Ontology Summit 2021 Communiqué: Ontology generation and harmonization

Appl. Ontology Pub Date : 2022-03-09 DOI:10.3233/ao-220266
K. Baclawski, Mike Bennett, G. Berg-Cross, Leia Dickerson, Todd Schneider, S. Seppälä, Ravi Sharma, R. Sriram, A. Westerinen
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引用次数: 1

Abstract

Advances in machine learning and the development of very large knowledge graphs have accompanied a proliferation of ontologies of many types and for many purposes. These ontologies are commonly developed independently, and as a result, it can be difficult to communicate about and between them. To address this difficulty of communication, ontologies and the communities they serve must agree on how their respective terminologies and formalizations relate to each other. The process of coming into accord and agreement is called “harmonization.” The Ontology Summit 2021 examined the overall landscape of ontologies, the many kinds of ontology generation and harmonization, as well as the sustainability of ontologies. The Communiqué synthesizes and summarizes the findings of the summit as well as earlier summits on related issues. One of the major impediments to harmonization is the relatively poor quality of natural language definitions in many ontologies. The summit surveyed the state of the art in natural language definition development, based on lexicographic principles, as well as examples of ongoing projects that are explicitly dealing with harmonization and sustainability.
2021本体峰会公报:本体生成和协调
机器学习的进步和非常大的知识图谱的发展伴随着许多类型和许多目的的本体的激增。这些本体通常是独立开发的,因此很难在它们之间进行通信。为了解决这种沟通困难,本体和它们所服务的社区必须就各自的术语和形式化如何相互关联达成一致。达成一致和一致的过程被称为“和谐”。2021年本体峰会探讨了本体的整体格局、多种本体生成和协调以及本体的可持续性。《公报》综合和总结了本次峰会以及此前几次峰会就相关问题达成的成果。协调的主要障碍之一是许多本体中自然语言定义的质量相对较差。峰会根据词典编纂原则调查了自然语言定义发展的最新状况,以及明确处理协调和可持续性的正在进行的项目的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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