Inteligência Artificial e Ciência de Dados em CRIS institucional: modelo conceitual

Abstract

The increasing availability of data and information related to research ecology, in multiple information systems, culminates in increasing complexity in the research management activity. In response to this complexity, Current Research Information System (CRIS) are developed, which aim to manage contextual metadata of research activities related to a particular institution, whether research or development. In this study, an Institutional CRIS Conceptual Model is revisited, aiming at improving the process, using Artificial Intelligence and Data Science. As a methodological procedure, it uses the bibliographic review for the theoretical-conceptual basis to contextualize Artificial Intelligence and Data Science, incorporated into the study. From that, the revisited model was created, inserting a data layer, which deals with the Data Science aspects, as well as Artificial Intelligence techniques and methods in all CRIS processes, in particular, it was inserted Natural Language Processing, Computer Vision, Text Mining and Machine Learning. It is concluded, therefore, that the adaptation of the model presented shows itself as maturation in the very understanding that one has of CRIS, with the insertion of elements that make this model more up-to-date. Thus, the studies and creation of CRIS models and applications allow evolution in institutional management.