://doi.org/10.1038/s41597-023-02169-0) are included in the 'iratebirds_raw_data_taxonomy_photoinfo_ratings_survey_251022.csv' and 'Haukka_et_al_Scientific_Data_modelling.R','Haukka_et_al_Scientific_Data_Figure.R' and 'Haukka_et_al_Scientific_Data_Tables.R' -files. Detailed information on dataprosessing and models can be found in the publication Haukka et al. 2023 The iratebirds Citizen Science Project: a Dataset on Birds’ Visual Aesthetic Attractiveness to Humans, Scientific Data doi: https://doi.org/10.1038/s41597-023-02169-0)