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Science and Technology Ontology: A Taxonomy of Emerging Topics

2023-05-06 14:04:24
Mahender Kumar, Ruby Rani, Mirko Botarelli, Gregory Epiophaniou, Carsten Maple

Abstract

Ontologies play a critical role in Semantic Web technologies by providing a structured and standardized way to represent knowledge and enabling machines to understand the meaning of data. Several taxonomies and ontologies have been generated, but individuals target one domain, and only some of those have been found expensive in time and manual effort. Also, they need more coverage of unconventional topics representing a more holistic and comprehensive view of the knowledge landscape and interdisciplinary collaborations. Thus, there needs to be an ontology covering Science and Technology and facilitate multidisciplinary research by connecting topics from different fields and domains that may be related or have commonalities. To address these issues, we present an automatic Science and Technology Ontology (S&TO) that covers unconventional topics in different science and technology domains. The proposed S&TO can promote the discovery of new research areas and collaborations across disciplines. The ontology is constructed by applying BERTopic to a dataset of 393,991 scientific articles collected from Semantic Scholar from October 2021 to August 2022, covering four fields of science. Currently, S&TO includes 5,153 topics and 13,155 semantic relations. S&TO model can be updated by running BERTopic on more recent datasets

Abstract (translated)

本体论在语义网技术中发挥了关键作用,通过提供结构化和标准化的方式来代表知识,使机器能够理解数据的含义。已经产生了多个分类和本体论,但个人主要关注一个领域,只有其中一些本体论的时间和手动努力成本很高。此外,需要更多涵盖非常规的主题,代表了知识领域和跨学科合作更全面和整体的视角。因此,需要建立一个涵盖科学和技术各领域的本体论,以促进新研究领域的发现和跨学科合作。为了解决这些问题,我们提出了一个自动的科学和技术本体论(S&TO),涵盖了不同科学和技术领域的非常规的主题。 proposed S&TO can promote the discovery of new research areas and collaborations across disciplines. The ontology is constructed by applying BERTopic to a dataset of 393,991 scientific articles collected from Semantic Scholar from October 2021 to August 2022, covering four fields of science. Currently, S&TO includes 5,153 topics and 13,155 semantic relations. S&TO model can be updated by running BERTopic on more recent datasets

URL

https://arxiv.org/abs/2305.04055

PDF

https://arxiv.org/pdf/2305.04055.pdf


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