A multi-layer framework for semantic modeling. Issue 2 (17th December 2019)

• Record Type: Journal Article
• Authors: Silva, Sergio Evangelista; Reis, Luciana Paula; Fernandes, June Marques; Pereira, Alana Deusilan Sester
• Is Part Of: Journal of documentation. Volume 76:Issue 2(2020)
• Page Start: 502
• Page End: 530
• Publication Date: 2019-12-17
• Subjects: Semantics -- Semiotics -- Information management -- Knowledge management -- Conceptual framework -- Document management -- Knowledge organization systems; Documentation -- Periodicals; Library science -- Periodicals; 025
• DOI: 10.1108/JD-03-2019-0042
• Languages: English
• ISSNs: 0022-0418

Abstract

Abstract : Purpose: The purpose of this paper is to introduce a multi-level framework for semantic modeling (MFSM) based on four signification levels: objects, classes of entities, instances and domains. In addition, four fundamental propositions of the signification process underpin these levels, namely, classification, decomposition, instantiation and contextualization. Design/methodology/approach: The deductive approach guided the design of this modeling framework. The authors empirically validated the MFSM in two ways. First, the authors identified the signification processes used in articles that deal with semantic modeling. The authors then applied the MFSM to model the semantic context of the literature about lean manufacturing, a field of management science. Findings: The MFSM presents a highly consistent approach about the signification process, integrates the semantic modeling literature in a new and comprehensive view; and permits the modeling of any semantic context, thus facilitating the development of knowledge organization systems based on semantic search. Research limitations/implications: The use of MFSM is manual and, thus, requires a considerable effort of the team that decides to model a semantic context. In this paper, the modeling was generated by specialists, and in the future should be applicated to lay users. Practical implications: The MFSM opens up avenues to a new form of classification of documents, as well as for the development of tools based on the semantic search, and to investigate how users do their searches. Social implications: The MFSM can be used to model archives semantically in public or private settings. In future, it can be incorporated to search engines for more efficient searches of users. Originality/value: The MFSM provides a new and comprehensive approach about the elementary levels and activities in the process of signification. In addition, this new framework presents a new form to model semantically any context classifying its objects.