Circular Economy Research Benchmarking

Leveraging comprehensive scientific databases such as OpenAlex and SciSciNet, the project will filter the global knowledge base in natural sciences and engineering to identify research that effectively uses AI for circular economy purposes. The results will be visualized as an interactive map, which will allow HEIs and individual researchers to easily locate relevant best practices based on their specific research focus and proximity.

Curation of best practices in accessible and engaging formats. To ensure that researchers can fully benefit from the identified best practices, these will be made available in multiple formats, including audio/video summaries, blog posts, and newsletters. This multimodal approach aims to cater to diverse learning preferences and to enhance the accessibility of the information.

Centers on the validation of the recommended formats for sharing best practices. By interviewing individual researchers and research groups, the project will assess which formats are most effective for different audiences. This feedback will be crucial for refining how best practices are communicated and ensuring that they are presented in a way that maximizes their utility.

Aims to establish a community of researchers engaged in exchanging knowledge about current AI applications in circular economy research. This community will serve as a platform for regular interactions, enabling researchers to discuss how AI could be further leveraged in their ongoing projects. By fostering these discussions, the project aims to create a collaborative environment that encourages continuous learning and innovation in circular economy research using AI.