Identitas: Semantics-free and human-readable identifiers

Author:

Alshammry Nizal12,Lord Phillip1

Affiliation:

1. School of Computing, Newcastle University NE4 5TG, United Kingdom. E-mails: Alshammry-nazal@hotmail.com, phillip.lord@newcastle.ac.uk

2. School of Computing, Northern Borders University, Saudi Arabia

Abstract

In this article, we present a new approach to identifiers, one that aims to improve the management of ontologies. This approach overcomes some of the main flaws associated with the existing approaches, providing alternative solutions. Ontology identifiers are the key for each entity defined in an ontology, and enable a unique and persistent reference to each term. The form of identifiers has been the subject of discussion, which has resulted in a number of different schemes. It is often recommended that identifiers for ontology terms should be semantics-free or meaningless. One practice is to use numeric identifiers, starting at one and working upwards. However, this has a number of disadvantages: it does not allow for concurrent development, is relatively hard to read, and it is difficult to detect errors when an identifier is misused. From the perspective of development, solving these issues could facilitate the process of building and managing ontologies. Here, we suggest random identifiers to enable concurrent development, while exploiting the proquint library to overcome the problems of memorability and pronounceability. Finally, a checksum is implemented to prevent the occurrence of errors while accessing relatively similar identifiers. Availability and Implementation: The software is available from https://github.com/Nizal-Shammry/identitas-j. It has been integrated into environments for ontology development such as Tawny-OWL and Protégé.

Publisher

IOS Press

Subject

Linguistics and Language,Language and Linguistics,General Computer Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3