Towards a moderate realist foundation for ontological knowledge organization systems: The question of the naturalness of classifications

IF 1.7 4区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Luís Miguel Oliveira Machado, D. Martínez-Ávila, M. Almeida, M. M. Borges
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引用次数: 0

Abstract

Several authors emphasise the need for a change in classification theory due to the influence of a dogmatic and monistic ontology supported by an outdated essentialism. These claims tend to focus on the fallibility of knowledge, the need for a pluralistic view, and the theoretical burden of observations. Regardless of the legitimacy of these concerns, there is the risk, when not moderate, to fall into the opposite relativistic extreme. Based on a narrative review of the literature, we aim to reflectively discuss the theoretical foundations that can serve as a basis for a realist position supporting pluralistic ontological classifications. The goal is to show that, against rather conventional solutions, objective scientific-based approaches to natural classifications are presented to be viable, allowing a proper distinction between ontological and taxonomic questions. Supported by critical scientific realism, we consider that such an approach is suitable for the development of ontological Knowledge Organisation Systems (KOSs). We believe that ontological perspectivism can provide the necessary adaptation to the different granularities of reality.
面向本体知识组织系统的适度现实主义基础:分类的自然性问题
几位作者强调,由于过时的本质主义支持的教条主义和一元论本体论的影响,分类理论需要改变。这些主张往往侧重于知识的易错性、多元化观点的必要性以及观察的理论负担。不管这些担忧的合法性如何,如果不是适度的,就有可能陷入相反的相对论极端。基于对文献的叙述性回顾,我们旨在反思性地讨论可以作为支持多元本体论分类的现实主义立场的基础的理论基础。其目的是表明,与相当传统的解决方案相比,基于科学的客观自然分类方法是可行的,从而能够正确区分本体论和分类学问题。在批判科学现实主义的支持下,我们认为这种方法适合本体论知识组织系统的发展。我们相信本体论的透视主义能够提供对现实的不同粒度的必要适应。
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来源期刊
Journal of Information Science
Journal of Information Science 工程技术-计算机:信息系统
CiteScore
6.80
自引率
8.30%
发文量
121
审稿时长
4 months
期刊介绍: The Journal of Information Science is a peer-reviewed international journal of high repute covering topics of interest to all those researching and working in the sciences of information and knowledge management. The Editors welcome material on any aspect of information science theory, policy, application or practice that will advance thinking in the field.
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