Data and Knowledge-Driven Processes for the Knowledge Graph Lifecycle

Explore comprehensive methodologies for managing knowledge graphs throughout their entire lifecycle in this conference talk that examines both data-driven and knowledge-driven approaches to knowledge graph development, maintenance, and optimization. Learn how to effectively integrate structured and unstructured data sources into knowledge graph frameworks while understanding the critical processes involved in knowledge graph creation, validation, and evolution. Discover practical strategies for implementing automated pipelines that can handle the complex challenges of knowledge extraction, entity resolution, and relationship mapping at scale. Gain insights into best practices for maintaining data quality and consistency across large-scale knowledge graph implementations, including techniques for handling schema evolution and knowledge base updates. Understand the theoretical foundations and practical applications of knowledge-driven processes that leverage existing domain expertise and ontological frameworks to enhance knowledge graph construction and refinement.