The dataset consists of a .db file for each of Gothenburg's primary areas. Each .db file consists of five relational tables: a person table, a household table, a house table, a building table, and an OD_Matrix table. Person Table Column Name Data Type Constraint Description uuid TEXT PRIMARY KEY Unique identifier for each person uuid_household TEXT FOREIGN KEY Identifier linking to the household uuid_parent TEXT FOREIGN KEY Identifier linking to the parent person age INTEGER Age of the person sex TEXT Sex of the person type_household TEXT Type of household household TEXT Name or identifier of the household has_car BOOLEAN Indicates if the person has a car child_count INTEGER Number of children is_head BOOLEAN Indicates if the person is head of the household is_child BOOLEAN Indicates if the person is a child origin TEXT Origin location activity_sequence TEXT Sequence of activities primary_status TEXT Primary status of the person age_group TEXT Age group of the person location_work TEXT Work location type_house TEXT Type of house has_child BOOLEAN Indicates if the person has children location_mapping TEXT Mapping of locations Household Table Column Name Data Type Constraint Description uuid TEXT PRIMARY KEY Unique identifier for each household name_category TEXT Category name count_children INTEGER Number of children in the household bool_children BOOLEAN Indicates if there are children in the household count_adults INTEGER Number of adults in the household count_members INTEGER Total number of members in the household uuid_members TEXT Identifiers of the household members type_house TEXT Type of house uuid_house TEXT FOREIGN KEY Identifier linking to the house count_cars INTEGER Number of cars in the household head_of_household TEXT FOREIGN KEY Identifier linking to the head of the household House Table Column Name Data Type Constraint Description uuid TEXT PRIMARY KEY Unique identifier for each house uuid_household TEXT FOREIGN KEY Identifier linking to the household uuid_building TEXT FOREIGN KEY Identifier linking to the building count_members INTEGER Number of members in the house count_adults INTEGER Number of adults in the house count_children INTEGER Number of children in the house count_cars INTEGER Number of cars in the household area_square_meters TEXT Area of the house in square meters Building Table Column Name Data Type Constraint Description uuid TEXT PRIMARY KEY Unique identifier for each building type_building TEXT Type of building area_square_meters REAL Area of the building in square meters height_meters REAL Height of the building in meters count_floors INTEGER Number of floors in the building population_per_floor INTEGER Population per floor population_total INTEGER Total population in the building built_up_area REAL Built-up area count_workers INTEGER Number of workers in the building is_empty BOOLEAN Indicates if the building is empty building TEXT Name or identifier of the building (consider revising this column's necessity) coord TEXT Coordinates of the building preferred_locations TEXT Preferred locations related to the building OD_Matrix Table Column Name Data Type Constraint Description uuid TEXT PRIMARY KEY Unique identifier for each OD matrix entry origin TEXT FOREIGN KEY Origin building identifier destination TEXT FOREIGN KEY Destination building identifier mode TEXT Mode of transportation distance REAL Distance of the trip duration REAL Duration of the trip Changelog v0.0.2 Improved validation Updated mode choice prediction Improved public transit routing Calibrated job assignment Added mode-choice enforcement for mode: Car (Until a home trip where mode can change again) Calibrated potential destinations to median travel distance

A synthetic population is a distribution of synthetic agents that replicates the demographic distribution of a real-world population according to census records.This dataset contains a synthetic population of residents in the city of Gothenburg in Sweden, along with activity schedules and mobility patterns for 2019. The synthetic population model is designed for applications in neighbourhood planning and includes detailed replicas of people in different neighbourhoods of Gothenburg organized as persons, households, houses, buildings, and daily activity chains. While the persons, households, and houses are synthetic replicas, they are connected to existing buildings.The model considers the allocation of primary and secondary locations based on a gravity model, realistic routing for active, public and private motorised modes of transportation and allows users to introduce new buildings and amenities if needed. The population data is provided as an SQLite3 database file for each neighbourhood of Gothenburg.