From Genesis to Maturity: Managing Knowledge Graph Ecosystems Through Life Cycles

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The proposed lifecycle approach enhances the accuracy and reliability of knowledge graphs while enabling better insights.
Critical tasks like data integration and provenance tracking are systematically managed in knowledge graph ecosystems.
Adopting this approach supports effective knowledge management in various industries through improved data analytics.
The relevance of knowledge graphs in integrating heterogeneous data sources is essential for modern decision-making.

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This vision paper addresses challenges in data integration and management of knowledge graphs, suggesting a lifecycle approach.

Geisler et al. (2025) studied this question.

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