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Metamorphic data sources: A user-centric paradigm to consume linked data in interactive workspaces

机译:变形数据源:以用户为中心的范例,用于在交互式工作空间中使用链接的数据

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摘要

In the last years, the debate about the success or failure of Linked Data (LD) has been growing. Despite the ever-increasing number of available ontologies and LD datasets, there is still a limited number of applications to let people benefit from using this huge amount of data. Some evident problems relate to the limited opportunities offered to the end users, i.e., people without skills in computer programming, to access, navigate and visualize LD. Tools supporting such tasks typically do not consider the end users' needs; even when they provide abstraction mechanisms to avoid programming, they do not properly hide the complexity of getting oriented into the plethora of available resources. Thus, they end up to be inadequate to real daily scenarios. In this paper, we propose an approach that enables end users to create visually entry points, which we call Metamorphic Data-Sources (MDSs), to query and visualize the LD without requiring any prior knowledge of semantic Web or visualization technologies. Through the MDS visual paradigm, end users can tailor ad-hoc data sources to retrieve information on topics they are interested in. The MDS creation process is also driven by a quality model that further helps users select LD elements potentially free of data quality problems. The paper also reports on the results of a user study that we conducted to assess the validity of the MDS paradigm with respect to the user needs. (C) 2019 Elsevier B.V. All rights reserved.
机译:在过去的几年中,有关链接数据(LD)成功或失败的争论一直在增长。尽管可用的本体和LD数据集数量不断增加,但仍然有数量有限的应用程序使人们可以从使用大量数据中受益。一些明显的问题与提供给最终用户(即没有计算机编程技能的人)访问,导航和可视化LD的机会有限有关。支持此类任务的工具通常不会考虑最终用户的需求。即使它们提供了避免编程的抽象机制,它们也没有适当地掩藏面向过多可用资源的复杂性。因此,它们最终不足以满足实际的日常情况。在本文中,我们提出了一种方法,使最终用户可以创建可视化的入口点(我们称为变形数据源(MDS))来查询和可视化LD,而无需任何语义Web或可视化技术的先验知识。通过MDS可视化范例,最终用户可以定制临时数据源以检索有关他们感兴趣的主题的信息。MDS创建过程还受质量模型的驱动,该模型进一步帮助用户选择可能没有数据质量问题的LD元素。本文还报告了我们进行的用户研究结果,以评估MDS范式相对于用户需求的有效性。 (C)2019 Elsevier B.V.保留所有权利。

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