Knowledge Organization System for the knowledge domain of geosciences: in search of categories for Mineral Research

• Autor(a) principal: Caetano, Gabriela Silva
• Data de Publicação: 2021
• Outros Autores: Almeida, Carlos Henrique Marcondes de
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Múltiplos Olhares em Ciência da Informação
• Texto Completo: https://periodicos.ufmg.br/index.php/moci/article/view/37070
• topic: Sistema de Organização do Conhecimento; Categorias; Pesquisa Mineral; Knowledge Organization System; Categories; Mineral Research

This work seeks subsidies for the Knowledge Organization in the field of Mineral Research. Natural language has phenomena such as synonymy, homonymy or, in the Brazilian context, regionalism that generate semantic ambiguity. Searching in an Information Retrieval System requires the use of language, this linguistic practice can be used in many ways and in various contexts, therefore, Knowledge Organization Systems - SOCs acts as auxiliaries in this natural language search process for Controlled language conversion. The basis of any representation of a domain is a system of categories. What categories can be identified in the scientific literature and Geoscience SOCs to represent the area of Mineral Research? The purpose of this article is to identify the patterns and state of the art of SOCs for the field of Geosciences and gather variations in the representation of the mineral exploration area of these SOCs. The methodology used was bibliographic research and content analysis of the retrieved documents. The results showed that a large part of the production was carried out in 2018, the countries of the authors were the two largest economic powers in the world, USA and China. Related to the analysis of conceptual models, it is believed that they are not sufficient for the proposed objective, as a hypothesis of this, the issue of confidentiality of geoscientific information is raised. It is believed that actions to standardize knowledge of mineral research will help to improve the economic productivity of the area, foster research and generate new knowledge.