Qualitative analysis of digital content curation models: Possibilities for use in CAQDAS

• Autor(a) principal: Katia Alexandra de Godoi e Silva
• Data de Publicação: 2022
• Outros Autores: António Pedro Costa, Natália Parron Teixeira
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.36367/ntqr.12.2022.e630
• topic: webQDA; Digital curation; Qualitative research; Curation framework; webQDA; Curadoria digital; Pesquisa qualitativa; Modelos de curadoria

 In recent years there has been a growing development and interest, on the part of researchers, in the use of software in scientific investigations, both in the increase of literature review strategies and in the organization, collection, analysis and triangulation of data. These aspects revealed possibilities for discussions related to the curation of digital content in Computer-assisted Qualitative Data Analysis Software (CAQDAS), as the choice and organization of qualitative data from scientific research is affected by this complexity of information, involving ethical dilemmas that permeate investigations. Thus, the objective of the present study is to contribute to the reflection and analysis of digital content curation models that can be used in CAQDAS. To achieve this objective, a qualitative descriptive methodology was used, made possible by a systematic literature review of scientific works on the subject of digital content curation, based on searches in two academic databases (Scientific Electronic Library On-line - SciELO and Scopus) and in two gray literature bases (Bank of Theses and Dissertations of the Coordination for the Improvement of Higher Education Personnel (BDT/Capes) and Google Scholar). As a result, it was found that there are few models of curation of digital content, with similar aspects and used in different modalities of education (higher, secondary and elementary), and that there are authors interested in reflecting and using such models. It was also found that digital content curation models can be re-signified and explored in the context of organizing qualitative data in CAQDAS.