Three-dimensional Geospatial Interlinking with JedAI-spatial

IF 2.1 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Web Semantics Pub Date : 2024-03-24 DOI:10.1016/j.websem.2024.100817

Marios Papamichalopoulos , George Papadakis , George Mandilaras , Maria Siampou , Nikos Mamoulis , Manolis Koubarakis

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引用次数: 0

Abstract

Geospatial data constitutes a considerable part of Semantic Web data, but so far, its sources are inadequately interlinked in the Linked Open Data cloud. Geospatial Interlinking aims to cover this gap by associating geometries with topological relations like those of the Dimensionally Extended 9-Intersection Model. Due to its quadratic time complexity, various algorithms aim to carry out Geospatial Interlinking efficiently. We present JedAI-spatial, a novel, open-source system that organizes these algorithms according to three dimensions: (i) Space Tiling, which determines the approach that reduces the search space, (ii) Budget-awareness, which distinguishes interlinking algorithms into batch and progressive ones, and (iii) Execution mode, which discerns between serial algorithms, running on a single CPU-core, and parallel ones, running on top of Apache Spark. We analytically describe JedAI-spatial’s architecture and capabilities and perform thorough experiments to provide interesting insights about the relative performance of its algorithms.

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利用 JedAI-spatial 实现三维地理空间互联

地理空间数据在语义网数据中占有相当大的比重，但迄今为止，其来源在关联开放数据云中的互联程度还不够。地理空间互联旨在通过将几何图形与拓扑关系（如维度扩展九交模型的拓扑关系）相关联来弥补这一不足。由于其二次方时间复杂性，各种算法都旨在高效地进行地理空间互联。我们介绍了 JedAI-spatial，这是一个新颖的开源系统，它根据三个维度对这些算法进行了组织：(i) 空间平铺（Space Tiling），它决定了缩小搜索空间的方法；(ii) 预算感知（Budget-awareness），它将相互链接算法区分为批处理算法和渐进算法；(iii) 执行模式（Execution mode），它区分了在单 CPU 内核上运行的串行算法和在 Apache Spark 上运行的并行算法。我们对 JedAI-spatial 的架构和功能进行了分析描述，并进行了全面的实验，以提供有关其算法相对性能的有趣见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Web Semantics 工程技术-计算机：人工智能

CiteScore

6.20

自引率

12.00%

发文量

审稿时长

14.6 weeks

期刊介绍： The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.