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Version: v0.1.0

Entity Map

Entity Map is a feature that visualizes entities with location information (coordinates) on a map. You can intuitively explore spatial data such as stores, sensors, and facilities.

Overview

If an entity defined in the ontology includes latitude and longitude properties, its data can be displayed as markers on a map. This allows you to see the geographic distribution and patterns of data at a glance.

Access Path

Navigate via the sidebar: Ontology → Select entity → Map tab, or access directly via the URL /ontology/entities/:entityId/map.

Entity Mapping

To display entities on the map, you must correctly map dataset columns to entity properties.

Mapping Procedure

  1. Select the target entity in the Ontology Builder.
  2. Connect a dataset in the Data Source tab.
  3. Map the columns corresponding to latitude and longitude to the respective entity properties.
  4. After mapping is complete, run Sink to load the data into the graph database.

Mapping Example

Entity PropertyDataset ColumnDescription
latitudelatLatitude (WGS84)
longitudelngLongitude (WGS84)
namestore_nameName displayed on the marker label
addressfull_addressDetailed address

Coordinate Data Requirements

For map visualization to work correctly, coordinate data must meet the following conditions.

ItemCondition
Coordinate SystemWGS84 (EPSG:4326)
Latitude Range-90 to 90
Longitude Range-180 to 180
Data Typefloat or double
NULL HandlingIf either latitude or longitude is NULL, that row will not be displayed on the map
Coordinate System Verification

Some datasets may use coordinate systems other than WGS84 (such as KATEC, TM, UTM-K). To display them on the map, you must convert the coordinates to WGS84 before mapping.

Map Interactions

Basic Controls

ActionMethod
Zoom in/outMouse wheel scroll or +/- buttons
PanDrag on the map
Marker clickDisplays entity detail popup
Close popupClick outside the popup area or the × button

Marker Popup

Clicking a marker displays the key properties of the corresponding entity in a popup.

  • Entity Name: The mapped name property
  • Property List: Properties defined for the entity and their values
  • Relationship Summary: Number of relationships connected to the node

Clustering

When markers are densely packed in the same area, they are automatically displayed as cluster markers. Zooming in separates them into individual markers.

Usage Examples

  • Store Distribution Analysis: View the geographic distribution of nationwide stores and identify concentrated areas
  • IoT Sensor Monitoring: Manage sensor installation locations on a map and check their status
  • Logistics Network Visualization: Understand the spatial relationships between warehouses and delivery hubs
Integration with Other Features

By combining spatial patterns identified in Entity Map with Cypher queries in Graph Explorer, you can perform in-depth analysis of entities and their relationships within specific areas.