Overview Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during COVID-19 pandemic. The smarty4covid dataset contains audio signals of cough (4,676), regular breathing (4,665), deep breathing (4,695) and voice (4,291) as recorded by means of mobile devices following a crowd-sourcing approach. Other self reported information is also included (e.g. COVID-19 virus tests), thus providing a comprehensive dataset for the development of COVID-19 risk detection models. The smarty4covid dataset is released in the form of a web-ontology language (OWL) knowledge base enabling data consolidation from other relevant datasets, complex queries and reasoning. Data structure The main directory is organized as shown below. Each directory contains the submissions of a specific user. The user directory is named after the user’s id. Apart from the submissions, a json file (“demographics_underlying_conditions.json”) with information regarding demographics (e.g. BMI, age group, gender) and potential underlying conditions is also included. Each submission corresponds to a separate sub-directory that is named after the unique submission id and it contains: 1. Audio recordings of cough (“audio.cough.mp3”), deep breathing (“audio.breath_deep.mp3”) and regular breathing (“audio.breath_regular.mp3”) 2. A json file (“main_questionnaire.json”) with information related to the COVID-19 test (result, type, and date), COVID-19 vaccination status, COVID-19 related symptoms, vital signs and more 3. A json file (“breathing_features.json”) with the extracted respiratory indicators and the manual annotations of the breathing phases (inhalation, exhalation) on the breathing audio signal 4. Four json files (“experts.breath.json”, “experts.cough.json”, “experts.medical_advice.json”, “experts.speech.json”) including the input/labels (characterization, advice) from the healthcare professionals. Finally, there is also a csv file “smarty4covid_tabular_data.csv”. This file contains any information available for every submission in the dataset. A detailed description of the various JSON files and their fields is provided in "smarty4covid_overview.pdf" file. ├── ... ├── <ParticipantID> │ ├── demographics_underlying_conditions.json │ ├── <SubmissionId1> │ │ ├── audio.breath_regular.mp3 │ │ ├── audio.breath_deep.mp3 │ │ ├── audio.cough.mp3 │ │ ├── main_questionnaire.json │ │ ├── breathing_features.json │ │ ├── experts.breath.json │ │ ├── experts.cough.json │ │ ├── experts.medical_advice.json │ │ └── experts.speech.json │ ├── ... │ └── <SubmissionIdN> │ ├── audio.breath_regular.mp3 │ ├── audio.breath_deep.mp3 │ ├── audio.cough.mp3 │ ├── main_questionnaire.json │ ├── breathing_features.json │ ├── experts.breath.json │ ├── experts.cough.json │ ├── experts.medical_advice.json │ └── experts.speech.json ├── ... ├── smarty4covid_tabular_data.csv ├── smarty4covid_overview.pdf ├── smarty-ontology.owl ├── smarty-triples.nt ├── Smarty4Covid experts info.xlsx └── readme.xlsx