PNZ - SIBI - Sistema Integrado de Bibliotecas da Univasf

URI Permanente desta comunidadehttps://repositorio.univasf.edu.br/handle/123456789/1533

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    Estratégias metodológicas para a geração de indicadores científicos na Universidade Federal do Vale Do São Francisco
    (2019-04-22) Silva, Ana Paula Lopes da; Cunha, Francisco José Aragão Pedroza; Sobral, Natanael Vitor
    The objective of this paper is to develop methodological strategies for the generation of scientific indicators in Federal University of the São Francisco Valley. The motivations for development of the project are linked to the desire to save resources in the construction of indicators, as well as to promote the scientometrics studies in the institution as a way to improve the instruments for evaluating scientific activities in the university. It was based on a survey of the university's stricto sensu postgraduate programs, which together with the teachers working in these programs, formed the research universe. The Lattes Platform Database of the National Council for Scientific and Technological Development was defined as the initial source for the construction of strategy and congregation of indicators, using the method of data extraction of the tool ScriptLattes and the processing and visualization media ruled in statistical tabulation, social network analysis and tag clouds. In general, we considered the methodological strategy, built from bibliometric and scientometrics tools, feasible to apply to the universe investigated, making it possible to establish several scientific indicators of the postgraduate programs of the selected institution. The objective of saving resources in the strategy was a priority item, and for this, free and low-cost tools were prioritized. As a main limitation of the strategies formulated, it is necessary to carry out some activities of a manual nature, which makes the methodological resources undertaken here more suitable for smaller groups. It is pointed out as differential of the strategies, the flexibility in the treatment of the data, allowing the personalization of the indicators and the replication of the models presented in institutions of similar nature.