Modelagem de redes de cooperação científica na educação profissional e tecnológica.

Abstract

Scientific cooperation is an important issue to expansion of operational capacity and optimal use of resources by improving the analytical capacity of research projects and the recognition of researchers in their area. Social Network Analysis - ARS is a strategy that has been increasingly adopted both in the math sciences and in the human sciences for scientific cooperation studies. The ARS approach has a very important feature, which is the change in the focus of individuals to the relationship between them, shifting the object of analysis from the element to the relationship structure to which they belong with source of verifying the relationships the bibliographic production to building strategies and analyzing social behavior based on co-authorship in scientific documents. The increase in computational processing capacity allows the storage of large bibliographic databases, indicating the need for proposals for the analysis and publication of statistical indicators and network relationships. In this thesis is presented a methodology developed for discovery, assessment and representation of knowledge in the field of vocational and technological education. The research methodology was based on techniques, concepts and fundamentals of Scientific Modeling, Social Network Analysis, knowledge-based systems, scientometrics and bibliometrics for the construction of a process of extraction, treatment, capture, analysis and publication (ETCAP) of scientific cooperation, using as an empirical source the data extracted from curricula registered in the Lattes Platform. The captured data were treated and used in the construction of a new relational database, with information temporally organized since the formation of the Federal Institutes of Education in 2008. A conceptual/operational framework is presented as strategy for the execution of discovery of knowledge from the scientific modeling of scientific cooperation networks. The framework was validated from a case study, supporting the empirical restrictions of the research, proving to be effective for extracting, processing, loading and analyzing data, allowing access to information, characteristics, indicators and metrics of the modeled cooperation network. The success in solving the research problem is materialized in the framework, through a computational solution with access and contextualized hipermodal visualization, in which interactivity created makes it possible to know the dynamics and evolution of the social network, the main agents producing knowledge, giving new meaning to the experience of consulting information, democratizing access to knowledge production. At end we provide a new free of charge set of tools and procedures to discover and represent knowledge about the cooperation network on the domain of professional and technological education, analyzing and publishing the network of scientific cooperation