EXTENDED ABSTRACT: In recent years, artificial intelligence (AI) technology based on big data has developed rapidly and is deeply integrated with all walks of life, which is profoundly changing the way humans think and behave. In the ffelds of condensed matter physics and quantum materials, building high-quality data resources that can be used by AI is an urgent problem that needs to be solved. The difffculties in data aggregation in condensed matter science lie in: difffculty in aggregation due to diverse data sources; difffculty in screening due to non-standardized and non-uniffed data; difffculty in ffnding, obtaining and utilizing data due to scattered data distribution; and integration due to the dispersion and isolation of existing databases, sharing is difffcult. Therefore, establishing a new paradigm of artiffcial intelligence and data-driven research requires completing four basic tasks: establishing an efffcient and stable data aggregation technology platform, building a high-quality data resource library, developing AI-based data analysis application methods, and building an open and shared Data community. In cooperation with multiple experimental research groups, we have developed and deployed the Material Science Electronic Laboratory (matElab), a software platform based on electronic experiment notebooks, to achieve efffcient scientiffc research data in condensed matter physics and materials. Stably gathered together, we built more than ten open and shared materials databases, developed a series of digital and intelligent integration R&D tools, and achieved several important original results in data-driven acceleration of material innovation, including improving the efffciency of hightemperature superconducting thin fflm material preparation process optimization Dozens of times, a new law of amorphous alloy formation ability was discovered, which increased the creation speed of new alloys by a hundred times. Keywords：Materials genetic engineering; high-level forum; electronic laboratory notebook; condensed matter physics; quantum materials database

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