In order to implement a regional innovation policy, regional decision-makers need an efficient information system that enables them to characterize their territory in detail and identify relevant development opportunities. In this article, we propose a methodological framework for developing such an informational system, emphasising two dimensions whose complementarity is often neglected: on the one hand, the type of information required, and on the other hand, the characteristics of the data to be collected. We explain that the first dimension can be characterised using the Regional Innovation Systems (RIS) approach. The results of this work highlight that four key components need to be analysed in order to describe and understand how the regional innovation system operates: Knowledge production and accumulation; Transfer and commercialisation of innovations; Supporting innovation policies; Regional system cooperation/collaboration. For the second dimension, we draw on the key principles of informational decision support approaches to identify the desirable characteristics of the data. We emphasise that a useful and effective informational system must pay close attention to the characteristics of the data used and consider the selection of databases according to five criteria (Geolocatable; Granularity; Nominative; Simple to use; Accessibility) in order to be able to truly inform the four components of the RIS in a concrete and operational way. We use the example of research laboratories to show the heuristic potential of the proposed framework. We conclude by explaining how this tool can be mobilised to help improve regional innovation policies. In particular, we highlight the role it can play in defining regional policies that are co-designed with regional actors.