Understanding the Structural Characteristics of Data Platforms Using Metadata and a Network Approach
Understanding the Structural Characteristics of Data Platforms Using Metadata and a Network Approach
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DOI：
10.1109/access.2020.2975064
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发表时间：
2020-02
期刊：
影响因子：
3.9
通讯作者：
Teruaki Hayashi;Y. Ohsawa
中科院分区：
文献类型：
--
作者：
Teruaki Hayashi;Y. Ohsawa
随着全球交易和买卖数据平台的出现，数据已成为一种有利可图的商品。这些平台的增长需要进一步扩大数字经济中的数据范围。为此，了解现有数据的性质及其相互关系已成为扩大其使用的一项重要挑战。因此，在这项研究中，我们假设平台上的数据作为总体，元数据作为样本。因此，我们对数据平台的结构特征进行了定量研究，同时通过不共享数据本身来避免失去商业机会和隐私问题的风险。通过观察数据和变量的特征，我们发现数据网络具有局部密集而全局稀疏的结构，这与人际关系网络非常相似。此外，我们发现，数据在平台上扮演不同的角色时，分为共享条件，即，可共享数据和敏感数据。最后，我们讨论了基于我们的研究结果创建/使用数据平台的个人的潜在策略。本研究的贡献包括数据平台观察的新框架以及使用元数据和网络方法分析数据结构特征的方法。
With the emergence of global platforms for trading and buying/selling data, data have become a profitable commodity. The growth of such platforms has necessitated the further expansion of the scope of data in digital economies. To this end, understanding the nature of available data and their relationships between them has become an important challenge for expanding their use. Thus, in this study, we assumed data on the platforms as a population and metadata as the samples. Thus, we quantitatively investigated the structural characteristics of data platforms, while avoiding the risk of lost business opportunities and privacy issues by not sharing the data themselves. By observing the characteristics of data and variables, we found that the data network had a structure that was locally dense and globally sparse, which is quite similar to networks of human relationships. Moreover, we found that data play different roles on the platforms when divided into sharing conditions, namely, shareable data and sensitive data. Finally, we discussed the potential tactics for individuals who create/use data platforms based on our findings. The contributions of this study include a new framework for data platform observation and a method that uses metadata and a network approach to analyze structural characteristics of data.