On the 10th, the Ministry of Industry and Information Technology issued the “Notice on Launching the Industrial Data Foundation‑Building Initiative and Conducting Pilot Projects for Developing High‑Quality Industry Data Sets Empowered by Artificial Intelligence,” aiming to overcome bottlenecks in the collection, aggregation, and utilization of industrial data.

The notice states that by the end of 2026, a number of industry‑specific data collaboration consortia will be established, trusted interconnection platforms for key industries will be built, a pool of industry‑wide data resources will be aggregated, critical data technologies will be tackled, a set of industrial data standards will be developed, and a portfolio of high‑quality, standardized, and interoperable industry data sets will be created, thereby enabling the deployment of large‑scale industry models, industrial intelligent agents, and other applications.

The notice states that, focusing on key manufacturing sectors with a strong foundation for digital transformation and significant potential for data‑driven value creation, it will leverage four types of stakeholders—leading enterprises in these sectors, platform providers, advanced manufacturing clusters, and pilot cities for the digital transformation of SMEs—to establish a number of consortia to spearhead pilot initiatives.

The notice requires that, in conjunction with the scenario map for digital transformation in key industries outlined in the “Reference Guidelines for Promoting Digital Transformation in Key Industries through Scenario‑Based and Knowledge‑Graph‑Driven Approaches (2025 Edition),” a “1+4+N” system be established. Leveraging industry consortia, a trusted interconnection platform for industry‑specific data will be built, along with four major resource repositories: an industry data repository, a data‑technology R&D repository, an industrial data standards repository, and a high‑quality industry data set repository. These efforts will enable the deployment of N application scenarios—such as industry‑wide large models and industrial intelligent agents—while distilling and formalizing effective pathways and mechanisms for the deep utilization and development of industrial data.

The Industry Data Trustworthy Interconnection Platform integrates data‑infrastructure capabilities such as the Industrial Internet, big‑data centers, computing‑power centers, data‑governance platforms, data‑engineering capability platforms, and industry‑specific trusted data spaces. It builds trusted interconnection platforms for key industries, deploys industrial data‑production and training bases, and offers capabilities including simulation‑environment data collection, specialized data annotation, and the synthesis of extreme‑scenario data.

The industry data repository system integrates knowledge assets such as operational manuals, safety standards, academic papers, and technical patents from key industries, alongside real-time data on equipment status, production processes, and operating environments, as well as business data including production work orders, product information, and supply-chain collaboration. This comprehensive framework establishes an industry-specific data repository that encompasses disciplinary expertise, process knowledge, and industrial mechanisms.

Data application scenarios are centered on key stages such as R&D and design, pilot-scale validation, production and manufacturing, business management, and industrial collaboration, with efforts focused on deploying industry‑wide large models and developing industrial intelligent agents to enhance quality, reduce costs, and boost efficiency. Consortium members are encouraged to explore institutional frameworks for authorized public data operations, industrial data rights confirmation, value assessment, and revenue sharing, while also facilitating data circulation and trading.

The notice requires relevant authorities to strengthen resource support and actively seek funding from channels such as the “Two Priorities” program. Local departments of industry and information technology are encouraged to support pilot initiatives through special funds, government awards, and other measures. Leveraging national-level open-source AI communities, efforts should be made to establish dedicated open-source zones for industrial data. Consortia members are also urged to engage in university–enterprise collaborations and other forms of cooperation.

(Source: China Chemical News, March 11, 2026)