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Directing the Development of Constraint Languages by Checking Constraints on RDF Data

机译:通过检查RDF数据的约束来指导约束语言的开发

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摘要

For research institutes, data libraries, and data archives, validating RDF data according to predefined constraints is a much sought-after feature, particularly as this is taken for granted in the XML world. Based on our work in two international working groups on RDF validation and jointly identified requirements to formulate constraints and validate RDF data, we have published 81 types of constraints that are required by various stakeholders for data applications. In this paper, we evaluate the usability of identified constraint types for assessing RDF data quality by (1) collecting and classifying 115 constraints on vocabularies commonly used in the social, behavioral, and economic sciences, either from the vocabularies themselves or from domain experts, and (2) validating 15,694 data sets (4.26 billion triples) of research data against these constraints. We classify each constraint according to (1) the severity of occurring violations and (2) based on which types of constraint languages are able to express its constraint type. Based on the large-scale evaluation, we formulate several findings to direct the further development of constraint languages.
机译:对于研究机构,数据库和数据档案馆而言,根据预定义的约束条件验证RDF数据是一个非常受欢迎的功能,尤其是在XML世界中,这是理所当然的。基于我们在两个有关RDF验证的国际工作组中的工作,并共同确定了制定约束和验证RDF数据的要求,我们发布了81种类型的约束,这些约束是各种利益相关者进行数据应用所需的。在本文中,我们通过(1)从词汇表本身或领域专家那里收集,分类社会,行为和经济科学中常用的词汇表上的115种约束条件,来评估确定的约束类型在评估RDF数据质量方面的可用性, (2)根据这些约束条件验证研究数据的15694个数据集(42.6亿个三倍)。我们根据(1)发生违规的严重性和(2)基于哪种约束语言能够表达其约束类型来对每个约束进行分类。在大规模评估的基础上,我们提出了一些发现,以指导约束语言的进一步发展。

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