海量图的隐喻

Aaron Eberhart, P. Haase, Wolfgang Schell
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引用次数: 0

摘要

知识图谱和语义技术允许科学家和领域专家以逻辑结构化和机器可读格式对数据之间的复杂关系进行建模。隐喻是一个平台,使用户能够轻松有效地构建这些类型的语义图。隐喻使用RDF等标准与OWL、SKOS、SHACL等结合使用,以提供灵活的端点与不同复杂性和表达能力的图进行交互。作为Graph-Massivizer项目的一部分,metaphtory正在支持项目中开发的组件的集成和基础设施整合。这项工作的一部分是开发一个工具包,该工具包用于在不牺牲可持续性的情况下处理非常大的图形。在本文中,我们详细描述了隐喻平台,以及它如何在graph - massivizer项目中支持大规模图形处理,并概述了项目中当前的努力,以及他们如何提高当前的能力以支持未来的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
metaphactory for Massive Graphs
Knowledge Graphs and semantic technologies allow scientists and domain experts to model complex relations between data in a logically structured and machine readable format. metaphactory is a platform that enables users to build these kinds of semantic graphs easily and efficiently. metaphactory uses standards such as RDF in combination with OWL, SKOS, SHACL, and others to provide a flexible endpoint to interact with graphs of varying complexity and expressivity. As part of the Graph-Massivizer project, metaphactory is supporting integration and infrastructure consolidation for components developed in the project. Part of this work is to develop a toolkit which metaphactory uses to process very large graphs without sacrificing sustainability. In this paper we describe in detail the metaphactory platform and how it supports large-scale graph processing in the Graph-Massivizer project, as well as outlining the current efforts within the project and how they aim to increase capabilities in the present to support future work.
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