As one can see on the homepage of Impacter we support in delivering better grant proposals by analyzing your proposal automatically within our platform. In matter of minutes you as a user receive your feedback, focused on your impact chapter, story, policy fit and uniqueness. Over the last couple of years we slowly evolved from just a keyword recognition machine towards a platform that includes more sophisticated text analysis and AI to help you delivering better grant proposals. One of the technologies we focus on is matchmaking algorithms, where we compare one input text (abstract, grant proposals, etc…) large corpora of documents. For our uniqueness check, we compare your text with 300.000 project descriptions (from databases like Cordis, FRIS and more) that received funds in previous years. Together with our partner ResearchConnect we compare your input text with their database with tens of thousands funding opportunities. The next step in matching your text with a large corpus, is the corpus of OpenRaadsinformatie, a Dutch database of policy documents from Dutch municipalities that is openly available.
Currently we are testing this concept with some of our Dutch customers. The basic idea is that a lot of (SSH) research has a direct link with municipality policies but often both the researchers and the municipality are unaware of this overlap. At the same time, we know that both are interested in collaborating, as is for instance described in the (Dutch) report of Rathenau institute ‘Town in search of gown’. But it can be quite difficult to find that one piece of the puzzle in the endless stream of policy documents and academic publications. By proactively sharing relevant policy documents with academics, collaborations can be created when preparing a grant application. Or to reach out to relevant municipalities for contract research in their area of interest. It all starts with the knowledge of the topics municipalities and researchers are interested in.
And this is only a starting point in matching policy documents, because another way you can view this development is by checking the relation to policy documents in calltopic documents. In Europe, most of the pillar 2 calltopics have their foundation in policy documents. We would expect that good proposal will have some sort of content overlap with the policy documents that were at the basis of the funding opportunity.
Since we are only at the start of developing these policy match making services we are curious to learn from you, as an academic, as a grant or policy officer in universities, what policies you feel are relevant in context to the research in your faculty/department.
Feel free to reach out to us with suggestions or maybe even repositories where policy documents are published! We are eager to further bridging the gap between science and policy making!