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Semantic Web technologies and bias in artificial intelligence: A systematic literature review 语义网技术与人工智能中的偏见:系统的文献综述
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-09-05 DOI: 10.3233/sw-223041
Paula Reyero-Lobo, E. Daga, Harith Alani, Miriam Fernández
Bias in Artificial Intelligence (AI) is a critical and timely issue due to its sociological, economic and legal impact, as decisions made by biased algorithms could lead to unfair treatment of specific individuals or groups. Multiple surveys have emerged to provide a multidisciplinary view of bias or to review bias in specific areas such as social sciences, business research, criminal justice, or data mining. Given the ability of Semantic Web (SW) technologies to support multiple AI systems, we review the extent to which semantics can be a “tool” to address bias in different algorithmic scenarios. We provide an in-depth categorisation and analysis of bias assessment, representation, and mitigation approaches that use SW technologies. We discuss their potential in dealing with issues such as representing disparities of specific demographics or reducing data drifts, sparsity, and missing values. We find research works on AI bias that apply semantics mainly in information retrieval, recommendation and natural language processing applications and argue through multiple use cases that semantics can help deal with technical, sociological, and psychological challenges.
由于人工智能(AI)的社会、经济和法律影响,偏见是一个关键而及时的问题,因为有偏见的算法做出的决定可能导致对特定个人或群体的不公平对待。已经出现了多种调查,以提供偏见的多学科观点或审查特定领域的偏见,如社会科学,商业研究,刑事司法或数据挖掘。鉴于语义网(SW)技术支持多种人工智能系统的能力,我们回顾了语义在多大程度上可以成为解决不同算法场景中偏见的“工具”。我们对使用软件技术的偏见评估、表示和缓解方法进行了深入的分类和分析。我们讨论了它们在处理诸如表示特定人口统计差异或减少数据漂移、稀疏性和缺失值等问题方面的潜力。我们发现人工智能偏差的研究工作主要将语义应用于信息检索、推荐和自然语言处理应用,并通过多个用例论证语义可以帮助处理技术、社会学和心理挑战。
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引用次数: 0
Characteristic sets profile features: Estimation and application to SPARQL query planning 特征集概要特征:SPARQL查询计划的估计和应用
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-09-05 DOI: 10.3233/sw-222903
Lars Heling, Maribel Acosta
RDF dataset profiling is the task of extracting a formal representation of a dataset’s features. Such features may cover various aspects of the RDF dataset ranging from information on licensing and provenance to statistical descriptors of the data distribution and its semantics. In this work, we focus on the characteristics sets profile features that capture both structural and semantic information of an RDF dataset, making them a valuable resource for different downstream applications. While previous research demonstrated the benefits of characteristic sets in centralized and federated query processing, access to these fine-grained statistics is taken for granted. However, especially in federated query processing, computing this profile feature is challenging as it can be difficult and/or costly to access and process the entire data from all federation members. We address this shortcoming by introducing the concept of a profile feature estimation and propose a sampling-based approach to generate estimations for the characteristic sets profile feature. In addition, we showcase the applicability of these feature estimations in federated querying by proposing a query planning approach that is specifically designed to leverage these feature estimations. In our first experimental study, we intrinsically evaluate our approach on the representativeness of the feature estimation. The results show that even small samples of just 0.5 % of the original graph’s entities allow for estimating both structural and statistical properties of the characteristic sets profile features. Our second experimental study extrinsically evaluates the estimations by investigating their applicability in our query planner using the well-known FedBench benchmark. The results of the experiments show that the estimated profile features allow for obtaining efficient query plans.
RDF数据集概要是提取数据集特征的形式化表示的任务。这些特性可能涵盖RDF数据集的各个方面,从许可和来源信息到数据分布及其语义的统计描述符。在这项工作中,我们专注于特征集概要特征,这些特征集捕获RDF数据集的结构和语义信息,使它们成为不同下游应用程序的宝贵资源。虽然以前的研究证明了特征集在集中式和联邦查询处理中的好处,但对这些细粒度统计数据的访问被认为是理所当然的。但是,特别是在联邦查询处理中,计算这个概要特性是具有挑战性的,因为访问和处理来自所有联邦成员的全部数据可能很困难,而且/或成本很高。我们通过引入轮廓特征估计的概念来解决这一缺点,并提出了一种基于采样的方法来生成特征集轮廓特征的估计。此外,我们通过提出一种专门为利用这些特征估计而设计的查询规划方法,展示了这些特征估计在联邦查询中的适用性。在我们的第一个实验研究中,我们从本质上评估了我们的方法对特征估计的代表性。结果表明,即使只有原始图实体的0.5%的小样本也可以估计特征集轮廓特征的结构和统计特性。我们的第二个实验研究通过使用著名的FedBench基准测试调查它们在我们的查询规划器中的适用性,从外部评估这些估计。实验结果表明,估计的轮廓特征可以获得有效的查询计划。
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引用次数: 1
RelTopic: A graph-based semantic relatedness measure in topic ontologies and its applicability for topic labeling of old press articles RelTopic:主题本体中基于图的语义关联度量及其在旧版新闻文章主题标注中的适用性
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-09-01 DOI: 10.3233/sw-222919
M. E. Ghosh, Nicolas Delestre, Jean-Philippe Kotowicz, C. Zanni-Merk, H. Abdulrab
Graph-based semantic measures have been used to solve problems in several domains. They tend to compare semantic entities in order to estimate their similarity or relatedness. While semantic similarity is applicable to hierarchies or taxonomies, semantic relatedness is adapted to ontologies. In this work, we propose a novel semantic relatedness measure, named Rel Topic , within topic ontologies for topic labeling purposes. In contrast to traditional measures, which are dependent on textual resources, Rel Topic considers semantic properties of entities in ontologies. Thus, correlations of nodes and weights of nodes and edges are assessed. The pertinence of Rel Topic is evaluated for topic labeling of old press articles. For this purpose, a topic ontology representing the articles, named Topic-OPA, is derived from open knowledge graphs by applying a SPARQL-based automatic approach. A use-case is presented in the context of the old French newspaper Le Matin. The generated topics are evaluated using a dual evaluation approach with the help of human annotators. Our approach shows an agreement quite close to that shown by humans. The entire approach’s reuse is demonstrated for labeling a different context of articles, recent (modern) newspapers.
基于图的语义度量已被用于解决多个领域的问题。他们倾向于比较语义实体,以估计它们的相似性或相关性。语义相似性适用于层次结构或分类法,而语义相关性适用于本体。在这项工作中,我们提出了一个新的语义相关性度量,命名为Rel Topic,在主题本体中用于主题标记目的。与依赖文本资源的传统度量不同,Rel Topic考虑本体中实体的语义属性。因此,评估节点的相关性以及节点和边的权重。对旧版报刊文章的主题标注进行了相关性评价。为此,通过应用基于sparql的自动方法,从开放知识图派生出一个表示文章的主题本体,名为topic - opa。在旧的法国报纸《晨报》的上下文中给出了一个用例。生成的主题在人工注释器的帮助下使用双重评估方法进行评估。我们的方法显示了与人类所显示的非常接近的一致性。整个方法的重用演示了标记文章的不同上下文,最近(现代)报纸。
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引用次数: 1
Analyzing biography collections historiographically as Linked Data: Case National Biography of Finland 作为关联数据的传记集的历史分析:芬兰国家传记案例
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-30 DOI: 10.3233/sw-222887
Minna Tamper, Petri Leskinen, E. Hyvönen, Risto Valjus, Kirsi Keravuori
Biographical collections are available on the Web for close reading. However, the underlying texts can also be used for data analysis and distant reading, if the documents are available as data. Such data is usable for creating intelligent user interfaces to biographical data, including Digital Humanities tooling for visualizations, data analysis, and knowledge discovery in biographical and prosopographical research. In this paper, we re-use biographical collection data from a historiographical perspective for analyzing the underlying collection. For example: What kind of people have been included in the collection? Does the language used for describing female biographees differ from that for men? As a case study, the Finnish National Biography, available as part of the Linked Open Data service and semantic portal BiographySampo – Finnish Biographies on the Semantic Web is used. The analyses show interesting results related to, e.g., how specific prosopographical groups, such as women or professional groups are represented and portrayed. Various novel statistics and network analyses of the biographees are presented. Our analyses give new insights to the editors of the National Biography as well as to researchers in biography, prosopography, and historiography. The presented approach can be applied also to similar biography collections in other countries.
个人传记集可以在网上仔细阅读。但是,如果文档作为数据可用,则底层文本也可以用于数据分析和远程读取。这些数据可用于创建传记数据的智能用户界面,包括用于可视化、数据分析和传记和人文学研究中的知识发现的数字人文工具。在本文中,我们从史学的角度重新使用传记收集数据来分析潜在的收集。例如:什么样的人被包括在收藏中?描述女性传记的语言与描述男性传记的语言不同吗?作为一个案例研究,芬兰国家传记作为链接开放数据服务和语义门户bioysampo -芬兰传记语义网的一部分被使用。这些分析显示了有趣的结果,例如,如何代表和描绘特定的人文学群体,如妇女或专业群体。各种新的统计和网络分析的传记提出。我们的分析为《国家传记》的编辑以及传记、传记学和史学方面的研究人员提供了新的见解。所提出的方法也可以应用于其他国家类似的传记收藏。
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引用次数: 18
Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science 蓝脑Nexus:一个开放、安全、可扩展的知识图谱管理和数据驱动科学系统
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-30 DOI: 10.3233/sw-222974
M. Sy, Bogdan Roman, Samuel Kerrien, Didac Montero Mendez, Henry Genet, Wojciech Wajerowicz, Michaël Dupont, Ian Lavriushev, Julien Machon, Kenneth Pirman, Dhanesh Neela Mana, Natalia Stafeeva, Anna-Kristin Kaufmann, Huanxiang Lu, Jonathan Lurie, Pierre-Alexandre Fonta, Alejandra Garcia Rojas Martinez, Alexander Ulbrich, Carolina Lindqvist, Silvia Jimenez, D. Rotenberg, H. Markram, Sean L. Hill
Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simulating the whole rodent brain in the Swiss EPFL Blue Brain Project (BBP) required a solution to managing large-scale highly heterogeneous data, and tracking their provenance to ensure quality, reproducibility and attribution throughout these iterative cycles. Here, we describe Blue Brain Nexus (BBN), an ecosystem of open source, domain agnostic, scalable, extensible data and knowledge graph management systems built by BBP to address these challenges. BBN builds on open standards and interoperable semantic web technologies to enable the creation and management of secure RDF-based knowledge graphs validated by W3C SHACL. BBN supports a spectrum of (meta)data modeling and representation formats including JSON and JSON-LD as well as more formally specified SHACL-based schemas enabling domain model-driven runtime API. With its streaming event-based architecture, BBN supports asynchronous building and maintenance of multiple extensible indices to ensure high performance search capabilities and enable analytics. We present four use cases and applications of BBN to large-scale data integration and dissemination challenges in computational modeling, neuroscience, psychiatry and open linked data.
现代数据驱动的科学通常由数据发现、获取、准备、分析、模型构建和验证的迭代周期组成,从而导致知识发现和大规模传播。在瑞士EPFL蓝脑项目(BBP)中,构建和模拟整个啮齿动物大脑的独特挑战需要一个解决方案来管理大规模高度异构的数据,并跟踪它们的来源,以确保在这些迭代周期中的质量、可重复性和归属。在这里,我们描述了蓝脑Nexus (BBN),这是一个开源、领域不可知、可扩展、可扩展的数据和知识图谱管理系统的生态系统,由BBP建立,以应对这些挑战。BBN建立在开放标准和可互操作的语义web技术之上,能够创建和管理经W3C SHACL验证的基于rdf的安全知识图谱。BBN支持一系列(元)数据建模和表示格式,包括JSON和JSON- ld,以及更正式指定的基于sha的模式,这些模式支持域模型驱动的运行时API。凭借其基于流事件的架构,BBN支持异步构建和维护多个可扩展索引,以确保高性能搜索功能并启用分析。我们提出了四个用例和BBN在计算建模、神经科学、精神病学和开放关联数据方面的大规模数据集成和传播挑战的应用。
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引用次数: 2
Move cultural heritage knowledge graphs in everyone’s pocket 把文化遗产知识图谱搬到每个人的口袋里
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-29 DOI: 10.3233/sw-223117
Maria Angela Pellegrino, Vittorio Scarano, Carmine Spagnuolo

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.

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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引用次数: 0
Paving the way for enriched metadata of linguistic linked data 为语言关联数据的丰富元数据铺平了道路
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-29 DOI: 10.3233/sw-222994
Maria Pia di Buono, Hugo Gonçalo Oliveira, V. Mititelu, Blerina Spahiu, Gennaro Nolano
The need for reusable, interoperable, and interlinked linguistic resources in Natural Language Processing downstream tasks has been proved by the increasing efforts to develop standards and metadata suitable to represent several layers of information. Nevertheless, despite these efforts, the achievement of full compatibility for metadata in linguistic resource production is still far from being reached. Access to resources observing these standards is hindered either by (i) lack of or incomplete information, (ii) inconsistent ways of coding their metadata, and (iii) lack of maintenance. In this paper, we offer a quantitative and qualitative analysis of descriptive metadata and resources availability of two main metadata repositories: LOD Cloud and Annohub. Furthermore, we introduce a metadata enrichment, which aims at improving resource information, and a metadata alignment to META-SHARE ontology, suitable for easing the accessibility and interoperability of such resources.
在自然语言处理下游任务中,对可重用、可互操作和相互关联的语言资源的需求已经通过开发适合表示多层信息的标准和元数据的不断努力得到了证明。然而,尽管做出了这些努力,在语言资源生产中实现元数据的完全兼容仍远未达到。访问符合这些标准的资源受到以下因素的阻碍:(i)缺乏或不完整的信息,(ii)对其元数据进行编码的方式不一致,以及(iii)缺乏维护。在本文中,我们对两个主要元数据存储库(LOD Cloud和Annohub)的描述性元数据和资源可用性进行了定量和定性分析。此外,我们还引入了元数据丰富,旨在改善资源信息,以及元数据与META-SHARE本体的对齐,适合于简化这些资源的可访问性和互操作性。
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引用次数: 2
Digital humanities on the Semantic Web: Sampo model and portal series 语义网上的数字人文:Sampo模型与门户系列
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-29 DOI: 10.3233/sw-223034
E. Hyvönen
Cultural heritage (CH) contents are typically strongly interlinked, but published in heterogeneous, distributed local data silos, making it difficult to utilize the data on a global level. Furthermore, the content is usually available only for humans to read, and not as data for Digital Humanities (DH) analyses and application development. This application report addresses these problems by presenting a collaborative publication model for CH Linked Data and six design principles for creating shared data services and semantic portals for DH research and applications. This Sampo model has evolved gradually in 2002–2021 through lessons learned when developing the Sampo series of linked data services and semantic portals in use, including MuseumFinland (2004), CultureSampo (2009), BookSampo (2011), WarSampo (2015), Norssit Alumni (2017), U.S. Congress Prosopographer (2018), NameSampo (2019), BiographySampo (2019), WarVictimSampo 1914–1922 (2019), MMM (2020), AcademySampo (2021), FindSampo (2021), WarMemoirSampo (2021), and LetterSampo (2022). These Semantic Web applications surveyed in this paper cover a wide range of application domains in CH and have attracted up to millions of users on the Semantic Web, suggesting feasibility of the proposed Sampo model. This work shows a shift of focus in research on CH semantic portals from data aggregation and exploration systems (1. generation systems) to systems supporting DH research (2. generation systems) with data analytic tools, and finally to automatic knowledge discovery and Artificial Intelligence (3. generation systems).
文化遗产(CH)内容通常紧密相连,但发布在异构的、分布式的本地数据筒仓中,因此很难在全球层面上利用这些数据。此外,这些内容通常只供人类阅读,而不是作为数字人文(DH)分析和应用程序开发的数据。本应用报告通过提出卫生保健关联数据的协作发布模型和为卫生保健研究和应用程序创建共享数据服务和语义门户的六项设计原则来解决这些问题。这种Sampo模式在2002-2021年通过开发Sampo系列关联数据服务和使用的语义门户的经验教训逐渐发展,包括MuseumFinland (2004), CultureSampo (2009), BookSampo (2011), WarSampo (2015), Norssit Alumni(2017),美国国会Prosopographer (2018), NameSampo(2019),传记Sampo (2019), war受害者Sampo 1914-1922 (2019), MMM (2020), AcademySampo (2021), FindSampo (2021), WarMemoirSampo(2021)和LetterSampo(2022)。本文调查的这些语义Web应用程序涵盖了语义Web的广泛应用领域,并在语义Web上吸引了多达数百万的用户,这表明所提出的Sampo模型的可行性。这项工作显示了CH语义门户研究的重点从数据聚合和探索系统(1)转移。生成系统)到支持DH研究的系统(2)。生成系统)与数据分析工具,最后到自动知识发现和人工智能(3)。一代系统)。
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引用次数: 42
Typed properties and negative typed properties: Dealing with type observations and negative statements in the CIDOC CRM 类型化属性和否定类型化属性:处理CIDOC CRM中的类型观察和否定语句
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-29 DOI: 10.3233/sw-223159
A. Velios, C. Meghini, M. Doerr, Stephen Stead
A typical case of producing records within the domain of conservation of cultural heritage is considered. During condition and collection surveys in memory organisations, surveyors observe types of multiple components of an object but without creating a record for each one. They also observe the absence of components. Such observations are significant to researchers and are documented in registration forms but they are not easy to implement using popular ontologies, such as the CIDOC CRM which primarily consider individuals. In this paper techniques for expressing such observations within the context of the CIDOC CRM in both OWL and RDFS are explored. OWL cardinality restrictions are considered and new special properties deriving from the CIDOC CRM are proposed, namely ‘typed properties’ and ‘negative typed properties’ which allow stating the types of multiple individuals and the absence of individuals. The nature of these properties is then explored in relation to their correspondence to longer property paths, their hierarchical arrangement and relevance to thesauri. An example from bookbinding history is used alongside a demonstration of the proposed solution with a dataset from the library collection of the Saint Catherine Monastery in Sinai, Egypt.
考虑了在文化遗产保护领域内制作记录的一个典型案例。在记忆组织的条件和收集调查中,调查者观察一个对象的多个组成部分,但不为每一个组成部分创建记录。他们还观察到组件的缺失。这些观察结果对研究人员来说很重要,并记录在注册表格中,但它们不容易使用流行的本体来实现,例如主要考虑个人的CIDOC CRM。本文探讨了在OWL和RDFS的CIDOC CRM背景下表达这些观测结果的技术。考虑了OWL的基数限制,并提出了从cdoc CRM衍生出来的新的特殊属性,即“类型化属性”和“负类型化属性”,它们允许声明多个个体的类型和个体的缺席。这些属性的性质,然后探讨其对应的较长的属性路径,他们的层次安排和相关的叙词表。一个来自装订历史的例子与来自埃及西奈圣凯瑟琳修道院图书馆馆藏的数据集一起演示了所提出的解决方案。
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引用次数: 1
Security approaches for electronic health data handling through the Semantic Web: A scoping review 通过语义网处理电子健康数据的安全方法:范围审查
IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Pub Date : 2022-08-29 DOI: 10.3233/sw-223088
V. Lima, Domingos Alves, F. Bernardi, R. Rijo
Integration of health information systems are crucial to advance the effective delivery of healthcare for individuals and communities across organizational boundaries. Semantic Web technologies may be used to connect, correlate, and integrate heterogeneous datasets spread over the internet. However, when working with sensitive data, such as health data, security mechanisms are needed. A scoping review of the literature was undertaken to provide a broad view of security mechanisms applied to, or along with, Semantic Web technologies that could allow its use with health data. Searches were conducted in the most relevant databases for the scope of this work. The findings were classified according to the main objective and features presented by each solution. Twenty-six studies were included in the review. They introduced mechanisms that addressed several security attributes, such as authentication, authorization, integrity, availability, confidentiality, privacy, and provenance. These mechanisms support access control frameworks, semantic and functional interoperability infrastructures, and privacy compliance solutions. The findings suggest that the application and use of Semantic Web technologies is still growing, with the healthcare area being particularly interested. The main security mechanisms for Semantic Web technologies, the key security attributes and properties, and the main gaps in the literature were identified, helping to understand the technical needs to mitigate the risks of handling personal health information over the Semantic Web. Also, this research has shown that complex and robust solutions are available to successfully address several security properties and features, depending on the context that the electronic health data is being managed.
卫生信息系统的整合对于促进跨组织边界为个人和社区提供有效的卫生保健至关重要。语义Web技术可用于连接、关联和集成分布在互联网上的异构数据集。但是,在处理敏感数据(如健康数据)时,需要使用安全机制。对文献进行了范围审查,以提供应用于或与语义Web技术一起使用的安全机制的广泛视图,从而允许将其用于健康数据。在最相关的数据库中对这项工作的范围进行了搜索。根据每个解决方案的主要目标和特征对结果进行分类。该综述纳入了26项研究。他们引入了解决几个安全属性的机制,例如身份验证、授权、完整性、可用性、机密性、隐私性和来源。这些机制支持访问控制框架、语义和功能互操作性基础设施以及隐私遵从性解决方案。研究结果表明,语义Web技术的应用和使用仍在增长,医疗保健领域尤其感兴趣。识别了语义Web技术的主要安全机制、关键安全属性和属性以及文献中的主要空白,有助于了解通过语义Web处理个人健康信息的技术需求,以降低风险。此外,该研究还表明,根据管理电子健康数据的上下文,可以使用复杂而强大的解决方案来成功解决若干安全属性和功能。
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引用次数: 1
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