Supplemental data from: A conceptual classification scheme of invasion science

In the era of Big Data and global biodiversity decline, there is a
pressing need to transform data and information into findable and
actionable knowledge. We propose a conceptual classification scheme for
invasion science that goes beyond hypothesis networks and allows to
organize publications and datasets, guide research directions, and
identify knowledge gaps. Combining expert knowledge with literature
analysis, we identified five major research themes in this field: (1)
introduction pathways, (2) invasion success and invasibility, (3) impacts
of invasion, (4) managing biological invasions and (5) meta-invasion
science. We divided these themes into ten broader research questions and
linked them to 39 major hypotheses forming the theoretical foundation of
invasion science. As artificial intelligence advances, such classification
schemes will become important references for organizing scientific
information. Our approach can be extended to other research fields,
fostering cross-disciplinary connections to leverage the scientific
knowledge needed to address Anthropocene challenges. The two datasets show
the final classification scheme presented in this paper and the literature
corpus used in this study.