The Ministry of Industry and Information Technology recently issued the "Guiding Opinions on the Development of Industrial Big Data," which clearly states the promotion of industrial data aggregation and sharing, deepening data fusion innovation, enhancing data governance capabilities, and strengthening data security management, with a focus on building an industrial big data ecosystem with rich resources, prosperous applications, industrial progress, and orderly governance. It also puts forward 21 guiding opinions in seven aspects: accelerating data aggregation, promoting data sharing, deepening data application, improving data governance, strengthening data security, promoting industrial development, and strengthening organizational assurance.

Ministry of Industry and Information Technology

Guiding Opinions on the Development of Industrial Big Data

MIIT Xinfa [2020] No. 67

To the industry and information technology authorities (big data industry authorities) of all provinces, autonomous regions, municipalities directly under the central government, cities specifically designated in the state plan, and the Xinjiang Production and Construction Corps:

Industrial big data is the general term for data throughout the entire lifecycle of products and services in the industrial field, including data generated and used by industrial enterprises in R&D and design, production and manufacturing, operation and management, and operation and maintenance services, as well as data in industrial internet platforms. To implement the national big data development strategy, promote industrial digital transformation, unleash the potential of industrial data resource elements, and accelerate the development of the industrial big data industry, the following opinions are hereby proposed.

I. General Requirements

Adhering to Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era as guidance, thoroughly implementing the spirit of the 19th National Congress of the CPC and the Second, Third, and Fourth Plenary Sessions of the 19th Central Committee, firmly establishing new development concepts, and in accordance with the requirements of high-quality development, promoting industrial data aggregation and sharing, deepening data fusion innovation, enhancing data governance capabilities, and strengthening data security management, with a focus on building an industrial big data ecosystem with rich resources, prosperous applications, industrial progress, and orderly governance.

II. Accelerating Data Aggregation

1. Promote comprehensive industrial data collection. Support industrial enterprises in implementing digital transformation of equipment, upgrading various information systems, and promoting data collection throughout the entire process of R&D, production, operation, and maintenance. Support key enterprises in developing industrial numerical control systems, guide industrial equipment enterprises to open data interfaces, and achieve comprehensive data collection.

2. Accelerate industrial equipment interconnection. Continue to promote industrial internet construction and achieve full connectivity of industrial equipment. Accelerate the compatibility and unification of industrial communication protocols, break down technical barriers, and form a complete and connected data chain.

3. Promote high-quality aggregation of industrial data. Organize industrial data resource surveys, guide enterprises to strengthen data resource management, and achieve data visibility, manageability, usability, and trustworthiness. Integrate statistical data and monitoring data in key areas, and build national-level databases in industries such as raw materials, equipment, consumer goods, and electronic information. Support enterprises in building data aggregation platforms to achieve the fusion and aggregation of multi-source heterogeneous data.

4. Coordinate the construction of the national industrial big data platform. Build a national industrial internet big data center, aggregate industrial data, support industrial monitoring and analysis, empower enterprise innovation and development, and improve the level of safe operation in the industry. Establish a multi-level coordinated national industrial basic big data database, develop industrial chain maps and supply chain maps, and serve the high-quality development of manufacturing.

III. Promoting Data Sharing

1. Promote the opening and sharing of industrial data. Support upstream and downstream enterprises in advantageous industries to open data, strengthen cooperation, jointly build a secure and trusted industrial data space, and establish a mutually beneficial and win-win sharing mechanism. Guide and regulate the open flow of public data resources, and encourage relevant entities to improve the level of data resource value creation through sharing, exchange, and trading.

2. Stimulate the vitality of the industrial data market. Support the development of key technology breakthroughs for data flow, and build a trusted industrial data circulation environment. Construct an industrial big data asset value evaluation system, research and formulate fair, open, and transparent data trading rules, strengthen market supervision and industry self-discipline, carry out data asset trading pilots, and cultivate the industrial data market.

IV. Deepening Data Application

1. Promote in-depth application of industrial data. Accelerate the application of data throughout the entire process, develop new models and new business formats of data-driven manufacturing, and guide enterprises to make good use of data in each business link.

2. Carry out industrial data application demonstrations. Organize industrial big data application pilot demonstrations, summarize and promote industrial big data application methods, formulate industrial big data application level evaluation standards, and strengthen the assessment of local and enterprise application status.

3. Enhance the supporting role of data platforms.Leverage the advantages of industrial internet platforms to enhance platform data processing capabilities. Open data service resources to small and medium-sized enterprises, and enhance enterprise data application capabilities. Accelerate the software-based transformation of industrial knowledge, technology, and experience, and cultivate and develop a batch of industrial APPs for different scenarios.

4. Build an industrial data application ecosystem. Cultivate a batch of industrial big data solution providers for key industries. Encourage innovation in industry applications through industrial big data competitions. Strengthen promotion and publicity, and carry out online and offline data application training activities.

V. Improving Data Governance

1. Carry out data management capability assessment and standard implementation.Promote the national standard "Data Management Capability Maturity Assessment Model" (GB/T 36073-2018, abbreviated as DCMM), build an industrial big data management capability assessment system, and guide enterprises to improve data management capabilities. Encourage governments at all levels to strengthen policy guidance and financial support in standard implementation, personnel training, and effectiveness assessment.

2. Promote standard development and application. Strengthen the construction of industrial big data standard systems, accelerate the development of key standards such as data quality, data governance, and data security, and select industries and regions with mature conditions for experimental verification and pilot promotion.

3. Strengthen industrial data classification and grading management. Implement the "Industrial Data Classification and Grading Guide (Trial)," achieve scientific data management, and promote the construction of an industrial data classification and grading management system with enterprises as the main entities.

VI. Strengthening Data Security

1. Build an industrial data security management system. Clarify the main responsibilities of enterprises for security and the supervision and management responsibilities of governments at all levels, and build an industrial data security responsibility system. Strengthen the construction of industrial big data security capabilities such as situational awareness, testing and assessment, and early warning and disposal, achieve closed-loop management, and comprehensively ensure data security.

2. Strengthen industrial data security product R&D. Carry out technical breakthroughs in encrypted transmission, access control, data desensitization, and other security technologies, and improve capabilities for tamper prevention, theft prevention, and leakage prevention. Accelerate the cultivation of security backbone enterprises, enhance data security services, and cultivate a sound security industry ecosystem.

VII. Promoting Industrial Development

1. Break through key common technologies for industrial data. Accelerate the R&D and application of common technologies such as data aggregation, modeling and analysis, application development, resource scheduling, and monitoring management, and promote the deployment and integration of frontier technologies such as artificial intelligence, blockchain, and edge computing.

2. Build an industrial data product and service system. Promote the development of related products in industrial big data collection, storage, processing, analysis, and service, and build a basic and universal product system for big data. Cultivate a batch of data resource service providers and leading data service enterprises, and develop a batch of third-party service institutions focusing on data standard formulation, testing and assessment, and research and consulting.

3. Focus on building an industrial data innovation ecosystem. Support industry-academia-research cooperation to build industrial big data innovation platforms, carry out collaborative innovation around major common needs and industry pain points, accelerate technology achievement transformation, and promote the advancement of the industrial base and the modernization of industrial chains.

VIII. Strengthening Organizational Assurance

1. Improve the work promotion mechanism. Provincial-level industry and information technology authorities (big data industry authorities) should establish industrial big data promotion work mechanisms to coordinate the promotion of local industrial big data development. Encourage localities to strengthen policy innovation according to local conditions, carry out major issue research, and implement policy assessment and consulting to support industrial big data innovation applications.

2. Strengthen financial and talent support. Leverage the guiding role of fiscal funds, and promote policy banks to increase precise credit support. Encourage financial institutions to innovate products and services to support industrial big data innovation and entrepreneurship. Improve the talent training system and cultivate compound talents with both big data technical capabilities and familiarity with industry needs.

3. Promote international exchange and cooperation. Around policy, technology, standards, talent, and enterprise aspects, promote industrial big data cooperation and exchange in a broader scope, wider fields, and deeper levels, and continuously improve the level of international development.