要深入探讨数据产权结构性分置对数据要素价值实现的影响，首先就要准确理解"数据产权结构性分置"这一概念的内涵。从概念构成看，"数据产权结构 性分置"内涵包含三个基本范畴，分别是"数据产权""结构性"和"分置"，本文从以上三个范畴进行分析。 (一)数据产权 数据产权是贯通经济学和法学范畴的一个概念。狭义的数据产权即数据财产权，是指围绕数据作为财产所衍生的包括所有权、使用权、收益权和处置权等 对世性权利，具有一定的排他性和支配性，强调经济行为主体之间对财产的一组或一束权利的界定与分配。然而，随着数字技术的加快落地与数据应用场 景的逐步丰富，数据权属的界定与分配不仅涉及以上对世性权利，还关乎数据在开发中的公共治理、在流通和交易过程中的权益保障等，呈现出从单一的 权利义务结构趋向复合的权利义务关系、从平面的权利样态发展为立体的权利样态、从静态赋权走向动态界权的趋势与特点。已有学者从权利功能分工、 权利动态配置、权利主体差异等视角对数据产权所承载的权利进行了探讨，但因数据产权复杂性、多维性以及传统产权理论的局限性，故数据产权概念尚 无定论。本文认为数据产权是一个动态、多维且复杂的权利体系，既涵盖与数据相关的所有权、使用权 ...

Core Viewpoint - The initial rights definition and minimization of transaction costs are prerequisites for establishing a unified national data factor market, which will drive the industrialization and fair pricing of data factors, ultimately benefiting the real economy [3][4]. Group 1: Basic Elements for Building a Unified Data Factor Market - The four basic elements for constructing a unified national data factor market are initial rights definition, transaction cost minimization, infrastructure development, and industrialization [4]. - Current obstacles to data factor market construction include unclear data property rights and high transaction costs, primarily due to the lagging property rights system behind technological advancements [4][5]. Group 2: Key Scientific Issues in Data Factor Market Construction - The initial rights definition of data resource development and utilization plays a foundational role in the construction of a unified data factor market, while transaction cost issues need urgent solutions [5]. - The construction of data circulation infrastructure introduces a technology trust mechanism, supporting data resource development, transaction pricing, and regulatory safety [5]. - The industrialization of data factors will act as an accelerator in promoting the construction of a unified national market [5]. Group 3: Data Property Rights Governance - The "Data Twenty Articles" propose a structural division of data property rights, which, while aligning with social equity from a legal perspective, presents significant logical conflicts from an economic standpoint [7]. - The classification and grading of data rights can increase transaction costs and complicate the sharing and trading of data resources, leading to data protectionism and monopolization [7][8]. - The initial rights to data resource development should ideally be assigned to the government, which can represent public interests and facilitate the efficient use of data resources [9]. Group 4: Transaction Cost Issues in Data Factor Market - Five key transaction costs affecting data factor flow include externality transaction costs, communication transaction costs, institutional transaction costs, intermediary service costs, and application delivery costs [11]. - High transaction costs hinder the incentive mechanisms for data resource circulation and utilization, necessitating government intervention to reduce these costs [12].