| 摘要: |
| 当前“数据”相关概念的语义混淆极大增加了学术对话成本。对此，应首先从横向专业领域区分与本源词“数据”“信息”“数字”相关的派生词，并从纵向区分三个本源词的关系，即信息是被记录的有待传播的内容，数字是随着信息技术发展带来的一种新的记录信息的手段，数据是信息记录的结果，其中数据元素是组成一份数据的最小单元。进一步地，从事实层面、价值层面、法律层面辨析数据与信息的关系，明确信息权益保护原始信息、数据权益保护增值信息。基于数据有用性、够用性、可用性和好用性的经济属性，数据的法律定义是“以数字化形式存在、能够产生增值信息以优化目标决策的数据元素集合及其处理结果”，并据此确定数据客体的构成要件包括： 数据元素之间具有相关性（质量要件）、数据元素集合具有规模性（数量要件）、数据具有现实的可利用性（形式要件）、数据具有用以优化目标决策的目的性（实质要件）。以数据行为环节“信息价值增值程度”作为分类标准，将数据客体分为原始数据、衍生数据、数据产品三类。 |
| 关键词: 数据产权 数据元素 权利客体 衍生数据 数据产品 |
| DOI： |
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| 基金项目:国家社会科学基金重大项目“新形势下我国参与知识产权全球治理的战略研究”（项目编号： 21&ZD165） |
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| Research on the Legal Definition of Data |
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Xu Chunming & Yang Huanhuan
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| Abstract: |
| The current semantic confusion of the concept of “data” greatly increases the cost of academic dialogue. Therefore, it is necessary to first distinguish the derived words related to the basic terms “data”, “information”, and “digits” across professional fields, and then vertically distinguish the relationship of the three basic terms. Information is the content that is recorded and waiting to be disseminated, digits are a new means of recording information brought about by the development of information technology, and data is the result of recording information, with data elements being the smallest unit composing a set of data. Furthermore, through analyzing the relationship between data and information at the factual level, the value level, and the legal level, it is important to clarify the protection of original information for information rights and the protection of value-added information for data rights. Based on the economic attributes of data, such as usefulness, sufficiency, availability, and usability, the legal definition of data is “a collection of data elements and their processing results that exist in digital form, capable of generating value-added information to optimize target decisions”. Based on this, the constitutive elements of data objects include: the correlation between data elements (quality requirement), the scale of the data element collection (quantity requirement), the practical usability of the data (formal requirement), and the purposefulness of the data to optimize target decisions (substantive requirement). Using the “degree of value-added information” in the data behavior process as a classification standard, data objects are classified into three categories: raw data, derived data, and data products. |
| Key words: Data Property Rights, Data Element, Object of Right, Derived Data, Data Product |
