AidMap

Data Source
Pulled the last 200 natural disasters (past, present, and contingent) from reliefweb.int using their public API.

Raw Data
Stored results in a JSON file for structured storage.

Processing
Cleaned and formatted the JSON to prepare for visualization.

Output
Data ready for exploration in KNIME workflows and visualization tools.

GET Request Node
A lone GET Request node was originally used to pull data directly from reliefweb.int. During development it began returning 202 errors, preventing data retrieval. It remains in the workflow for now in hopes of restoring functionality.

GDELT Dataset
Pulled from gdeltproject.org, which provides global news coverage databases. Used to analyze media reporting on disasters identified in the reliefweb.int dataset.

Processing
Because of its scale, extensive parsing was required to extract usable information. A GET Request node was used to gather HTML source code and match keywords against ReliefWeb terms

ReliefWeb Visualization
The ReliefWeb dataset is displayed on a geospatial map, showing both location and status of each disaster:

• Ongoing → The disaster is currently active.

• Passed → The disaster has ended or is no longer active.

• Alert → A potential disaster risk has been identified, but not yet confirmed.

Overlapping Coordinates
Since disasters are often assigned the latitude/longitude of their nation, many overlap on the map.

Solution
A secondary graph records and visualizes the count of disasters per location, turning overlap into useful insight.

Status-Specific Graphs
Beyond overall disaster density per country, three separate graphs were created:

• Passed

• Ongoing

• Alert

Each graph is color-coded by disaster type for clearer comparison.

GDELT Term Filtering
After parsing and filtering to the ‘NATURAL_DISASTER’ theme, a term filter scans each webpage’s HTML source for ReliefWeb terms.

Extraction
This identifies the source, organization, and location (lat/lon) for each article.

Visualization
Results are plotted on a geospatial map, color-coded by average tone score:

• Positive → Upbeat coverage

• Negative → Somber or critical coverage

Organization Coverage
This pie chart shows how often each organization covers the topic, based on the provided keyword(s).