Knowledge graphs (KGs) have drawn massive attention from both academia and industry, and become the backbones of many AI applications. Current KGs are often constructed and maintained by large parties, which provide services in the form of RDF dumps or SPARQL endpoints. This kind of centralized management has inherent drawbacks like non-durable accessibility. Furthermore, some facts in KGs may be outdated or conflicting, and there is no convenient way of resolving them democratically. As an innovative distributed infrastructure, blockchain has many characteristics such as decentralization and consensus, which is of great significance for the construction and management of KGs. This study designs a blockchain-enhanced knowledge management framework called FactChain, which aims to establish a new decentralized ecology for knowledge sharing and fusion. FactChain leverages a consortium architecture containing blockchain, organizations, and participants. The on-chain smart contracts enable the truth discovery algorithm of multiple- source conflicting knowledge. FactChain also supports participant management, mapping between local schemata and global ontology and integration of on/off-chain knowledge based on the decentralized application (DApp) in organizations.