Abstract: It is the important issue to promote the value realization of data elements through clarifying the multiple stakeholders and multi-source heterogeneous data of scientific and technological knowledge, and their synergistic mechanism, as well as delineating the knowledge extraction paths empowered with big data and intelligent technology. Based on the process of data-to-wisdom derivation in the DIKW chain, this study constructed a synergistic framework of scientific and technological knowledge involving multiple stakeholders, such as universities, research institutes, enterprises, government and the public, covering multi-source data such as papers, patents, products, policies and user-generated content. Furthermore, this study expanded the front-end and back-end structures of scientific and technological knowledge extraction paths, and explored the knowledge extraction outcomes and their diverse service scenarios under intelligent strategy combination patterns. Driven by digital intelligence, scientific and technological knowledge has formed a bi-directional and multi-dimensional intertwined synergy pattern under the direction of multi-stakeholders to facilitate the interaction and matching of knowledge supply and demand.

Key words: Data-intelligence driven, Multi-source heterogeneous data, Multi-stakeholder, Knowledge synergy, Knowledge extraction