A strong information and knowledge base is critical at the heart of the foresight process, and is produced by:
- Stakeholder analysis
- Systems analysis
- Empirical evidence
- Data sets
- Quantitative modelling
- Qualitative analysis and insights
- Game Theory
These methods produce a rich set of resources and information that will be used in the systems mapping and foresight process. However, the information must be presented in a way that is easily approachable by the various stakeholders involved.
The table below categorizes the types of information that form part of the analysis and dialogue process. ‘Tacit formal’ information includes things like unpublished models and databases and information in the private domain, while ‘Formal Explicit’ include things like the ecosystem assessments and peer-reviewed materials that are shared with the wider public and specialist communities. ‘Tacit Informal’ includes opinions and experiences that are shared through stakeholder engagement processes, and ‘Explicit Informal’ include indigenous knowledge and practices, communal beliefs, and untested databases. An inclusive knowledge base ensures that the dialogue and analysis can be well-informed and not exclude the views of marginal groups.
Source: Fabricius, C., R. Scholes, and G. Cundill. 2006. Mobilizing knowledge for integrated ecosystem assessments. Pages 165-182 in W. V. Reid, F. Berkes, T. J. Wilbanks, and D. Capistrano, editors. Bridging scales and knowledge systems: concepts and applications in ecosystem assessment. Island Press, Washington, D.C., USA.
Computational models contribute to the ‘explicit’ set of knowledge and information discussed on page 16. They use equations to characterize how key processes (e.g. atmospheric, economic, water) operate, and use quantitative methods to simulate the interactions of the important drivers of the systems of concern. Examples of models used in food systems foresight are presented below:
IMPACT - The International Model for Policy Analysis of Agricultural Commodities and Trade (IFPRI) is a network of linked economic, water, and crop models. At its core is a partial equilibrium multi-market economic model, which simulates national and international agricultural markets.
GLOBIOM - Global Biosphere Management Model (IIASA) is used to analyze the competition for land use between agriculture, forestry, and bioenergy, which are the main land-based production sectors. As such, the model can provide scientists and policymakers with the means to assess, on a global basis, the rational production of food, forest fiber, and bioenergy, all of which contribute to human welfare.
MOSAICC - Modelling System for Agricultural Impacts of Climate Change (FAO), in partnership with European research institutes, has developed an integrated pack- age of models to assess the impacts of climate change on agriculture (including forestry), water resources and the national economy.
PEM - Policy Evaluation Model (OECD) partial equilibrium model based on the PSE database, developed to connect Producer Support Estimates (PSE) database and its economic outcome.
CAPRI (Common Agricultural Policy Regionalized Impact Modelling System) supports decision making related to the Common Agricultural Policy based on sound scientific quantitative analysis.
MAGNET is a multi-sector, multi-region computable general equilibrium model of the world economy which is widely used to simulate the effects of agricultural, trade, land and biofuel policies on the global economy, as well as for long-term projections (IPCC SSP scenarios and mitigation and adaptation options).
IMAGE (Integrated Model to Assess the Global Environment) is designed to capture interactions between economic activity, land use, greenhouse gas (GHG) emissions, climate, crop yields and other environmental variables. It includes a multi-region CGE model of global trade and production, a carbon-cycle module to calculate GHG emissions resulting from economic activity including energy and land use, a detailed land-use module and an atmosphere–ocean climate module that translates GHG emissions into climate outcomes.
Data sets and databases on food and foresight often provide methods and standards for food and agriculture statistics, and disseminates data for global monitoring, evaluation, and research. Data from these databases are used in computational models (discussed above). Example data sets that can be used in food systems foresight are presented below:
FAOSTAT provides free access to food and agriculture data for over 245 countries and territories and covers all FAO regional groupings
IFPRI Dataverse is a collection of IFPRI’s primary data and the compilation and processing of secondary data. The resulting datasets provide information at the local (household and community), national, and global levels.
OECD Datasets provide statistics on agriculture, development, economy, education, energy, environment, finance, health, technology, etc. They publish an Agricultural Outlook every year for a ten-year period
African Growth and Development Policy modeling consortium (AGRODEP) brings together dispersed and disparate statistical, economic, and geo-spatial data from Africa in one central Web data portal. It links existing key data sources, complements them as necessary, and develops shared standards, formats, and exchange protocols that facilitate access
Office for National Statistics is the UK's largest independent producer of official statistics and the recognised national statistical institute of the UK
World Bank Open Data provides free access to global development data by indicator and country and facilitates access to data collected through sample surveys of households, business establishments or other facilities
UNdata brings international statistical databases within easy reach of users through a single-entry point. Users can search and download a variety of statistical resources compiled by the UN statistical system and other international agencies
Global Health Observatory data repository contains an extensive list of indicators, which can be selected by theme or through a multi-dimension query functionality. It is the WHO’s primary health statistics repository
Resourcetrade.earth/ has been developed by Chatham House to enable users to explore the fast-evolving dynamics of international trade in natural resources, the sustainability implications of such trade, and the related interdependencies that emerge between importing and exporting countries and regions.