2026第一届“数元Datakernel ”数据测评体系交流研讨会成功举行

Core Insights - The first "DataKernel" data evaluation system seminar was successfully held in Beijing, attended by nearly 300 representatives from various sectors including government departments, data groups, state-owned enterprises, private enterprises, and research institutions [1][3]. Group 1: Establishment of Data Evaluation Standards - The establishment of a unified and authoritative measurement standard is crucial for the high-quality development of the data factor market, as emphasized by the Deputy Director of the China Electronic Technology Standardization Institute [3]. - The "DataKernel" evaluation system aims to address the core bottleneck of the lack of measurement standards in the data field, providing reliable quality benchmarks for various industries and promoting the standardization and prosperity of the data ecosystem [3][6]. Group 2: Collaboration and Ecosystem Development - A "DataKernel" data evaluation laboratory was jointly established by 20 representatives from local authorities, data groups, data exchanges, and research institutions, initiating an ecological partnership plan to collaboratively build standards, research technologies, enhance capabilities, and promote innovation [5]. - The "DataKernel" data evaluation system 1.0 was officially released, featuring a three-tier design logic that includes assessments of data management capability maturity (DCMM), data service capability maturity (DSEM), high-quality data set quality evaluation, data format standard compliance testing, data product quality evaluation, trusted data space testing, and big data system testing [6]. Group 3: Recognition and Pilot Initiatives - During the seminar, certificates were awarded to units that passed the high-quality data set quality evaluation and trusted data space testing, while the pilot for the data service capability maturity evaluation (DSEM) was also launched [8]. - Experts from various organizations shared insights and practical experiences on topics related to the "DataKernel" evaluation system, high-quality data sets, trusted data spaces, and data flow [10].