The Future of Big Data Patent Analytics
Aistemos is supporting ‘The Future of Big Data Patent Analytics’ workshop on Friday the 3rd of March 2017 at the University of Cambridge.
The Innovation and Intellectual Property group, within the Centre of Technology Management, at the Institute for Manufacturing (IfM), Department of Engineering, University of Cambridge, seeks expressions of interest for attendance at a one-day workshop on “The Future of Patent Analytics: A foresight study of breakthrough enabling technologies”.
The aim of the workshop is to identify future technologies, with the potential to deliver breakthroughs for substantially better analyzing and visualizing patent data to enable previously untapped use cases, through the engagement of academic and industry.
Big Data Patent Analytics is an area which stretches across several EPSRC themes, such as the ‘productive nation’ theme with the introduction of the next generation of innovative and disruptive technologies, digital transformation, and the ‘connected nation’ theme for enabling a competitive and data-driven economy.
The project objectives will
- Help improve patent analytics for more effective exploitation of the worldwide largest repository of technological information to enable new use cases.
- Develop a public technology roadmap to facilitate collaboration and coordinated action of actors in the patent analytics community to further develop the capabilities for analyzing patent data.
- Reflect on the technology roadmap and the development of future technologies to solve outstanding and long term problems.
- Bring together relevant stakeholders in a research setting to enable new collaborations, thereby enhance patent analytics progress. The workshop will take place on the 3rd of March, at the Institute for Manufacturing (IfM), University of Cambridge. Expressions of interest to attend are welcome from academia and industry. As places are limited, the EoIs received will be reviewed by an internal IfM selection process to ensure a diverse representation of attendees across career stages and organizations. Selection will primarily be based on justification of attendance, in relation to technology expertise, although the number of participants from a given organization may have to be restricted in the event of multiple applications.