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Generating Executable Mappings from RDF Data Cube Data Structure Definitions

机译:从RDF数据多维数据集数据结构定义生成可执行映射

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Data processing is increasingly the subject of various internal and external regulations, such as GDPR which has recently come into effect. Instead of assuming that such processes avail of data sources (such as files and relational databases), we approach the problem in a more abstract manner and view these processes as taking datasets as input. These datasets are then created by pulling data from various data sources. Taking a W3C Recommendation for prescribing the structure of and for describing datasets, we investigate an extension of that vocabulary for the generation of executable R2RML mappings. This results in a top-down approach where one prescribes the dataset to be used by a data process and where to find the data, and where that prescription is subsequently used to retrieve the data for the creation of the dataset "just in time". We argue that this approach to the generation of an R2RML mapping from a dataset description is the first step towards policy-aware mappings, where the generation takes into account regulations to generate mappings that are compliant. In this paper, we describe how one can obtain an R2RML mapping from a data structure definition in a declarative manner using SPARQL CONSTRUCT queries, and demonstrate it using a running example. Some of the more technical aspects are also described.
机译:数据处理越来越成为各种内部和外部法规(例如最近生效的GDPR)的主题。我们没有假设这些过程可以利用数据源(例如文件和关系数据库),而是以一种更加抽象的方式解决了该问题,并将这些过程视为将数据集作为输入。然后,通过从各种数据源中提取数据来创建这些数据集。以W3C推荐标准来规定数据集的结构和描述数据集,我们研究了该词汇表的扩展,以生成可执行的R2RML映射。这导致一种自上而下的方法,其中规定了数据处理要使用的数据集以及在何处查找数据,并且随后使用该处方来检索数据以“及时”创建数据集。我们认为,这种从数据集描述生成R2RML映射的方法是朝着政策感知映射迈出的第一步,在这种策略中,生成考虑了规则以生成符合要求的映射。在本文中,我们描述了如何使用SPARQL CONSTRUCT查询以声明的方式从数据结构定义中获得R2RML映射,并通过一个运行示例进行演示。还描述了一些更多的技术方面。

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