Abstract
Many governments worldwide have proposed transitioning from a fossil-based economy to a bioeconomy to address climate change, resource depletion, and other environmental concerns. The bioeconomy utilizes renewable biological resources across all sectors and is strongly founded on scientific advances and technological progress. Given that the bioeconomy spans multiple sectors, industries, and technological fields, tracking it is challenging, and both policymakers and researchers lack a comprehensive understanding of the bioeconomy transition's progress. We aim to solve this problem by providing a dataset on patents, a commonly used indicator to study the development of novel knowledge and technological change, that identifies bioeconomy-related inventions. We leverage the advanced semantic understanding embedded in pre-trained transformer models to identify bioeconomy-related patents based on patent abstracts, and we use a topic modelling approach to identify several coherent technological fields within the corpus of bioeconomy patents. The dataset can be linked to other patent databases and therefore provides rich opportunities to study the technological knowledge base of the bioeconomy.