Analysis of Information Features for Identification of Digital Intellectual Property Metadata Elements

Main Article Content

Watsaporn Arayaphan
Pornanant Iamkhajornchai

Abstract

This research aims to analyze the content of physical and contextual characteristics of digital intellectual property in Thailand. The sample consists of copyrighted digital intellectual property registered and recorded in the copyright information verification system of the Department of Intellectual Property, Ministry of Commerce, from 2017 to 2024, totaling 65,944 items. This study employs qualitative research methodology, focusing on information attribute analysis. Research results of the digital intellectual property analysis can identify 23 metadata elements of intellectual property in three dimensions. The first dimention is content that consists of four elements: type of copyrighted works, details of creation or inspiration, title of the work, and language of the work. The second one is a physical aspect that consists of seven elements: copyright owner, agent, creator or pseudonym, copyright ownership, contact address, the informant on the use of copyright infringement exceptions for the benefit of disabled persons who cannot access copyrighted works and the nature of creative works. The third one is a contextual aspect that
consists of twelve elements: filing date, receipt date, application number, notification number, data registration, advertisement of copyrighted work, place of creation of the work, year of creation, information on the use of copyright infringement exceptions for the benefit of disabled persons, types of media exempted from copyright infringement for the benefit of disabled persons, list of requests for revocation of copyright information and supporting documents for copyright notification. A metadata framework has been developed by organizations and entities involved in intellectual property to capture knowledge and the management of intellectual property in both traditional and digital forms, enabling users to access knowledge from intellectual property effectively.

Article Details

How to Cite
Arayaphan, W., & Iamkhajornchai, P. (2025). Analysis of Information Features for Identification of Digital Intellectual Property Metadata Elements. Journal of Information and Learning [JIL], 36(1), e277582. retrieved from https://so04.tci-thaijo.org/index.php/jil/article/view/277582
Section
Research Article

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