R Application
GEOSPATIAL DASHBOARD - R SHINY APPLICATION
A professional, interactive web application for exploring Point of Interest (POI) data from OpenStreetMap (OSM) in real-time.
Year :
2026
Projects
Real-Time Data Fetching: Automatically retrieve location data from OpenStreetMap based on user input
🗺️ Interactive Map Visualization:
Zoomable and scrollable map using Leaflet
CartoDB.Positron basemap for clean visualization
Clickable markers displaying place names
Marker clustering for better performance
📊 Modern User Interface:
Clean, responsive design using bslib
Sidebar controls for easy navigation
Tabbed interface (Map, Data Table, About)
Real-time statistics
**Tech Stack:** R 4.5.2 | Shiny 1.12.1 | Leaflet (Mapping) | osmdata (API) | sf (Spatial Data) | bslib (styling)
**The Challenge:**
Handled multiple data quality issues:
- Missing names in certain locations (solved with fallback logic)
- Different OpenStreetMap feature types (points, polygons, lines)
- Real-time performance optimization for 500+ markers
**Backend Architecture:**
Browser → Shiny Server (R) → OSM API
- Real-time API calls to OpenStreetMap
- Dynamic query building based on user filters
- Fallback logic for data quality assurance
```
**Data Pipeline:**
1. User selects city + category (e.g., Jakarta + Hospital)
2. Extract bounding box coordinates
3. Build OSM query: `opq(bbox) %>% add_osm_feature(key, value)`
4. Fetch features (points/polygons/lines)
5. Convert multi-type geometries to standardized format
6. Extract coordinates using `sf::st_coordinates()`
7. Apply fallback name extraction (name → operator → brand → amenity)
8. Render interactive Leaflet map with clustering
More Projects
R Application
GEOSPATIAL DASHBOARD - R SHINY APPLICATION
A professional, interactive web application for exploring Point of Interest (POI) data from OpenStreetMap (OSM) in real-time.
Year :
2026
Projects
Real-Time Data Fetching: Automatically retrieve location data from OpenStreetMap based on user input
🗺️ Interactive Map Visualization:
Zoomable and scrollable map using Leaflet
CartoDB.Positron basemap for clean visualization
Clickable markers displaying place names
Marker clustering for better performance
📊 Modern User Interface:
Clean, responsive design using bslib
Sidebar controls for easy navigation
Tabbed interface (Map, Data Table, About)
Real-time statistics
**Tech Stack:** R 4.5.2 | Shiny 1.12.1 | Leaflet (Mapping) | osmdata (API) | sf (Spatial Data) | bslib (styling)
**The Challenge:**
Handled multiple data quality issues:
- Missing names in certain locations (solved with fallback logic)
- Different OpenStreetMap feature types (points, polygons, lines)
- Real-time performance optimization for 500+ markers
**Backend Architecture:**
Browser → Shiny Server (R) → OSM API
- Real-time API calls to OpenStreetMap
- Dynamic query building based on user filters
- Fallback logic for data quality assurance
```
**Data Pipeline:**
1. User selects city + category (e.g., Jakarta + Hospital)
2. Extract bounding box coordinates
3. Build OSM query: `opq(bbox) %>% add_osm_feature(key, value)`
4. Fetch features (points/polygons/lines)
5. Convert multi-type geometries to standardized format
6. Extract coordinates using `sf::st_coordinates()`
7. Apply fallback name extraction (name → operator → brand → amenity)
8. Render interactive Leaflet map with clustering
More Projects
R Application
GEOSPATIAL DASHBOARD - R SHINY APPLICATION
A professional, interactive web application for exploring Point of Interest (POI) data from OpenStreetMap (OSM) in real-time.
Year :
2026
Projects
Real-Time Data Fetching: Automatically retrieve location data from OpenStreetMap based on user input
🗺️ Interactive Map Visualization:
Zoomable and scrollable map using Leaflet
CartoDB.Positron basemap for clean visualization
Clickable markers displaying place names
Marker clustering for better performance
📊 Modern User Interface:
Clean, responsive design using bslib
Sidebar controls for easy navigation
Tabbed interface (Map, Data Table, About)
Real-time statistics
**Tech Stack:** R 4.5.2 | Shiny 1.12.1 | Leaflet (Mapping) | osmdata (API) | sf (Spatial Data) | bslib (styling)
**The Challenge:**
Handled multiple data quality issues:
- Missing names in certain locations (solved with fallback logic)
- Different OpenStreetMap feature types (points, polygons, lines)
- Real-time performance optimization for 500+ markers
**Backend Architecture:**
Browser → Shiny Server (R) → OSM API
- Real-time API calls to OpenStreetMap
- Dynamic query building based on user filters
- Fallback logic for data quality assurance
```
**Data Pipeline:**
1. User selects city + category (e.g., Jakarta + Hospital)
2. Extract bounding box coordinates
3. Build OSM query: `opq(bbox) %>% add_osm_feature(key, value)`
4. Fetch features (points/polygons/lines)
5. Convert multi-type geometries to standardized format
6. Extract coordinates using `sf::st_coordinates()`
7. Apply fallback name extraction (name → operator → brand → amenity)
8. Render interactive Leaflet map with clustering