链接开放数据的模式提取和可视化

Chutiporn Anutariya, Reshma Dangol
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引用次数: 9

摘要

尽管关联开放数据的概念已经存在了二十多年,但理解一个新的数据集仍然是一项具有挑战性的任务,需要大量的时间和精力。它本身集成多个本体/词汇表的灵活性带来了挑战,因为它导致难以理解数据集的模式。在本文中,我们提出了一个基于web的工具VizLOD,它基于LOD数据源中的三元组推断本体特征来提取模式信息。SPARQL查询用于此目的。提取的模式信息使用交互式节点链接图进行可视化,从而减轻了用户的认知负担。为了使数据集更加清晰,实例视图还以表格形式和实例级图的形式提供。我们的初步实验显示了VizLOD的一些有希望的结果。
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VizLOD: Schema Extraction And Visualization Of Linked Open Data
Even though the concept of Linked Open Data has been around for over two decades, understanding a new dataset still remains as a challenging task demanding lot of time and effort. Its flexibility of integrating multiple ontolo-gies/vocabularies in itself creates a challenge as it leads to difficulty in understanding the schema of the dataset. In this paper, we propose VizLOD, a web based tool that extracts schema information by inferring ontological characteristics based on the triples in the LOD data sources. SPARQL queries are used for this purpose. The extracted schema information is visualized using an interactive node-link graph that eases the cognitive load on the users. To add clarity to the dataset, instance view is also provided in tabular form and as an instance level graph. Our preliminary experiments have shown some promising results for VizLOD.
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