What is Spatio-Temporal Big Data?

Spatio-Temporal Big Data is Multidimensional Data with both space and time information involved.

Spatio refers to the space or geographical area of data; while temporal is data in relation to time. This type of data is multi-dimensional while most big data is singular dimensional. Spatio / spatial data represents data such as coordinates, points, and shapes (both 2D or 3D) etc. For instance the location of a shopping man is spatial data.

While temporal data can come in a wide range of types such as valid time, transaction time, or bitemporal data; which refers to data within different time periods. An example could be a shopping purchase at 08:00 vs 09:30.

This data combines to create Spatio-Temporal Big Data. An example of this could be climbing a hiker climbing a mountain. They began walking at 05:00 and finished their hike at 11:00 and walked 5miles. Every movement between 05:00 and 11:00 in relation to the time such as the steps were taken, speed of movement, and even the elevation at that time, are all Spatio-Temporal Data points.

Many companies struggle with processing Spatio-Temporal data due to its unusual multi-dimensional nature; though what makes it worse is there are many modern examples this type of data is popping up