{"title":"Can you trust Wikidata?","authors":"V. Santos, Daniel Schwabe, Sérgio Lifschitz","doi":"10.3233/sw-243577","DOIUrl":null,"url":null,"abstract":"In order to use a value retrieved from a Knowledge Graph (KG) for some computation, the user should, in principle, ensure that s/he trusts the veracity of the claim, i.e., considers the statement as a fact. Crowd-sourced KGs, or KGs constructed by integrating several different information sources of varying quality, must be used via a trust layer. The veracity of each claim in the underlying KG should be evaluated, considering what is relevant to carrying out some action that motivates the information seeking. The present work aims to assess how well Wikidata (WD) supports the trust decision process implied when using its data. WD provides several mechanisms that can support this trust decision, and our KG Profiling, based on WD claims and schema, elaborates an analysis of how multiple points of view, controversies, and potentially incomplete or incongruent content are presented and represented.","PeriodicalId":48694,"journal":{"name":"Semantic Web","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Semantic Web","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3233/sw-243577","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
In order to use a value retrieved from a Knowledge Graph (KG) for some computation, the user should, in principle, ensure that s/he trusts the veracity of the claim, i.e., considers the statement as a fact. Crowd-sourced KGs, or KGs constructed by integrating several different information sources of varying quality, must be used via a trust layer. The veracity of each claim in the underlying KG should be evaluated, considering what is relevant to carrying out some action that motivates the information seeking. The present work aims to assess how well Wikidata (WD) supports the trust decision process implied when using its data. WD provides several mechanisms that can support this trust decision, and our KG Profiling, based on WD claims and schema, elaborates an analysis of how multiple points of view, controversies, and potentially incomplete or incongruent content are presented and represented.
为了在计算中使用从知识图谱(KG)中获取的值,用户原则上应确保其信任该声明的真实性,即认为该声明是事实。众包知识图谱或通过整合多个不同质量的信息源构建的知识图谱必须通过信任层来使用。应评估底层 KG 中每个声明的真实性,并考虑哪些声明与执行某些行动相关,从而激发信息搜索。本研究旨在评估维基数据(WD)对使用其数据时所隐含的信任决策过程的支持程度。维基数据提供了几种可以支持信任决策的机制,而我们基于维基数据声明和模式的KG剖析则详细分析了多种观点、争议以及潜在的不完整或不一致内容是如何呈现和表示的。
Semantic WebCOMPUTER 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.