Competent departments of industry and informatization of all provinces, autonomous regions, municipalities directly under the central government, cities specifically designated in the state plan, and Xinjiang production and Construction Corps (competent departments of big data industry):
 
 Industrial big data is the general term of the whole life cycle data of products and services in the industrial field, including the data generated and used by industrial enterprises in R & D and design, production and manufacturing, operation and management, operation and maintenance services, as well as the data in the industrial Internet platform. In order to implement the national big data development strategy, promote industrial digital transformation, stimulate the potential of industrial data resources and accelerate the development of industrial big data industry, the following opinions are put forward.  
 
 

      oneGeneral requirements

      *** Industrial big data ecosystem with prosperity, industrial progress and orderly governance.
 
 

      twoAccelerate data aggregation

        （1） Promote the comprehensive collection of industrial data.  Support industrial enterprises to implement digital transformation of equipment, upgrade various information systems, and promote data collection in the whole process of R & D, production, operation, operation and maintenance. Support key enterprises to develop industrial CNC system, guide industrial equipment enterprises to open data interface and realize comprehensive data collection.
 　
      （2） Accelerate the interconnection of industrial equipment.  Continue to promote the construction of industrial Internet and realize the full connection of industrial equipment. Accelerate the compatibility and unification of industrial communication protocols, break technical barriers and form a complete and connected data chain.
 
  　  （3） Promote high-quality aggregation of industrial data.  Organize the investigation of industrial data resources, guide enterprises to strengthen data resource management, and realize the visualization, manageability, availability and credibility of data. Integrate statistical data and monitoring data in key areas, and build national databases in raw materials, equipment, consumer goods, electronic information and other industries. Support enterprises to build a data aggregation platform to realize the integration and aggregation of multi-source heterogeneous data.
 
  　  （4） Overall construction of national industrial big data platform.  Build a national industrial Internet big data center, gather industrial data, support industrial monitoring and analysis, enable enterprises to innovate and develop, and improve the safe operation level of the industry. Establish a multi-level linkage national industrial basic database, develop industrial chain map and supply chain map, and serve the high-quality development of manufacturing industry.  
 
 

      threePromote data sharing

        （5） Promote the open sharing of industrial data.  Support upstream and downstream enterprises in advantageous industries to open data, strengthen cooperation, 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 improve the value creation level of data resources through sharing, exchange and transaction.
　
        （6） Stimulate the vitality of industrial data market.  We will support tackling key technologies of 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 trading rules, strengthen market supervision and industry self-discipline, carry out pilot data asset trading, and cultivate the industrial data market.  
 
 

      fourDeepen data application

　　  （7） Promote the in-depth application of industrial data.  Accelerate the application of data in the whole process, develop new data-driven manufacturing models and new business formats, and guide enterprises to make good use of data in all business links.
　　
        （8） Carry out industrial data application demonstration.  Organize pilot demonstration of industrial big data application, summarize and promote industrial big data application methods, formulate evaluation standards for industrial big data application level, and strengthen the evaluation of local and enterprise application status.
 
  　　  （9） Improve the supporting role of data platform.  Give play to the advantages of industrial Internet platform and improve the data processing capacity of the platform. Open data service resources for small and medium-sized enterprises and improve enterprise data application ability. Accelerate the software of industrial knowledge, technology and experience, and cultivate and develop a number of industrial apps for different scenarios.
 
  　  （10） Create an industrial data application ecology.  Cultivate a number of industrial big data solution suppliers for key industries. Encourage industrial big data competition to help industry innovation and application. Strengthen publicity and promotion, and carry out online and offline data application training activities.  
 
 

      fiveImprove data governance

　　  （11） Carry out data management capability evaluation and standard implementation.  Promote the national standard of data management capability maturity evaluation model (GB / T 36073-2018, referred to as dcmm), build an industrial big data management capability evaluation system, and guide enterprises to improve data management capability. Governments at all levels are encouraged to strengthen policy guidance and financial support in the implementation of standards, personnel training and effect evaluation.

        （12） Promote the development and application of standards.  Strengthen the construction of 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 experimental verification and pilot promotion.
 
  　　  （13） Strengthen the classified and hierarchical management of industrial data.  Implement the guidelines for classification and classification of industrial data (Trial), realize scientific data management, and promote the construction of industrial data classification and classification management system with enterprises as the main body.
 
 
 

      sixStrengthen data security

　　  （14） Build an industrial data security management system.  Clarify the main responsibility of enterprise safety and the supervision and management responsibility of governments at all levels, and build an industrial data safety responsibility system. Strengthen the construction of industrial big data security capabilities such as situation awareness, test evaluation and early warning disposal, realize closed-loop management and comprehensively ensure data security.

        （15） Strengthen the research and development of industrial data security products.  We will tackle key security technologies such as encrypted transmission, access control and data desensitization, and improve the ability to prevent tampering, theft and leakage. Accelerate the cultivation of security backbone enterprises, enhance data security services, and cultivate a good security industry ecology.

        seven  Promote industrial development
 
         （16） Break through the key common technologies of 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 cutting-edge technologies such as artificial intelligence, blockchain and edge computing.
 　
        （17） Build an industrial data product and service system.  Promote the development of products related to industrial big data collection, storage, processing, analysis and services, and build a basic and universal big data product system. Cultivate a number of data resource service providers and leading data service enterprises, and develop a number of third-party service institutions focusing on data standard formulation, testing and evaluation, research and consulting, etc.
 
         （18） Strive to build 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 the upgrading of industrial foundation and the modernization of industrial chain.  
    

      eightStrengthen organizational guarantee

        （19） Improve the work promotion mechanism.  Provincial competent departments of industry and information technology (competent departments of big data industry) shall establish a working mechanism for promoting industrial big data and comprehensively promote the development of local industrial big data. Encourage all localities to strengthen policy innovation according to local conditions, carry out research on major issues, implement policy evaluation and consultation, and help the innovative application of industrial big data.

　  （20） Strengthen financial and talent support.  Give play to the guiding role of financial funds and promote policy banks to increase support for precision credit. 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 with big data technology ability and familiar with the needs of the industry.
 
         （21） Promote international exchanges and cooperation.  Focusing on policies, technologies, standards, talents, enterprises and other aspects, promote industrial big data to carry out cooperation and exchange in a wider range, wider fields and deeper levels, and constantly improve the level of international development.


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