首个新材料领域AI数据治理标准发布

Core Viewpoint - The newly released group standard "Artificial Intelligence Data Governance Guidelines for New Materials" aims to address data governance challenges in the new materials sector, providing a structured framework for the industry's intelligent transformation [1][2]. Group 1: Governance Principles - The standard establishes eight key principles including standardization, transparency, compliance, safety, and emphasizes experimental traceability [2]. Group 2: Comprehensive Process Coverage - It constructs a four-stage governance system covering top-level design, organizational support, engineering construction, and operational optimization [2]. Group 3: Focus on Multi-Modal Data - The standard sets unified standards for the collection, storage, and sharing of various data types, including experimental characterization, simulation, process manufacturing, and application performance, aiming to eliminate data silos [2]. Group 4: Quality and Safety Enhancement - Specific data quality indicators are defined, and security mechanisms such as data classification, tiered encryption, and regional access control are established, supported by technologies like differential privacy and homomorphic encryption [2]. Group 5: Industry Applicability and Impact - The standard is applicable across multiple sectors including alloys, new energy materials, semiconductors, and biopharmaceuticals, covering the entire chain from R&D to industrial application, expected to lower costs, enhance efficiency, and support digital infrastructure and competitiveness in the new materials industry [2].