Gecko：用于大规模生成和变异真实个人身份数据的 Python 库

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-08-10 DOI:10.1016/j.softx.2024.101846

Maximilian Jugl, Toralf Kirsten

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引用次数: 0

摘要

记录关联算法需要在真实的个人身份数据上进行测试，以评估其在现实环境中的有效性。由于严格的数据隐私法规，获取此类数据往往是不可行的。用于生成真实数据的开源工具要么缺乏维护，要么性能不足以扩展到生成数百万条记录。我们介绍的 Gecko 是一个 Python 库，用于创建可共享的脚本，以生成和变异真实的个人数据。它建立在流行的 Python 数据科学库之上，极大地方便了与现有工作流程的整合。为证明该库的性能和可扩展性，我们提供了基准测试。

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Gecko: A Python library for the generation and mutation of realistic personal identification data at scale

Record linkage algorithms require testing on realistic personal identification data to assess their efficacy in real-world settings. Access to this kind of data is often infeasible due to rigid data privacy regulations. Open-source tools for generating realistic data are either unmaintained or lack performance to scale to the generation of millions of records. We introduce Gecko as a Python library for creating shareable scripts to generate and mutate realistic personal data. Built on top of popular data science libraries in Python, it greatly facilitates integration into existing workflows. Benchmarks are provided to prove the library’s performance and scalability claims.

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.