Letramento informacional para reúso de dados nas ciências sociais em ambientes virtuais de pesquisa: proposta de requisitos e competências

Abstract

The scientific research environment has been impacted by the increase availability of research data in open access, mainly due to the requirement of data deposit by government’s laws, funding agencies’ policies and scientific publication’s mandates. In this scenario, the researchers face difficulties in managing their own data as well as third parties’; especially in data reuse related matters. Each field of Science has its own particularities of data types, volumes and forms of data production, which is inherent to each scientific particularities. However, the relation of availability versus data management is more complex in the Social Sciences, whose data are heterogeneous and variable. Therefore, this work seeks to evidence, from bibliographical sources, the lack of researcher’s information data literacy, which exposes the untapped potential of data reuse already available. From the Actor-Network Theory (ANT) point of view, research data is itself a relevant actor in the process of scholarly communication, since they alter the way in which researchers can produce analyzes, inferences and comparisons, from data reuse available in virtual research environments, resulting in new knowledge. From an Actor-Network Theory (TAR) perspective, the research data are themselves a relevant actor in the process of scientific communication, since they alter the way researchers can produce analyzes, inferences and comparisons by reusing available data in virtual research environments, resulting in new knowledge. This work proposes, therefore, from an ANT perspective, the requirements of a virtual environment for informational data literacy, with the minimals necessary skills for data reuse in Social Sciences. The research is applied, exploratory-descriptive combined, based on a bibliographical background, and uses the NVivo analysis tool to support the content analysis techniques and material exploration into three research instances. For the first instance, it compares (1) the conceptual frameworks of information data literacy, identifying the common requirements proposed for data reuse within those frameworks. For the second instance, it reuses (2) secondary datasets about researchers' behavior in sharing and reusing data in their own research, highlighting literacy gaps as barriers to reuse. For the third instance, it identifies (3) in the Virtual Learning Environments of selected projects, what learning resources teache data literacy for reuse purposes. From the result of the triangulation analysis of these instances (frameworks, datasets and learning resources), this work presents a model of 16 requirements and 37 competences for research data reuse in the Social Sciences. Key requirements include access, licensing and use, and core competencies are access rules, license types and how to use available datasets. The validity test of the proposed model is performed by adherence checking with the best available data management recommendation practices by the World Wide Web Consortium (W3C).