The Technology Policy Assessment Center (TPAC) is a center for data analytics for science and innovation in the School of Public Policy at Georgia Institute of Technology. TPAC produces high-quality, high-impact research, advanced education and training, and funded research opportunities. TPAC applies data analytic techniques to assess the science and technology landscape as follows:
- Profiling emerging technological areas such as nanotechnology, synthetic biology, autonomous systems, big data, energy and environmental technologies, cybersecurity, and cognitive science and learning. Such emerging domains are of great importance for Georgia Tech and the US and offer opportunities for TPAC to engage in emerging technology assessment in conjunction with colleagues in engineering, innovation, and policy.
- Establishing indicators to reflect science and technology positioning in areas such as technological emergence, interdisciplinarity, diffusion, and high technology (building on TPAC’s prior national “High Tech Indicators”).
- Creating visual mapping of scientific areas and patented technologies using intellectual property analytics to enrich R&D profiling and science, technology and innovation (ST&I) indicators.
- Developing new interdisciplinary evidence-based approaches to technology assessment, including in such areas as responsible research and innovation and constructive life-cycle assessment.
- Nurturing the state of the art in responsible application of metrics in university research evaluation.
- Developing techniques to track knowledge flow from funding through research through to professional practice and societal impact.
- Providing strategic intelligence for initiatives in science, technology, and innovation-driven economic development.
This center addresses these areas by extending and developing a complementary toolkit of methods and data sources:
- Management of large scale datasets for analysis.
- Systematic search strategies for defining technological domains using multi-stage Boolean, citation-based, and learning strategies.
- Application of data analytics to scientific, business and social science journal articles, proceedings, and other types of published scientific papers; US and global patent datasets (e.g., PatStat); and research funding sources.
- Analysis of unstructured Internet data such as company websites and social media, e.g., twitter.
- Linking heterogeneous datasets such as research funding, employment, output and policy use.
- Visualization of results using network analysis, and geographic, disciplinary, and patent mapping
Center faculty are already lead users of VantagePoint data mining software (commercial revenues of which provide some $25,000 licensing royalties to Georgia Tech annually). In September of 2017, TPAC transitioned to a data analytics and technology forecasting orientation in line with its original 1981 center mission.