Why China Needs Open Big Data Platforms: Insights from Representative Zhang Jindong

Seeing the 2018 government work report repeatedly mention “big data” and emphasizing the conversion of old and new kinetic energy, Representative Zhang Jindong felt a strong resonance. After last year’s proposal to establish a full‑life‑cycle data management system, Zhang again raises the issue of data sharing this year.

Big data is an emerging production material of a digital China and a crucial foundation for enterprises to use the Internet and expand new kinetic energy. Data management is urgent; Zhang observes that China’s current big data management and usage suffer from fragmentation and gaps, with data security remaining a weak point.

He suggests jointly building a shared digital‑China open platform, gradually introducing artificial intelligence and blockchain technologies, and promoting the integration of big data with AI and blockchain to leverage the advantages of technology fusion, improving risk perception, prediction, and prevention capabilities.

He stresses that big data is difficult to share and that “data islands” must be broken.

In 2017, AI was first written into the government work report; this year, big data has moved to the forefront with unlimited expectations. The 2018 report repeatedly mentions promoting the widespread application of big data, cloud computing, and the Internet of Things, strengthening AI research and applications across many sectors.

Big data is growing like a snowball, from various sensors, new IoT devices, to wearable smart devices, forming a massive network. Yet China’s big data development is still in its early stage, with many foundational and critical datasets locked away by institutions, and a lack of common standards leading to difficulties in data collection and low efficiency in data use.

Zhang proposes that the state should treat data platforms as important public infrastructure, guide open sharing across industries, enable small and medium enterprises to compete with leading giants, break data barriers, and prevent data monopolies.

He recommends that the government lead the effort, referencing models such as UnionPay and NetUnion, with enterprises as the construction and operation entities, to create a national, cross‑regional, cross‑industry open data unified management platform that provides favorable conditions for data applications.

He warns that big data faces no privacy and that data security legislation must keep pace. Data, as a social asset that gains value with use, is increasingly vital in smart city construction, public services, and e‑government, but security issues such as manipulation risk, lack of trust and rights assurance create “data islands” that hinder the industry’s true value.

Zhang believes that AI and deep‑learning techniques for automatic data classification and behavior detection are key to solving data security problems, and calls for rapid legislative action to establish committees, accelerate laws on data collection, openness, sharing, security, privacy, standards, boundaries, tiered management, and regulation of data resources.

He also argues that blockchain, with its decentralized trust mechanism, tamper‑proof accounting, transparency, joint supervision, and traceability, offers great potential for data security. The integration of AI, blockchain, and big data can serve as an effective remedy for current data security shortcomings.