Extreme and Sustainable Graph Processing for Urgent Societal Challeng...

The use, interoperability, and analytical exploitation of graph data are essential for the European data strategy. Graphs or linked data are crucial to innovation, competition, and prosperity and establish a strategic investment in technical processing and ecosystem enablers. Graphs are universal abstractions that capture, combine, model, analyze, and process knowledge about real and digital worlds into actionable insights through item representation and interconnectedness. For societally relevant problems, graphs are extreme data that require further technological innovations to meet the needs of the European data economy. For example, a study by IBM revealed that the world generates nearly 2.5 quintillion bytes of financial data daily, posing extreme analytics challenges. The complexity, diversity, and data multilingualism lead to highly complex graph operations when encoding media, news, and social-networking messages. Digital graphs help pursue the United Nations Sustainable Development Goals by enabling better value chains, products, and services for more profitable or green investments in the financial sector and deriving trustworthy insight for creating sustainable communities. All science, engineering, industry, economy, and society-at-large domains can leverage graph data for unique analysis and insight, but only if graph processing becomes easy to use, fast, scalable, and sustainable.