place

A collection of 34 posts

CityDash for San Francisco Bay Area cities

CityDash for San Francisco Bay Area cities

C [http://lotadata.com/]ITYDATA.ai transforms time and place into actionable context for smart cities, enterprise businesses, mobile apps and wearables. STIR 2016 One of the few companies selected to join STIR

Top 5 Mobile Gaming Micro-moments

Top 5 Mobile Gaming Micro-moments

Mobile gamers are an interesting bunch. We should know. We are them. The typical mobile gaming session transpires at home and at work, through commutes, across multiple different places and venues, intertwining in-game

Frank Underwood vs. Donald Trump

Frank Underwood vs. Donald Trump

The data scientists at CITYDATA.ai take a look at the presidential matchup that we all wish could happen. Excited at the prospect of rambunctious contested conventions? Giddy with anticipation as major political

Making Sense of the Census: Polygons

Making Sense of the Census: Polygons

The U.S. Census Bureau [https://www.census.gov/en.html] provides a very intricate and sometimes unstructured hierarchy of geospatial geometries that link back to the U.S. demographic data. This post

Neighborhood Data Landscape: Geometry

Neighborhood Data Landscape: Geometry

Intro What neighborhood related datasets are openly available, how good are they, and how can I use them? These are essential questions for any project looking to use or understand neighborhoods. This first

What defines a Neighborhood?

What defines a Neighborhood?

Pinpointing the composition, coordinates, and concept of a single neighborhood is a tough proposition. To understand these elements, we need more than simple data collection - we need a philosophical and sociological approach

We have Lift-off !

We have Lift-off !

You are cordially invited to the spatiotemporal intelligence blog by LotaData. We are the experts in location-based predictive technologies. Our data platform is open to all and free to try. Our APIs and