The project will use foresight methods, as described by Bourgeois, Robin et al. in “The state of foresight in food and agriculture and the roads toward improvement” (2012) to explore mid- to long-term futures and drivers of change through participatory and multi-stakeholder approaches. 

Knowledge will be collected and analysed through different channels: expert panels, surveys, literature (academic and reports) reviews and during the workshops through SWOT and brainstorming, etc. to foster creativity and build possible scenarios for the “vision”. The figure below describes the methodology that the project will follow to envision future trends and scenarios, build a shared vision based on the preferred scenario and design the foresight roadmap to make this vision befall. 

erosa graph
e-ROSA’s roadmap planning process

Based on this methodology, the project will provide the necessary framework to answer the following questions and design a long-term foresight roadmap:

#1. What has happened and where are we now:

Depict the landscape of relevant initiatives, projects and research teams involved in digital agriculture at national and internationallevel

The first steps will consist in establishing the baseline analysis by scanning the current scientific technological, social, political landscape and identifying historic and current trends and factors that affect(ed) the study area and the related community. In doing so, the project will:

  • Map the scientific ecosystem relevant for digital agriculture using bibliometric analysis;

  • Collect and analyse policies and roadmaps from key players;

  • Complete these descriptions with surveys and open calls to communities to enrich the inventory of infrastructures and relevant projects;

  • Identify existing scientific, technological, social and political trends, current drivers and disruptions.

#2. What might/should happen:

Identify interests through participatory and multi-stakeholder approaches and establish the grand challenges to meet users’ needs

Anticipating potential new drivers and related variables, alternative and plausible sets of (preferred) futures requires input from multiple perspectives and a wide range of different domains. The project will involve the entire community of interest and reinforce the link between the different stakeholders by establishing a strategic dialogue between researchers, education, practitioners and policy makers. To do so, the process to build the roadmap will be totally open so that everybody can contribute and understand the progress in building the vision. This will rely mainly on the AIMS (Agricultural Information Management Standards) community by FAO, which is made up of individuals involved in agricultural information management from around the world, with varying levels of technical expertise. The following tools will be used to explore possible and desired scenarios:

  • Open consultations;

  • Webinars with keynote speakers from the different communities;

  • 2 workshops: The first one - “Community Building and fine-Mapping” - while improving the map of the current landscape, will build the foundation of future collaborations. Based on identified complementarities, overlaps, gaps, the second workshop - “Challenges & Solutions Envisioning” - will specifically address the needs of the community to develop the visioning strategy, i.e. i) lay out a description of the desirable end-states (i.e. what does the optimal digital agriculture landscape look like at the horizon 2030) and ii) propose possible pathways leading to these end-states (i.e. storylines describing the sequence of events that will suitably occur in the following ten years or more).

#3. Where do we want to be:

Reach a shared vision for an e-infrastructure for open science in agriculture

During the second workshop, the desirable visions will be discussed against main uncertainties, risks and constraints which could be encountered in the future and evaluated according to the following criteria:

  • Plausibility – the selected scenarios have to be capable of happening.

  • Differentiation – they should be structurally different and not simple variations on the same theme.

  • Consistency – the combination of logics in a scenario has to ensure that there is no built-in internal inconsistency that would undermine its credibility.

  • Decision-Making Utility – each scenario should contribute specific insights into the future that help make the decision identified in step one.

  • Challenge – the scenarios should challenge the community’s conventional wisdom about the future.

This analysis, based on objective criteria (focusing on probability of occurrence rather than desirability), will help achieve common consensus and build one shared vision of the future digital agriculture.

#4. How do we get there:

Build and discuss the roadmap to achieve the vision

The vision will be further discussed and transformed into an actionable roadmap with clear recommendations for implementation. A third workshop will be organised, to refine and validate, through a backcasting methodology, sound implementation modalities and steps towards unfolding the vision. The final foresight roadmap will thus connect the vision to the present.

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