<p>Clustering of innovation– the driving core behind regional innovation systems (RISs)– is a crucial contributor to economic prosperity. Such clusters are often denoted as innovation districts. While spatial characteristics, including accessibility to innovation services, rich amenities, and mixed land-use, have been associated with heightened regional innovativeness in previous studies, there is a gap in our knowledge on how to identify the boundaries of innovation districts within RIS. To fill this research gap, we propose a (data-driven) multi-layer approach consisting of a set of indicators depicting four RIS sub-systems (knowledge generation, knowledge exploitation, regional policy, and living environment sub-systems) and three different levels of spatial characteristics (clustering, coupling and coordination, and spatial mixing). The feasibility of the suggested “innovation district evaluation framework” is tested based on multi-source point of interest and patent data collected in Qingdao, China. The paper argues that the framework is a valuable tool assisting evidence-based development of specialized or diversified planning strategies to enhance the innovativeness of cities and to facilitate knowledge-based urban development.</p>