
The goal of achieving a net-zero emission European economy by 2050 demands a shift from linear, fossil-based systems to circular, bio-based systems. This transition is vital for meeting the United Nations Sustainable Development Goals and reconciling environmental protection with sustainable growth. However, the complexity of the transition relies on societal transformations, cutting-edge technologies, and multi-actor processes, requiring a new societal and economic framework and policy priorities that align with the European Green Deal. In this context, monitoring systems, modelling techniques and data are key tools to support policy making and facilitate a better understanding of the complexity, trade-offs, and potential pathways to achieve a sustainable transition to a circular bioeconomy. This dataset presents the review of existing knowledge for monitoring and evaluating the transition to circular bio-based systems. More than 130 research items, including scientific articles and reports, were consulted to identify major gaps across indicators and approaches generally used to monitor and evaluate the bioeconomy across the three major policy-level analyses: (i) micro-level (products/processes/companies), (ii) meso-level (city/regions) and (iii) macro-level (World, Europe or countries). This dataset is suplementary to the publication of SUSTRACK project: D2.1 - Review of Approaches and Identification of Research Gaps
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
