Technology Mining for Digital Innovation

"The course has two primary objectives. Firstly, to understand cutting-edge Computer Science techniques for data management, analysis, and Intellectual Property (IP) protection within the field of digital innovation, collectively known as ""technology mining."" Secondly, to learn how to design and manage the progression from methodological research in Computer Science to actual, fully engineered digital innovation products.
The course combines methodological foundations with empirical skills to help PhD students navigate future challenges in applied research and industrial innovation. These include identifying and manipulating appropriate data sources, formulating development strategies in the innovation sector, and linking technical research with intellectual property rights and business dynamics. 1. Technological Innovation and Data Mining: Background and methodological approaches to tech mining.
2. Technology Readiness Levels (TRL): Framework and contextualization within digital innovation research (academic, applied, and industrial). Strategies and approaches for increasing TRL—moving from basic Computer Science research to fully engineered digital products.
3. Understanding IP Rights, Identifying and Exploiting IP Data Sources: Scientific publications, patents, trademarks, copyrights, and other IP protection solutions; major patent databases (e.g., OrbisIP, Patstat) and other IP sources; how to select and effectively exploit the correct sources.
4. Patent Quality and Valorization: Formal patent data analysis methods, quality indicators, and valuation metrics.
5. Case Study: A corporate case study presented by an industrial expert specialized in tech mining and intellectual property management. Additionally, the course will feature a success case study in digital innovation presented by an industrial expert, demonstrating the strategic use of tech mining approaches to support corporate innovation and competitiveness "