The Ministry of Industry and Information Technology recently issued the "Guiding Opinions on the Development of Industrial Big Data", which clearly promotes the convergence and sharing of industrial data, deepens data fusion innovation, enhances data governance capabilities, strengthens data security management, and strives to create resource enrichment, application prosperity, An industrial big data ecosystem with industrial progress and orderly governance. And put forward 21 guiding opinions in seven aspects, including speeding up data aggregation, promoting data sharing, deepening data application, improving data governance, strengthening data security, promoting industrial development, and strengthening organizational guarantees.

1. General requirements

Adhere to the guidance of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, thoroughly implement the spirit of the 19th National Congress of the Communist Party of China and the Second, Third and Fourth Plenary Sessions of the 19th Central Committee, firmly establish a new development concept, and promote the convergence of industrial data in accordance with the requirements of high-quality development Share and deepen data fusion innovation, improve data governance capabilities, strengthen data security management, and strive to create an industrial big data ecosystem with rich resources, application prosperity, industrial progress, and orderly governance.

2. Speed up data aggregation

(1) Promote comprehensive collection of industrial data. Support industrial enterprises to implement digital transformation of equipment, upgrade various information systems, and promote data collection throughout the entire process of R&D, production, operation, and operation and maintenance. Support key enterprises to develop industrial numerical control systems, guide industrial equipment enterprises to open data interfaces, and realize comprehensive data collection.

(2) Speed up the interconnection of industrial equipment. Continue to promote the construction of the industrial Internet to realize the full connection of industrial equipment. Accelerate the promotion of compatibility and unification of industrial communication protocols, break down technical barriers, and form a complete data link.

(3) Promote high-quality aggregation of industrial data. Organize and carry out industrial data resource surveys, guide enterprises to strengthen data resource management, and realize data visualization, manageability, usability, and credibility. Integrate statistical data and monitoring data in key areas, and build a national-level database in industries such as raw materials, equipment, consumer goods, and electronic information. Support enterprises to build a data aggregation platform to realize the integration and aggregation of multi-source heterogeneous data.

(4) Coordinate the construction of a national industrial big data platform. Build a national industrial Internet big data center, gather industrial data, support industrial monitoring and analysis, empower enterprises to innovate and develop, and improve the level of safe operation of the industry. Establish a multi-level linkage national industrial base database, develop industrial chain maps and supply chain maps, and serve the high-quality development of the manufacturing industry.

3. Promote data sharing

(5) Promote the open sharing of industrial data. Support upstream and downstream enterprises in advantageous industries to open up data, strengthen cooperation, jointly build a safe and reliable industrial data space, and establish a mutually beneficial and win-win sharing mechanism. Guide and standardize the open flow of public data resources, and encourage relevant units to increase the level of value creation of data resources through sharing, exchange, and trading.

(6) Stimulate the vitality of the industrial data market. Support the development of key technologies for data flow, and build a credible industrial data flow environment. Build an industrial big data asset value evaluation system, study and formulate fair, open, and transparent data transaction rules, strengthen market supervision and industry self-discipline, carry out pilot data asset transactions, and cultivate an industrial data market.

Fourth, deepen data applications

(7) Promote the in-depth application of industrial data. Accelerate the application of data throughout the entire process, develop new data-driven manufacturing models and new formats, and guide enterprises to make good use of data in all business links.

(8) Carry out industrial data application demonstration. Organize and carry out 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 evaluation of local and enterprise application status.

(9) Enhance the supporting role of the data platform. Give full play to the advantages of the industrial Internet platform and improve the data processing capabilities of the platform. Open up data service resources for small and medium-sized enterprises and improve their data application capabilities. Accelerate the promotion of the softwareization of industrial knowledge, technology, and experience, and cultivate and develop a batch of industrial apps for different scenarios.

(10) Create an industrial data application ecosystem. Cultivate a group of industrial big data solution providers for key industries. Encourage the development of industrial big data competitions to help the industry with innovative applications. Intensify publicity and promotion, and carry out online and offline data application training activities.

Five, improve data governance

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

(12) Promote the development and application of standards. Strengthen the construction of the industrial big data standard system, accelerate the development of key standards such as data quality, data governance, and data security, and select industries and regions with mature conditions to carry out test verification and pilot promotion.

(13) Strengthen the classified and hierarchical management of industrial data. Implement the "Industrial Data Classification and Classification Guidelines (for Trial Implementation)" to realize data scientific management and promote the establishment of an enterprise-based industrial data classification and classification management system.

Six, strengthen data security

(14) Establish an industrial data security management system. Clarify the main responsibility of enterprise security and the responsibility of government supervision and management 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 evaluation, and early warning and disposal, realize closed-loop management, and fully guarantee data security.

(15) Strengthen the research and development of industrial data security products. Carry out security technology research such as encrypted transmission, access control, data desensitization, and improve the ability of anti-tampering, anti-theft, and anti-leakage. Accelerate the cultivation of key security companies, enhance data security services, and cultivate a good security industry ecosystem.

7. Promote industrial development

(16) Break through the key common technologies of industrial data. Accelerate the development and application of common technologies such as data aggregation, modeling analysis, application development, resource scheduling, and monitoring management, and promote the deployment and integration of cutting-edge technologies such as artificial intelligence, blockchain and edge computing.

(17) Build an industrial data product and service system. Promote the development of related products in industrial big data collection, storage, processing, analysis and services, and build a basic and universal big data product system. Cultivate a group of data resource service providers and leading data service companies, and develop a group of third-party service organizations focusing on data standard formulation, testing and evaluation, research and consulting.

(18) Focus on building an industrial data innovation ecosystem. Support industry-university-research cooperation to build an industrial big data innovation platform, carry out collaborative innovation around major common needs and industry pain points, accelerate the transformation of technological achievements, and promote advanced industrial foundation and industrial chain modernization.

8. Strengthen organizational guarantees

(19) Improve the work promotion mechanism. Provincial-level industry and informatization authorities (the big data industry authorities) should establish a working mechanism for promoting industrial big data, and coordinate the development of local industrial big data. Encourage localities to strengthen policy innovation in accordance with local conditions, conduct research on major issues, implement policy evaluation and consultation, and facilitate the innovative application of industrial big data.

(20) Strengthen financial talent support. Give full play to the guiding role of fiscal funds, and encourage policy banks to increase precision credit support. Encourage financial institutions to innovate products and services, and support industrial big data innovation and entrepreneurship. Improve the talent training system and cultivate compound talents who are both capable of big data technology and familiar with industry needs.

(21) Promote international exchanges and cooperation. Focusing on policies, technology, standards, talents, enterprises, etc., promote industrial big data to carry out cooperation and exchanges on a larger scale, broader field, and deeper level, and continuously improve the level of international development.

(Source: Ministry of Industry and Information Technology, Editor: Lan Haixia)