The Water Health Open Knowledge Graph.

Area of Science:

• Environmental Science
• Public Health
• Data Science

Background:

• Global sustainability challenges necessitate better management of water and health resources.
• Open data is crucial for achieving United Nations Sustainable Development Goals, particularly clean water and sanitation.
• Existing data management approaches may not adequately integrate diverse water and health information.

Purpose of the Study:

• To introduce the Water Health Open Knowledge Graph (WHOW-KG) and its design.
• To analyze the impact and potential applications of the WHOW-KG.
• To provide a valuable resource for researchers, policymakers, and practitioners in water and health domains.

Main Methods:

• Developed a semantic knowledge graph (WHOW-KG) using a network of five ontologies.
• Modeled linked open data encompassing water consumption, pollution, extreme weather, infectious diseases, and drug distribution.
• Employed a fully distributed system design for sustainability and scalability.

Main Results:

• The WHOW-KG successfully integrates diverse water and health datasets.
• The knowledge graph supports various applications, including knowledge discovery and decision-making.
• The system is sustainable, handles large datasets, and empowers data providers.

Conclusions:

• The WHOW-KG is a vital European asset for water consumption and pollution research.
• It enhances the ability to address global sustainability challenges through integrated data.
• The semantic approach facilitates informed decision-making in water and health resource management.