Move cultural heritage knowledge graphs in everyone’s pocket

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Semantic Web Pub Date : 2022-08-29 DOI:10.3233/sw-223117
Maria Angela Pellegrino, Vittorio Scarano, Carmine Spagnuolo
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引用次数: 0

Abstract

Last years witnessed a shift from the potential utility in digitisation to a crucial need to enjoy activities virtually. In fact, before 2019, data curators recognised the utility of performing data digitisation, while during the lockdown caused by the COVID-19, investing in virtual and remote activities to make culture survive became crucial as no one could enjoy Cultural Heritage in person. The Cultural Heritage community heavily invested in digitisation campaigns, mainly modelling data as Knowledge Graphs by becoming one of the most successful Semantic Web technologies application domains.

Despite the vast investment in Cultural Heritage Knowledge Graphs, the syntactic complexity of RDF query languages, e.g., SPARQL, negatively affects and threatens data exploitation, risking leaving this enormous potential untapped. Thus, we aim to support the Cultural Heritage community (and everyone interested in Cultural Heritage) in querying Knowledge Graphs without requiring technical competencies in Semantic Web technologies.

We propose an engaging exploitation tool accessible to all without losing sight of developers’ technological challenges. Engagement is achieved by letting the Cultural Heritage community leave the passive position of the visitor and actively create their Virtual Assistant extensions to exploit proprietary or public Knowledge Graphs in question-answering. By accessible to all, we mean that the proposed software framework is freely available on GitHub and Zenodo with an open-source license. We do not lose sight of developers’ technical challenges, which are carefully considered in the design and evaluation phases.

This article first analyses the effort invested in publishing Cultural Heritage Knowledge Graphs to quantify data developers can rely on in designing and implementing data exploitation tools in this domain. Moreover, we point out challenges developers may face in exploiting them in automatic approaches. Second, it presents a domain-agnostic Knowledge Graph exploitation approach based on virtual assistants as they naturally enable question-answering features where users formulate questions in natural language directly by their smartphones. Then, we discuss the design and implementation of this approach within an automatic community-shared software framework (a.k.a. generator) of virtual assistant extensions and its evaluation in terms of performance and perceived utility according to end-users. Finally, according to a taxonomy of the Cultural Heritage field, we present a use case for each category to show the applicability of the proposed approach in the Cultural Heritage domain. In overviewing our analysis and the proposed approach, we point out challenges that a developer may face in designing virtual assistant extensions to query Knowledge Graphs, and we show the effect of these challenges in practice.

把文化遗产知识图谱搬到每个人的口袋里
摘要过去几年见证了从数字化的潜在效用到虚拟享受活动的关键需求的转变。事实上,在2019年之前,数据策展人认识到执行数据数字化的效用,而在2019冠状病毒病造成的封锁期间,投资于虚拟和远程活动以使文化得以生存至关重要,因为没有人能够亲自欣赏文化遗产。文化遗产社区在数字化活动中投入了大量资金,主要是通过成为最成功的语义网技术应用领域之一,将数据建模为知识图。尽管在文化遗产知识图上投入了大量资金,但是RDF查询语言(例如SPARQL)的语法复杂性对数据利用产生了负面影响和威胁,有可能使这一巨大的潜力未被开发。因此,我们的目标是支持文化遗产社区(以及对文化遗产感兴趣的每个人)查询知识图,而不需要语义Web技术的技术能力。我们提出了一种引人入胜的开发工具,所有人都可以使用,而不会忽视开发人员的技术挑战。通过让文化遗产社区离开访问者的被动位置,并积极创建他们的虚拟助理扩展,以利用专有或公共知识图谱来回答问题,从而实现参与度。通过对所有人开放,我们的意思是提议的软件框架可以在GitHub和Zenodo上免费获得开源许可证。我们不会忽视开发人员的技术挑战,这些挑战在设计和评估阶段被仔细考虑。本文首先分析了在发布文化遗产知识图谱方面投入的努力,以量化开发人员在设计和实现该领域的数据开发工具时可以依赖的数据。此外,我们指出了开发人员在自动化方法中利用它们可能面临的挑战。其次,它提出了一种基于虚拟助手的领域不可知论知识图谱开发方法,因为虚拟助手自然地启用了问答功能,用户可以直接通过智能手机用自然语言提出问题。然后,我们讨论了该方法在虚拟助手扩展的自动社区共享软件框架(又名生成器)中的设计和实现,以及根据最终用户对其性能和感知效用的评估。最后,根据文化遗产领域的分类,我们为每个类别提供了一个用例,以显示所提出的方法在文化遗产领域的适用性。在概述我们的分析和提出的方法时,我们指出了开发人员在设计查询知识图的虚拟助手扩展时可能面临的挑战,并展示了这些挑战在实践中的影响。
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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.
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