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Creating NoSQL Biological Databases with Ontologies for Query Relaxation

机译:使用本体创建NoSQL生物数据库以进行查询放松

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The complexity of building biological databases is well-known and ontologies play an extremely important role in biological databases. However, much of the emphasis on the role of ontologies in biological databases has been on the construction of databases. In this paper, we explore a somewhat overlooked aspect regarding ontologies in biological databases, namely, how ontologies can be used to assist better database retrieval. In particular, we show how ontologies can be used to revise user submitted queries for query relaxation. In addition, since our research is conducted at today's “big data” era, our investigation is centered on NoSQL databases which serve as a kind of “representatives” of big data. This paper contains two major parts: First we describe our methodology of building two NoSQL application databases (MongoDB and AllegroGraph) using GO ontology, and then discuss how to achieve query relaxation through GO ontology. We report our experiments and show sample queries and results. Our research on query relaxation on NoSQL databases is complementary to existing work in big data and in biological databases and deserves further exploration.
机译:建立生物数据库的复杂性是众所周知的,本体在生物数据库中起着极其重要的作用。但是,对本体论在生物数据库中的作用的许多强调都在于数据库的构建。在本文中,我们探索了有关生物学数据库中本体的一个被忽略的方面,即如何使用本体来帮助更好地进行数据库检索。特别是,我们展示了如何使用本体来修改用户提交的查询以简化查询。此外,由于我们的研究是在当今的“大数据”时代进行的,因此我们的研究集中在NoSQL数据库上,该数据库是大数据的一种“代表”。本文包含两个主要部分:首先,我们描述使用GO本体构建两个NoSQL应用程序数据库(MongoDB和AllegroGraph)的方法,然后讨论如何通过GO本体实现查询松弛。我们报告我们的实验,并显示示例查询和结果。我们对NoSQL数据库的查询松弛的研究是对大数据和生物数据库中现有工作的补充,值得进一步探索。

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