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| 分布式大数据资产权益管理问题与对策 | |
| 引用本文： | 顾立平,张潇月. 分布式大数据资产权益管理问题与对策[J]. 农业图书情报学刊, 2023, 35(1): 39-55. DOI: 10.13998/j.cnki.issn1002-1248.22-0834 |
| 作者姓名： | 顾立平 张潇月 |
| 作者单位： | 1.中国科学院文献情报中心,北京 100190; 2.中国科学院大学 经济与管理学院信息资源管理系,北京 100490; 3.北京大学 信息管理系,北京 100871 |
| 基金项目： | 国家社科基金项目“开放科学环境中数据馆员服务模式研究”（21BTQ005） |
| 摘 要： | [目的/意义]数字技术成为数据生产要素充分开发利用的重要驱动力量,充分利用数据资源的底层伴生议题是产权管理。数据流转中存在所有权与使用权分离的问题,在合理合法、保障用户权益的基础上进行数据资源管理活动成为亟待解决的问题。[方法/过程]基于“实践基础-抽象化分析-一般的具体认识”总思路,本文首先识别出分布式大数据资产的实践情况,而后从技术资源规范、合理使用边界、权益复杂性和使用权解析这4方面抽象化分析其权益管理关键内容。[结果/结论]基于抽象化分析,从机构层面具体说明：1）数据政策的原理和条款,2）权益组合的场景与内容规划,3）数据资产的配置管理,和4）数据资产管理业务的建构标准、工作流程、涉及的协议与规定、评估措施,以期对图书馆等数据资源管理机构在分布式大数据环境下为用户开展数据资产权益管理提供启发。 |
| 关 键 词： | 分布式大数据 数据政策 数据资产管理 数据权益管理 政策框架 权益组合 |
| 收稿时间： | 2022-11-25 |
Problems and Solutions of Distributed Big Data Asset Right Management |
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| GU Liping,ZHANG Xiaoyue. Problems and Solutions of Distributed Big Data Asset Right Management[J]. Journal of Library and Information Sciences in Agriculture, 2023, 35(1): 39-55. DOI: 10.13998/j.cnki.issn1002-1248.22-0834 | |
| Authors: | GU Liping ZHANG Xiaoyue |
| Affiliation: | 1. National Science Library, Chinese Academy of Sciences, Beijing 100190; 2. Department of Information Resources Management, School of Economics and Management, University of the Chinese Academy of Sciences, Beijing 100049; 3. Department of Information Management, Peking University, Beijing 100871 |
| Abstract: | [Purpose/Significance] Digital technology has become an important driving force in the utilization of data production elements. To make full use of data resources, the underlying accompanying problem is rights management. In practice, the ownership and the right to use of data resource are separated in the circulation process. It has become an urgent problem to conduct data resource management activities based on reasonable and legal protection of users' rights. [Method/Process] Based on the general framework of practical basis - abstract analysis - general concrete understanding, this paper firstly identified four practice statuses of distributed big data assets as followings: 1) the application of new technology leading to facilitating platforms; 2) attention needed to paid to intellectual properties of multiple users' groups; 3) users' needs to be satisfied on various contexts. For example, conducting resource procurement, collection, data processing and layout of resource allocation systems based on cloud service platforms; 4) maintainance and management of high quality data sets, including self-built and imported resources, the negotiation of ownership and use rights, and emphasis on the rights strategies. Next, this study conducted abstract analysis on the generalized idea of basic dimensions of data rights management from four aspects, namely, technical resource regulation, reasonable use boundary, complexity of rights, and analysis of use rights. [Results/Conclusions] Based on the abstract analysis, this paper put forward and explained four successive solutions at data resource management institute level, as described below. 1) the principle and terms of data policy, which include but not limited to general statement, policies of content use, policy statement on metadata, social media policies, and terms of service; 2) the typical contexts and content planning of rights potofolio. This paper took the resource procurement business of academic libraries as an example to illustrate and summarize the four content planning items on rights portfolio: strategic plan, operational policies, data policies, end-user policies; and 3) the allocation management of data assets, which lays the key part of data asset management. In this paper, we consider that data asset management refer to description and management of the constituent terms of data assets and the relationship between terms. The cost structure of data asset management contains tangible cost (such as consulting, software and hardware purchase fee, and digital resources purchase fee) and intangible cost (such as indirect human resource costs, risks, social credit, and loss compensation); and 4) finally, the establishment standard, working process, associated contrasts and regulations, and the evaluation measurements of data asset management businesses at the institute level. Such solutions are proposed to provide some inspirations to data resource management institutes（such as libraries） under the distributed big data circumstance. |
| Keywords: | distributed big data data policy data asset management data rights management policy framework rights potofolio |
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