Q. Data on the movement of people?

Dewey Data includes:

• Advan Research: Aggregated raw counts of visits to POIs from a panel of mobile devices over a given month, detailing how often people visit, how long they stay, where they came from, where else they go, and more. The Advan Monthly Patterns dataset includes visitor and demographic aggregations for points of interest (POIs) in the US over the course of a month. This contains aggregated raw counts of visits to POIs from a panel of mobile devices, answering how often people visit, how long they stay, where they came from, where else they go, and more. Data is anonymized and aggregated to provide insights into the volume of visitors to certain locations and overall behavioral patterns. Also included in this download are the SafeGraph Places and Geometry datasets which can be added to Patterns via the Placekey unique identifier for further context. Historical data is available back to 2019.
• Advan Neighborhood Patterns dataset contains footfall data aggregated by census block group (CBG) over the course of a month. Neighborhood Patterns show how the population moves between different areas, in terms of both volume and frequency. This dataset also breaks down what time of day certain areas are busiest, and how people travel throughout the day and week. Historical data is available back to 2019.
• Neighborhood Patterns dataset contains footfall data aggregated by dissemination area (DA) in Canada over the course of a month. Neighborhood Patterns shows how the population moves between different areas, in terms of both volume and frequency. This dataset also breaks down what time of day certain areas are busiest, and how people travel throughout a day and week. Historical data is available back to 2019.
• Pass_by which includes retail store visits. Starts in 2024.
• SafeGraph Global Places and Geometry data provides points of interest (POIs) and building footprints for any place in the world that is not a private residence. Attributes for each POI include place name, brand affiliation, address string, lat/long coordinate, NAICS code and category, detailed category tags, and more. Attributes for each building footprint include location name, area (square meters), polygon type (synthetic or real), whether or not the polygon is enclosed or owned by another, and related parking. The two datasets can be easily joined via the Placekey unique identifier to provide more context about each place and how places relate to each other. POIs can be easily mapped with latitude and longitude coordinates or address string, and building footprints can be mapped using the well-known text (WKT) column. Historical data is available back to 2019.
• SafeGraph Spend data aggregates anonymized credit and debit transactions at specific points of interest over the course of a month. Attributes include aggregated transaction volume and amounts, as well as transaction intermediary (Apple Pay, Doordash, etc.), and anonymized customer details. Spend data is available for both online and offline transactions. This data is available for the entire US from 2019 to present.
• SafeGraph Parking Lots is a collection of geometry rows depicting the shape and size of surface parking lots in the US. A column called related_parking is appended to the end of the Places and Geometry schema to show the relationship between places and the surrounding parking lot(s) likely serving those POIs. ~6M U.S. places currently have an associated parking lot(s) mapped in the related_parking column.