Federal University of Minas Gerais
Fundação Getulio Vargas, Brazil
Österreichische Akademie der Wissenschaften
______________________________________________________________________________________________________________________________________
Plenary Talk: Data Science, Machine Learning, Knowledge Organization and Digital Humanities: some reflections on the fields of knowledge
Abstract: Data Science has been described as an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured. Just like Information Science revolutionized Knowledge Organization in the 1960s, this field has arisen to provide theoretical, methodological and practical tools to study and deal with information needs; and both are very dependent on technological constructs. The aim of this talk is to discuss the points of convergence of the two fields and the challenges and opportunities that Data Driven Science can bring to the Informational Tasks within the Digital Humanities.
Brief Biography: After graduating and completing his masters on Engineering, developed his doctorate and post doctorate in Information Science and Computer Science, dealing with the topics of Information Retrieval, Natural Language Processing and Knowledge Organization Systems, as thesaurus and ontologies. Has been working in the past ten years with Scientific Programming, Data Science and Machine Learning/Deep Learning, as a professor and researcher in the Applied Mathematics School at Fundação Getulio Vargas, Rio de Janeiro, and in School of Information Science, in the Federal University of Minas Gerais. Has been developing projects in the domains of Political Science, Law, Economics, Public Health and Education; integrating information resources in analytical pipelines.
Works nowadays as a researcher in the Austrian Centre for Digital Humanities, in the Austrian Academy of Sciences, exploring the possibilities of Natural Language Processing, Automatic Classification, Text Mining and Machine Learning aiding Digital Humanities and Citizen Science projects.
