Synthesis research includes integrating existing data or knowledge from different sources to answer a question or questions that will support climate and development policy and/or practice. Synthesis typically integrates across multiple disciplines, and transcends academic boundaries to include associated knowledge from policy or practice. Research can be focused on any geographical scale, but if your research includes very localised synthesis (e.g., a focus on a specific city or locality as opposed to a synthesis across many cities or localities or cases) then the research should be relevant by being able to inform research, policy and/or practice in other contexts more generally.
Examples of synthesis research include, but are not restricted to: (i) combining data from many independent research projects or data sources to produce insights across different contexts; (ii) integration of diverse quantitative and/or qualitative data such as multiple case studies, government datasets, satellite data, climate model data, commercial data or other data and knowledge types to undertake a novel analysis; (iii) convening experts from different backgrounds to address a question through expert elicitation, delphi processes, or other approaches; (iv) conceptual synthesis of different theories or frameworks, or integration of different existing methods or models (e.g., integration of different approaches to vulnerability assessment); (v) extracting and processing data from reports and research articles or other sources such as social media or remote sensing to generate large, newly integrated datasets and analysing the resulting data to produce new insights or evidence; (vi) using machine learning to assist with synthesis of large datasets; (vii) large systematic reviews, evidence mapping, or meta-analyses that combine statistical results from multiple separate studies. Teams might often propose to adopt multiple approaches to generating synthesis results, such as integrating diverse quantitative data coupled with synthesis of qualitative frameworks. Proposals should provide evidence that sufficient data and appropriate analytical tools are available or will be developed to tackle the research questions. This synthesis of existing data may often require substantial data processing (e.g., for cleaning climate impacts data, or aggregating social survey data) and can often lead to the development of new, integrated datasets or knowledge frameworks as important research products. Our requests for proposals will not support new data collection using fieldwork or laboratory experiments.