Figure 1

Rethinking knowledge-based innovations as being composed of actors and narrators. In a knowledge ecosystem such as public health pharmacogenomics, innovation actors co-produce knowledge and calibrate their actions and trajectory through open and transparent mutual learning, enabled by recursive practices such as wiki-governance. First-order narrators, who are situated at a crucial but not imperceptible analytical distance from the innovation actors, can examine and steer the innovation ecosystem trajectory, thereby contributing to collective action in the innovation ecosystem. Second-order narrators (for example, innovation observatories represented by citizen scholars, hitherto marginalized groups, and patients) can further keep the first-order narrators in check by making them more accountable, and by rendering visible their actions and situating them in a socio-technical context. Definitions: phase 1 translation (T1) aims to advance a basic genome-based discovery into a candidate health application (for example, a pharmacogenomics test); phase 2 translation (T2) concerns the development of evidence-based guidelines for a pharmacogenomics application; phase 3 translation (T3) aims to connect evidence-based guidelines with health practice, through delivery, dissemination and diffusion research; phase 4 translation (T4) evaluates the real world health outcomes of a pharmacogenomic application. See Khoury et al. [36] for the T1 to T4 translation research continuum and its actors.