Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371)
Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371)
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DOI：
10.4230/dagrep.8.9.29
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发表时间：
2019-03
期刊：
影响因子：
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通讯作者：
P. Bonatti;S. Decker;A. Polleres;V. Presutti
中科院分区：
文献类型：
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作者：
P. Bonatti;S. Decker;A. Polleres;V. Presutti
网络日益普及的本质，扩展到日常生活中的设备和事物，以及人工智能的新趋势，要求语义网的新范式和知识表示和处理的新视角。“知识图谱”这一新兴但仍有待具体形成的概念为语义网研究的现状提供了一个极好的统一隐喻。二十多年的语义网研究为互连网络上的数据、本体和知识提供了坚实的基础和有前途的技术和标准堆栈。然而，知识图的应用程序并不局限于链接开放数据，企业中的知识图实例也不局限于核心语义Web堆栈（虽然经常受到启发）。本报告记录了Dagstuhl研讨会18371“知识图谱：语义网上知识表示的新方向”的计划和成果，来自学术界和工业界的一组专家在2018年9月初的一周内围绕这些主题讨论了基本问题，包括以下内容：我们看到哪些应用会出现？哪些开放的研究问题仍然需要解决，哪些技术差距仍然需要缩小？
The increasingly pervasive nature of the Web, expanding to devices and things in everyday life, along with new trends in Artificial Intelligence call for new paradigms and a new look on Knowledge Representation and Processing at scale for the Semantic Web. The emerging, but still to be concretely shaped concept of "Knowledge Graphs" provides an excellent unifying metaphor for this current status of Semantic Web research. More than two decades of Semantic Web research provides a solid basis and a promising technology and standards stack to interlink data, ontologies and knowledge on the Web. However, neither are applications for Knowledge Graphs as such limited to Linked Open Data, nor are instantiations of Knowledge Graphs in enterprises – while often inspired by – limited to the core Semantic Web stack. This report documents the program and the outcomes of Dagstuhl Seminar 18371 "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web", where a group of experts from academia and industry discussed fundamental questions around these topics for a week in early September 2018, including the following: what are knowledge graphs? Which applications do we see to emerge? Which open research questions still need be addressed and which technology gaps still need to be closed?