PULSE dataset

Motivation

This dataset is derived and cleaned from the full PULSE project dataset to share with others data gathered about the users during the project.

Disclaimer

Any third party need to respect ethics rules and GDPR and must mention “PULSE DATA H2020 - 727816” in any dissemination activities related to data being exploited. Also, you should provide a link to the project associated website: http://www.project-pulse.eu/

The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous.

Description of the dataset

The only difference with the original dataset comes from anonymised user information.

The dataset content is described in a dedicated JSON file:

{
    "citizen_id": "pseudonymized unique key of each citizen user in the PULSE system",
    "city_code": {
        "description": "3-letter city codes taken by convention from IATA codebook of airports and metropolitan areas, as the codebook of global cities in most common and widespread use and therefore adopted as standard in PULSE (since there is currently - in the year 2020 - still no relevant ISO or other standardized codebook of cities uniformly globally adopted and used). Exception is Pavia which does not have its own airport,and nearby Milan/Bergamo airports are not applicable, so the 'PAI' internal code (not existing in original IATA codes) has been devised in PULSE. For cities with multiple airports, IATA metropolitan area codes are used (New York, Paris).",
            "BCN": "Barcelona",
            "BHX": "Birmingham",
            "NYC": "New York",
            "PAI": "Pavia",
            "PAR": "Paris",
            "SIN": "Singapore",
            "TPE": "Keelung(Taipei)"
	},
	"zip_code": "Zip or postal code (area) within a city, basic default granular territorial/administrative subdivision unit for localization of citizen users by place of residence (in all PULSE cities)",
    "models": {
        "asthma_risk_score": "PULSE asthma risk consensus model score, decimal value ranging from 0 to 1",
        "asthma_risk_score_category": {
            "description": "Categorized value of the PULSE asthma risk consensus model score, with the following possible category options:",
            "low": "low asthma risk, score value below 0,05",
            "medium-low": "medium-low asthma risk, score value from 0,05 and below 0,1",
            "medium": "medium asthma risk, score value from 0,1 and below 0,15",
            "medium-high": "medium-high asthma risk, score value from 0,15 and below 0,2",
            "high": "high asthma risk, score value from 0,2 and higher"
			},
        "T2D_risk_score": "PULSE diabetes type 2 (T2D) risk consensus model score, decimal value ranging from 0 to 1",
        "T2D_risk_score_category": {
            "description": "Categorized value of the PULSE diabetes type 2 risk consensus model score, with the following possible category options:",
            "low": "low T2D risk, score value below 0,05",
            "medium-low": "medium-low T2D risk, score value from 0,05 and below 0,1",
            "medium": "medium T2D risk, score value from 0,1 and below 0,15",
            "medium-high": "medium-high T2D risk, score value from 0,15 and below 0,2",
            "high": "high T2D risk, score value from 0,2 and below 0,25",
            "very_high": "very high T2D risk, score value from 0,25 and higher"
            },
        "well-being_score": "PULSE well-being model score, decimal value ranging from -5 to 5",
        "well-being_score_category": {
            "description": "Categorized value of the PULSE well-being model score, with the following possible category options:",
            "low": "low well-being, score value below -0,37",
            "medium-low": "medium-low well-being, score value from -0,37 and below 0,04",
            "medium-high": "medium-high well-being, score value from 0,04 and below 0,36",
            "high": "high well-being, score value from 0,36 and higher"
            },
        "computed_time": "Timestamp (UTC) when each relevant model score value/result had been computed or derived"    
    }
}