Modelagem da informação tecnológica baseada em patentes para a inovação

Abstract

Innovation has been researched and practiced in multiple ways in recent years and, despite certain nuances, this concept has evolved beyond the simple idea of introducing something new into the economic context to reflect the complexity involved throughout the entire innovation process. The literature also indicates that innovation processes are affected by different factors and depend on the availability of technological information. The primary source of technological information for innovation comes from patent documents; however, there are two major challenges to consider. The first is that the information describing the inventions behind patents may be difficult for different audiences to understand and does not represent the full complexity of technological information which, by definition, is multidimensional. The second is that information sources that may serve as inputs for innovation are usually disconnected and involve considerable volumes of data, creating obstacles for analytical strategies that are not based on computational approaches. Furthermore, certain patent and inventive databases are paid services, hindering access for communities characterized by scarce resources. Based on this context, the main objective of this research was to model technological information aimed at innovation in such a way that, within the resulting dataset, four informational perspectives coexist inseparably: inventive, encyclopedic, scientific, and industrial. An informational architecture is proposed, guided by a reference model and constituted through the integration of databases, classification schemes, and an inventive methodology. Multiple research methods were adopted and combined, with a predominantly exploratory objective and both quantitative and qualitative approaches. Due to the volume of data, computational techniques grounded in a set of algorithms were applied. For the construction of the informational model, the following components were used: the TRIZ methodology (the Russian acronym for Theory of Inventive Problem Solving) and TRIZ effects databases; the International Patent Classification; Wikipedia and Wikidata; the Lattes Curriculum; the National Classification of Economic Activities; and the Espacenet database. As a result, the resulting dataset provides millions of potential pathways connecting researchers, new technologies, and industrial sectors in Brazil. The use cases discussed provide evidence that, by integrating fragmented data from distinct sources into a single whole, according to the proposed methodological framework, it is possible to arrive at certain inventive insights that could not easily be mapped through the simple combination of the individual parts. Specifically, regarding the scientific perspective, a certified and expanded patent database derived from the Lattes Curriculum was achieved, overcoming the unitary patent-based perspective in order to attain a broad view of inventions necessary for integration into the model. From the STS (Science, Technology, and Society) perspective, this research is part of a context shaped by social demands and market dynamics under a constructivist approach, representing only one part of a larger and unfinished system and, therefore, subject to continuous evolution. Thus, it is considered that the results obtained and their subsequent developments may contribute to strengthening the connections between research, technology, and industry in Brazil.