摘要
工业大数据是支撑产业数字化转型、促进数字经济与实体经济深度融合的关键生产要素。与其他数据类型相比,工业大数据具有更强的排他性、价值性、系统性和风险性,在提升数据要素潜力的同时,也对其价值创造机制形成更多约束。基于生产设备、工业产品、产业链等数据的分析使用,有助于优化资产性能、提升产品研制效率、增强产业链协同配合,提升数据的价值创造潜力。然而,工业大数据的独特属性也造成企业数据供给意愿不足、采集分析技术难度提升、数据应用场景不明确等价值创造挑战。以欧盟IDS、日本CIOF为代表的“数据空间”模式是目前较为可行的工业大数据开发模式,能够较好满足数据主体对可信安全环境、技术标准支撑、应用场景优化的需求。为充分释放我国工业大数据要素潜力,可借鉴欧日相关模式经验,着力完善工业大数据战略规划和管理体系、创新工业大数据流通和服务模式、加强工业企业数据管理和使用能力,加快推进工业大数据制度体系和产业生态建设。
Industrial big data is a key production factor that supports the digital transformation of industries and promote the integration of digital and real economy.Compared with other types of data,industrial data is featured with stronger exclusivity,greater value,higher systematism and increased risk exposure,which,while enhancing its factor potential,have more constraints on its value creation mechanism.Data analysis of production equipment,industrial product,and industrial chain can effectively optimize asset performance,promote product development,and improve industrial chain coordination so as to enhance the potential for data value creation.However,the unique attributes of industrial data also pose challenges to value creation,such as unwillingness of enterprises to supply data,increased difficulty in technology for data collection and analysis,and undefined data application scenarios.At present,the‘data space’mode represented by EU’s IDS and Japan’s CIOF is a more feasible industrial data development mode,which can better meet the needs of data subjects for trusted security environment,technical standard support and application scenario optimization.To fully unleash the potential of China’s industrial big data,we can learn from the experience of relevant modes in Europe and Japan,focus on improving the strategic planning and management system of industrial big data,innovate the mode of circulation and service for industrial data,strengthen the data management and application capability of industrial enterprises,so as to accelerate the construction of industrial big data system and industrial ecosystem.
作者
陈楠
蔡跃洲
CHEN Nan;CAI Yue-zhou(Institute of Quantitative and Technological Economics,Chinese Academy of Social Sciences,Beijing 100732,China)
出处
《北京交通大学学报（社会科学版）》
CSSCI
北大核心
2023年第3期25-36,共12页
Journal of Beijing Jiaotong University(Social Sciences Edition)
基金
国家自然科学基金重大项目“宏观大数据建模和预测研究”(71991475)
国家自然科学基金应急管理项目“数据要素总量测算、结构分析与统计体系研究”(72241435)。
关键词
工业大数据
数据要素
价值创造
国际经验
industrial big data
data as production factor
value creation
international experience
