开源Java项目中图形查询语言使用的实证研究

Philipp Seifer, Johannes Härtel, Martin Leinberger, R. Lämmel, Steffen Staab
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引用次数: 15

摘要

图数据模型在许多领域都很有趣,部分原因是与关系模型相比,它们提供了直观性和灵活性。专门的查询语言,如用于属性图的Cypher或用于RDF的SPARQL,促进了它们的使用。在本文中,我们对GitHub上的开源Java项目中基于图形的查询语言的使用进行了实证研究。我们调查了SPARQL、Cypher、Gremlin和GraphQL的流行程度及其发展情况。我们根据与这些技术相关的依赖关系选择存储库,并为目标项目选择使用各种流行的和基于源代码的过滤器和排名功能。对于具体的语言SPARQL和Cypher,我们分析了存储库随时间的活动。对于SPARQL,我们研究了在查询具体实例数据的应用程序中常见的应用程序域、查询使用和本体数据建模的存在性。我们的结果显示,在过去几年中,开源项目中图形查询语言的使用有所增加,其中SPARQL和Cypher是目前最受欢迎的。SPARQL项目在与查询相关的工件更改和所涉及的独特开发人员方面更为活跃,但Cypher正在赶上来。相对较少的应用程序使用SPARQL查询具体的实例数据:这些应用程序中的大多数使用多个不同的本体,包括特定于项目和领域的本体。常见的应用领域是管理系统和数据可视化工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empirical study on the usage of graph query languages in open source Java projects
Graph data models are interesting in various domains, in part because of the intuitiveness and flexibility they offer compared to relational models. Specialized query languages, such as Cypher for property graphs or SPARQL for RDF, facilitate their use. In this paper, we present an empirical study on the usage of graph-based query languages in open-source Java projects on GitHub. We investigate the usage of SPARQL, Cypher, Gremlin and GraphQL in terms of popularity and their development over time. We select repositories based on dependencies related to these technologies and employ various popularity and source-code based filters and ranking features for a targeted selection of projects. For the concrete languages SPARQL and Cypher, we analyze the activity of repositories over time. For SPARQL, we investigate common application domains, query use and existence of ontological data modeling in applications that query for concrete instance data. Our results show, that the usage of graph query languages in open-source projects increased over the last years, with SPARQL and Cypher being by far the most popular. SPARQL projects are more active in terms of query related artifact changes and unique developers involved, but Cypher is catching up. Relatively few applications use SPARQL to query for concrete instance data: A majority of those applications employ multiple different ontologies, including project and domain specific ones. Common application domains are management systems and data visualization tools.
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