Helio:实现知识图谱生命周期的框架

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Semantic Web Pub Date : 2023-01-12 DOI:10.3233/sw-233224
Andrea Cimmino, R. García-Castro
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引用次数: 4

摘要

构建和发布知识图(KG)作为关联数据,无论是在Web上还是在私人公司中,都已成为许多领域的相关和关键过程。这个过程要求用户执行大量符合KG生命周期的任务,这些任务通常涉及不同的不相关的研究主题,如RDF物化或链接发现。已经有大量的工具和方法被设计来执行这些任务;然而,缺乏一种工具来收集它们,导致从业者开发特别的管道,这些管道不是通用的,因此是不可重用的。因此,构建和发布KG正在成为一个复杂且消耗资源的过程。本文提出了一个通用的框架Helio。该框架旨在涵盖KG生命周期中产生的一系列需求,并提供一个能够执行构建和发布KG所需的不同任务的工具,因此,Helio旨在为用户提供减少执行此过程所需的工作量的方法,同时,Helio旨在防止开发ad-hoc管道。此外,Helio框架已应用于许多不同的环境,从欧洲项目到研究工作。
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Helio: A framework for implementing the life cycle of knowledge graphs
Building and publishing knowledge graphs (KG) as Linked Data, either on the Web or in private companies, has become a relevant and crucial process in many domains. This process requires that users perform a wide number of tasks conforming to the life cycle of a KG, and these tasks usually involve different unrelated research topics, such as RDF materialisation or link discovery. There is already a large corpus of tools and methods designed to perform these tasks; however, the lack of one tool that gathers them all leads practitioners to develop ad-hoc pipelines that are not generic and, thus, non-reusable. As a result, building and publishing a KG is becoming a complex and resource-consuming process. In this paper, a generic framework called Helio is presented. The framework aims to cover a set of requirements elicited from the KG life cycle and provide a tool capable of performing the different tasks required to build and publish KGs. As a result, Helio aims at providing users with the means for reducing the effort required to perform this process and, also, Helio aims to prevent the development of ad-hoc pipelines. Furthermore, the Helio framework has been applied in many different contexts, from European projects to research work.
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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.
期刊最新文献
Wikidata subsetting: Approaches, tools, and evaluation An ontology of 3D environment where a simulated manipulation task takes place (ENVON) Sem@ K: Is my knowledge graph embedding model semantic-aware? Using semantic story maps to describe a territory beyond its map NeuSyRE: Neuro-symbolic visual understanding and reasoning framework based on scene graph enrichment
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