Innovative AI based tool for HEIs knowledge monitoring and visualization
About this good practice
Effective higher education and research institutions cooperation with business is based on impact assessment and clear understanding how scientific knowledge is used in various business sectors, and how effective it is. Currently it is not clear how and what king of knowledge generated by different research and higher education institutions is used, which sectors are most receptive to this knowledge, for whom the greatest added value is generated, and so on.
In this context, it is essential to have tools to collect, sort and use open data to evaluate the use of scientific knowledge. This Artificial intelligence- based tool for visualization and monitoring of knowledge produced by HEIs provides a possibility by using different filters and selecting the NACE code, get a variety of graphical data on the efficiency of higher education knowledge usage, such as R&D investment and its links to the number of publications or higher education absolvents, etc.
The main beneficiaries of this good practice are innovation policy makers at national level such as the Ministry of Education, Science and Sport and Ministry of Economy and Innovation, but this tool of impact assessment is also relevant for other institutions at various levels involved in promoting science and business cooperation.
The total value of this project is 55.000 EUR. The project was implemented in two phases: in the 1st phase, we allocated € 19,800 for the project tender. The 2nd phase was 35.700 EUR for the winner of the 1st stage.
A team of 5 LIC employees was assembled to run this project .
Evidence of success
This AI-based tool has following major advantages:
- systematic monitoring process of HEIs and business cooperation;
- enables the development of evidence-based R&D&I policies;
- provides visualized data in various aspects;
- results could be used by various beneficiaries.
- results could be visible wherever is needed.
Potential for learning or transfer
This good practice is easy to transfer as it requires only AI-based solution development and maintenance. The solution is based on various open data sources available in the region. Any organization interested in good practice transfer could easily modify resources for open data, filters of ways of visualisation adopted to their needs.