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Improving discoverability of open government data with rich metadata descriptions using semantic government vocabulary

机译:使用语义政府词汇来利用丰富的元数据描述提高开放政府数据的可发现性

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The descriptive metadata gathered by open data catalogs are often simple key-value pairs that describe provenance information, but not concepts from the domain of the described dataset. Search engines relying on such metadata cannot make use of semantic connections among datasets. In this paper, we present a Semantic Government Vocabulary that is used for creating rich annotations of Open Government Data, allowing to find their mutual interconnections, as well as document their meaning in the machine readable form. We discuss how the Semantic Government Vocabulary is layered based on the different ontological types of terms occurring in the Open Government Data. Next, we show how the vocabularies can be used to annotate Open Government Data on different levels of detail and how to formalize the whole stack in the Web Ontology Language. We evaluate feasibility and usability of our approach using a study in the elections domain. (C) 2018 Elsevier B.V. All rights reserved.
机译:由开放数据目录收集的描述性元数据通常是简单的键/值对,它们描述来源信息,而不是描述数据集范围内的概念。依赖于此类元数据的搜索引擎无法利用数据集之间的语义联系。在本文中,我们提供了一个语义政府词汇表,该词汇表用于创建开放政府数据的丰富注释,从而可以找到它们之间的相互联系,并以机器可读的形式记录其含义。我们讨论了基于公开政府数据中出现的不同本体论类型的语义政府词汇如何分层。接下来,我们展示如何使用词汇表在不同详细程度上注释开放政府数据,以及如何以Web本体语言对整个堆栈进行形式化。我们使用选举领域的研究来评估我们方法的可行性和可用性。 (C)2018 Elsevier B.V.保留所有权利。

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