Digital agriculture is broadly defined as the application of big data and precision technology systems in agriculture (Rotz et al., 2019). Innovation1 in digital agriculture is embedded in economic, political, social and ethical relations and as such should be regarded as a socio-technical process (Klerkx et al., 2019). Understanding and en- acting innovation processes in digital agriculture, including OFE, therefore requires constructive dialogue with a range of stakeholders. Advances in big data and precision technologies offer the prospect of a ‘step change’ in productivity and profitability, and present analytical, learning and decision support opportunities to farmers (Walter et al., 2017; Wolfert et al., 2017). However, their full potential is often not realised (Barnes et al., 2019; Finger et al., 2019) and does not match expectations (Weersink et al., 2018). This has been attributed in part to a gap between design and the reality of experiences on farm (Masiero, 2016). The need to incorporate user-perspectives to address these gaps is widely recognised (Dodson et, 2013). Researchers have demonstrated the value of integrating farmer and other key ac- tors actively in the design, development, implementation and evaluation of digital advisory tools and services. This allows analysis and understanding of users’ capa- cities, the enabling environment and the agricultural knowledge systems, as well as a consideration of scale and long-term purpose (Steinke et al., 2020). No