Standards are at the core of the development of industrial big data. Organisations and major manufacturing countries have been enhancing research and development of industrial big data standards, which led to the formulation of numerous big data standards. China, along with the international community, provided active contribution to the planning and layout of the industrial big data standardisation.
Major international organisations involved in big data and industrial big data standard research are: ISO/TC184 (Automation systems and integration); IEC/TC65 (Industrial-process measurement, control and automation); ISO/IEC JTC1; the Organisation for Economic Cooperation and Development (OECD); as well as United States Government-Industry Data Exchange Program (GIDEP) and the United Kingdom Engineering Sciences Data Unit (ESDU). All these organisations have formulated international standards covering big data terminology, referential structural models, and use cases.
China has established SAC/TC28, SAC/TCI59 and SAC/TC124 as the respective counterparts of ISO/IEC JTC1, ISO/TC184 and IEC/TC65; it has also established various organisations, such as the China Communications Industry Association on Big Data (CCIABD) and the Industrial Big Data Alliance (IBDA). All these organisations have actively engaged in the research and release of industrial big data standards systems, industrial products metadata, application referential structure, data collection specifications, data description standards, as well as a series of standards based on the needs for digitalisation and network of production and manufacturing, covering digital workshops, smart factory, connectivity, and information security.
To date, numerous industrial big data standards have been released both domestically and globally. Nonetheless, Shi Zhenshan, deputy director of the Instrumentation Technology & Economy Institute (ITEI, which acts as the secretariat of SAC/TC124), pointed out that industrial big data standards both at home and abroad are still largely insufficient to fully cope with the digitalisation of the manufacturing industry. In addition, coordination between Chinese industrial big data standards and international ones still proves challenging, in view of persisting differences and gaps in terms of:
- Understanding of the concept of industrial big data, and inconsistent terminology;
- Laws and regulations on the industrial data management;
- Maturity of industrial big data-related technologies, e.g. data collection, analysis, equipment integration and connectivity;
- Schedule of technology promotion and application.
Shi Zhenshan made a thorough analysis of the constraints that are affecting the development of domestic and foreign industrial big data standards, suggesting in particular that China’s industrial big data standards should:
- Firstly, strengthen data-related legislation and governance systems. Standards are the basis of laws and regulations, and at the same time complement them. In turn, the formulation and implementation of many standards usually is grounded on domestic laws and regulations, and at the same time also need to be coordinated with the relevant international standards and treaties. Within the context of globalisation, industrial big data are entangled with industrial security, data privacy and even ideology – which makes and coordination efforts challenging, as each country has its own management process regarding data security, industrial data application and intellectual property. In fact, the slow progress of international standardisation in the field of industrial big data is partly due to the many differences existing among the laws and regulations of all countries involved. As this issue requires a long-term approach and perspective in order to be solved, in the meantime China should, based on its internal needs, improve relevant legislation on industrial big data authentic rights, data transactions and sharing; it should improve industrial data security protection mechanisms, specify responsibilities and rights in the collection, storage, management and transaction of industrial data; and define the rights of data property, data operation and profit distribution. In sum, China will need to build a path and system that suit its standardisation development and needs, at the same time making continuous efforts for improvement and normalisation.
- Secondly, China should seek to establish solid standards foundations, at the same time leading through application and developing in a coordinated manner. Relevant actors need, in particular, to prioritise research and formulation of standards targeting industrial big data terminology, referential structure, and metadata category and identification. Emphasis should also be put on the formulation of product big data template and sorting techniques, on the establishment of a product big data standards system with clear attributes and traceability, and on the refining of industrial big data processing applications such as exchanges integration, whole-process modeling and analytic algorithms. Furthermore, data application standards should be formulated through pilot application and verification, before being then replicated and promoted on a wider scope. Finally, coordination between data collection, edge computing, platform security and other standards should be enhanced. In sum, as industrial big data-related technologies cover a wide range of databases, edge computing, deep learning, cloud computing, internet technologies, business passwords, etc. – all of which are evolving very rapidly –, China needs to test the maturity of these technologies in order to assess the feasibility of their application in the industry. Hence, the formulation of industrial big data standards should be closely coordinated with the development of relevant technologies, thus demarcating the agenda of industrial big data standardisation development.
- Thirdly, China should stimulate the vitality of enterprises in industrial data application. Research and formulation of international standards is usually a bottom-up process powered by industry actors; on the contrary, domestic big data standardisation is mostly top-down and depends on the allocation of tasks from higher levels. Government could use incentives to promote the industrial big data standards system and the contribution of enterprises. China’s manufacturing industry is mainly comprised of small and medium-sized companies (SMEs). Currently, typical industrial big data application is mainly conducted by enterprises with rich experience in digitalisation and informationisation, as application can enhance their quality, efficiency and productivity. SMEs with weaker development foundations face difficulties in achieving the digital transformation while solving their rigid development needs – and this is a key problem to be urgently solved for the development of China’s industrial big data standardisation.
Industrial big data is the general term for the entire life cycle data of industrial products and services, including: data generated from and utilised by industrial enterprises during R&D, design, manufacturing, operations and maintenance processes; as well as data generated from and utilised by industrial Internet platforms. As the fourth industrial revolution deepens, industrial big data has gradually become one of the most valuable strategic resources for industrial development, and a key production factor that contributes to the digitalisation and smartification of the manufacturing industry. Major countries and leading companies around the world are increasing their efforts on industrial big data and actively developing new data-driven industrial development models.
The Chinese government has vigorously promoted the development of the industrial big data, through the introduction of top-level policy documents like the Action Plan on Promoting Big Data Development, and the Guiding Opinions on Deepening the “Internet + Advanced Manufacturing Industry” to Develop the Industrial Internet: both documents clearly reflect the idea and efforts to promote the development and application of industrial big data.
Such efforts continued in 2020. The Communist Party of China (CPC) Central Committee and the State Council in April released the Guideline on Improving the Market-Based Allocation Mechanisms of Production Factors, clearly pointing out that China fully supports the construction of standardised data development and utilisation scenarios in industries and other fields, and the increase of the value of data resources. In May, the Ministry of Industry and Information Technology (MIIT) unveiled the Guiding Opinions on the Development of Industrial Big Data, which clearly states that China should strengthen the construction of the industrial big data standards system, and expedite research and formulation of key standards, including e.g. data quality, governance and security.
Drafted by Ming