Characteristics of a Spatiotemporal Dataset

Spatial Studio considers a dataset to contain spatiotemporal data if it belongs to any one of the following types.

• Live Spatiotemporal Dataset: A dataset which meets the following characteristics is known as a Live dataset:
  • The dataset is based on a geometry table or view with a geometry column or pair of latitude/longitude columns.
  • The dataset has one or more entities (that represent an object in the dataset) which are uniquely identified by one of the columns.
  • The dataset's underlying table or view contains a column of the type TIMESTAMP or DATE (or a qualifying field in the GeoJSON response), that stores the UTC datetime of the entities as they are being observed and recorded.
  • The dataset's underlying table or view must have ongoing inserts with recently obtained location data of entities being observed or monitored.

  Spatial Studio considers all the different dataset rows of the same entity id as entries representing the entity with different TIMESTAMP values. However, they may or may not have varying location coordinates or geometries. Hence, these live spatiotemporal datasets can again be classified as shown:

  • Moving Objects: For each entity, if the location or geometry change with changing TIMESTAMP values, then these datasets are called moving objects datasets. In this case, a trail layer (if it is a qualifying geometry) gets added, which shows the trajectory of the moving object as a line string by fetching data for last N seconds (or higher time unit).
  • Non-Moving Objects: For each entity, if only certain properties change (and not the location or geometry) with changing TIMESTAMP, then these are called non-moving objects datasets. In this case, no trail layer gets added as only the properties change with time.
• Non-Live Spatiotemporal Dataset: A dataset with the following characteristics is known as a Non-Live dataset:
  • The dataset is based on a geometry table or view with a geometry column or pair of latitude/longitude columns.
  • The dataset's underlying table or view contains a TIMESTAMP or DATE type column that contains historic time values.
  These datasets can again be classified as shown:
  • Moving Objects: Similar to a Live dataset, if this dataset contains entities (that uniquely represent an object in the dataset) with varying TIMESTAMP values, then a trail layer gets added. The trail layer shows the trajectory of the moving object as a line string by fetching data for last N seconds (or higher time unit).
  • Non-Moving Objects: In this configuration, the dataset is just treated to have various rows with different TIMESTAMP values (not grouped by any entity id).
• Time-enabled WMS Dataset: If a WMS Service offers a time dimension for an image layer selected in a WMS dataset, then that WMS Dataset can be configured as spatiotemporal.
• GeoJSON URL (external) Dataset: These types of datasets can be configured to refresh periodically based on an interval value.