The Open Location Platform (OLP) enables you to enrich and transform geospatial data such as sensor data or map data. The following examples illustrate some high-level use cases.
- Process geospatial sensor data coming from mobile devices or vehicles
- Measure congestion on a road or around a point of interest (POI) based on probe data collected from GPS devices
- Update map data based on sensor data to correct attributes such as travel direction, the speed limit, or forbidden/allowed parking
- Provide hazard warnings in real time by sending alerts about incoming events
- Transform map data into different formats and indices, such as Navigation Data Standard (NDS) format maps
- Publish GPS data to others for further processing
To support these use cases, OLP leverages batch and stream pipelines to transform data. The batch pipelines are built on the Apache Spark Framework, while the stream pipelines are built on the Apache Flink Framework. Batch pipelines run whenever a new version of an input data catalog is available to produce new or updated output. Stream pipelines run continuously.
To accomplish these uses and others, the HERE Open Location Platform provides:
- A GUI for managing, exploring, and analyzing your data and data transformation processes (pipelines)
- A set of REST APIs for managing data, managing pipelines, and retrieving authentication tokens
- An OLP SDK for Java and Scala containing:
- A command-line interface (CLI) for managing data and pipelines
- Java and Scala libraries for managing data, creating batch and streaming pipelines
- Maven Archetypes for setting up basic project scaffolding
You can also use other HERE products in combination with OLP SDK for Java and Scala to extend your capabilities. Specifically, you can use the Data Inspector Library to debug your pipeline applications by inspecting visualized output on top of the base map. For more information, see Data Inspector Library Developer Guide.
For the terms and conditions covering this documentation, see the HERE Documentation License.