在网络上发布链接的开放政府数据的方法:系统的映射和统一的过程模型

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Semantic Web Pub Date : 2022-02-08 DOI:10.3233/sw-222896
B. Penteado, J. Maldonado, Seiji Isotani
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引用次数: 5

摘要

自从许多国家开始发布开放数据以来,已经提出了不同的发布关联数据的方法。然而,由于不同的原因,它们似乎没有被早期探索关联数据的研究所采用。在这项工作中,我们在文献中进行了系统的映射,以综合围绕以下主题的不同方法:公共步骤,相关工具和实践,质量评估验证,以及方法的评估。研究结果显示了一组基于关联数据原则的核心活动,但也包含了用于大规模实际应用的额外关键步骤。此外,尽管文献中报道了相当数量的质量问题,但这些方法中很少在其过程中嵌入验证步骤。我们描述了不同活动的综合概述,以及如何使用适当的工具执行这些活动。我们还提出了在该领域未来工作中需要解决的研究挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methodologies for publishing linked open government data on the Web: A systematic mapping and a unified process model
Since the beginning of the release of open data by many countries, different methodologies for publishing linked data have been proposed. However, they seem not to be adopted by early studies exploring linked data for different reasons. In this work, we conducted a systematic mapping in the literature to synthesize the different approaches around the following topics: common steps, associated tools and practices, quality assessment validations, and evaluation of the methodology. The findings show a core set of activities, based on the linked data principles, but with additional critical steps for practical use in scale. Furthermore, although a fair amount of quality issues are reported in the literature, very few of these methodologies embed validation steps in their process. We describe an integrated overview of the different activities and how they can be executed with appropriate tools. We also present research challenges that need to be addressed in future works in this area.
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来源期刊
Semantic Web
Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍: The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.
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