Boundary objects - flexible enough to appeal and apply to different interest groups, and yet robust enough to maintain core concepts - offer a medium to connect findings from different disciplines.
We propose a boundary object on scale 鈥?a 3-dimensional framework, whose axes are reality-, model- and data-scale. This framework can be applied to facilitate an improved transdisciplinary understanding of scale and more conscious scale selection that promotes the credibility, salience and legitimacy of decision support systems.