Universities have assumed an increasingly important role in transferring technology to society with a strong economic impact. The companies originated from the academic environment, called academic spin-offs, have fostered the appearance of new projects based on emerging technologies and knowledge, created by young students and researchers who seek to launch their own business and generate new jobs in society. However, the number of existing studies on academic spin-offs is limited and restricted to the specific national realities, and the results of these studies are typically incorporated only in scientific manuscripts. In this sense, this study proposes a web platform that allows the analysis of academic spin-offs according to multiple dimensions, such as firm, institutions, individual, localization, science parks, financial data and corporate actions. The application is built exclusively in open source technologies and allows data to be explored in real-time and interactively. The results obtained allow us to evaluate the behavior of the application regarding fundamental elements in the success of the adoption of a Web application, such as usability, security, interoperability and portability.
The creation of university spin-offs plays a fundamental role in the technology transfer process between universities and the business field. Universities have developed for themselves internal processes within their technology transfer offices in order to collect this information. However, this data is only available locally and often outdated. Furthermore, the number of frameworks that allow the study and simultaneously access to this data in an integrated way is still small on a global scale, and in Portugal, there isn't a repository which contains this information. This study proposes the establishment of a framework for longitudinal analysis that could identify and characterize the evolution and performance of Portuguese university spin-offs. The repository is built exclusively in open source technologies and offers the potential to characterize and analyze the evolution and performance of university spin-offs in different perspectives, such as individual factors; organizational factors; institutional factors; and scientific, educational, and commercial outputs.
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