Preconditions for Visualization
This chapter defines a set of preconditions that must be in place for the Data Inspector to successfully visualize data. These preconditions relate to the following areas:
With the Data Inspector Library, you can visualize these types of layers:
- Object store
Versioned layers store slowly changing data that must remain logically consistent with other layers in the catalog. When you want to update a catalog of versioned layers, all the layers related to the update (and partitions within a layer) must be updated in one publication so that they can be versioned together.
Volatile layers store data in the key/value form where values for a given key can change, and only the latest value is retrievable. As new data is published, old data is overwritten. Volatile layers use in-memory storage. Storing data in memory helps reduce data access latency and provides applications with consistently high throughput.
Object store layers offer free-form data storage, with no layer-level restrictions on partitioning, schemas, and content type. An object store layer is a generic key-value store. A value is always represented as a binary object (encoded protobuf data, JSON, image, and the like). Each object is associated to a key where a key represents an arbitrary path to an object. For more details on object store layer inspection see Inspect Object Store Layers.
Layer Partitioning Scheme
The Data Inspector Library supports two types of partitioning schemes:
- HERE Tile partitioning
- Generic partitioning
HERE Tile partitioning is a method for storing map data where layers contain rectangular geographic tiles that represent an area of the map. These tiles are also known as partitions. If you use HERE Tile partitioning, you can take advantage of the HERE platform libraries and APIs to perform geo-related tasks.
Generic partitioning is the simplest form of partitioning where partition names have no semantic meaning. Generic partitioning is best suited to data other than map data, such as search index data. With the Partitions List panel, you can view non-visualized partition data from generic layers.
For more information on partitioning schemes, see Partitions in the Data User Guide.
You can visualize different types of data from a local file or from a platform catalog. Both data sources support a wide range of formats.
GeoJSON is a format for encoding a variety of geographic data structures that supports the following geometry types:
MultiPoint to describe addresses and locations.
MultiLineString to describe streets, highways, and boundaries.
MultiPolygon to describe countries, provinces, and tracts of land.
These features do not have to describe only "real-world" entities. They can also describe invisible entities such as areas of mobile coverage or IoT geofences.
The Data Inspector Library provides out-of-the-box support for rendering GeoJSON data with the
GeoJsonDataSource conforms to the GeoJSON specification and supports all geometry types from the GeoJSON format. You can use a GeoJSON file as a local data source, or you can connect to a HERE platform catalog that stores GeoJSON data.
The data source supports a set of styling properties of the
Feature objects to customize the appearance of geometries. For more information, see Style GeoJSON Visualization.
Sensor Data Ingestion Interface (SDII)
SDII is a multifunctional web service for collecting and validating data generated by sensors. It connects equipment manufacturers and data vendors to the platform. Messages sent through this interface must be structured and encoded according to the Sensor Ingestion Interface Specification. You can use this interface to post messages with sensor data to the platform. For more information, see the Sensor Ingestion Interface Specification.
The Data Inspector Library can render SDII data out of the box from the platform or from a local file with the
SdiiDataSource class and supports the following:
- Static display of data
- Animation of vehicle paths
- Visualization of road signs
- Visualization of live data streams with a configurable auto-refresh rate
- Hazard warnings and other path events
You can filter the data by type, that is paths, road signs, hazard warnings, and other path events.
HERE Map Content
HERE Map Content is a Data API catalog that integrates highly accurate map data (including topology nodes and segments, assorted attributes, administrative data, and so on) from various sources. For more information, see HERE Map Content Specification.
Most layers in the HERE Map Content catalog have a default plugin for visualization bundled with the corresponding schema. For more information on HERE Map Content data visualization, see the corresponding How To chapter. For more information on HERE Map Content data visualization, see the corresponding How To chapter.
In addition to the visualization of geometry from the HERE Map Content layers, the Library can provide this data to other data sources. This can be used to visualize various data with no geometry information in it but that can be mapped to HERE Map Content geometry. For more information, see GeoJSON Data.
HERE Real-Time Traffic
The HERE Real-Time Traffic Data Specification is used for representing traffic data within the platform. Real-time traffic comprises highly accurate map data from multiple sources, including connected car probes, roadway sensors, and live operations centers. For more information, see HERE Real-Time Traffic Specification.
The Data Inspector Library can visualize traffic flow data (current traffic speed of certain road sections and road closures) by mapping it onto the OMV Plus base map road geometry using the dedicated rendering plugin.
For more information on traffic data visualization, see the corresponding How To chapter.
The Data Inspector Library allows you to visualize data in formats that are not supported by the standard rendering engine. There are a few preconditions that must be met:
This way, the Data Inspector Library can decode your partitions and render them with the rendering plugin. The rendering plugin returns the GeoJSON representation of the partition that is then rendered by the
Please note that for your datasets to be visualized correctly, it is your responsibility to develop and thoroughly test your rendering plugins.