Using data in the grant making cycle
Through our integrated grant making cycle map, we provide a list of methods, tools, and case studies that can be applied at each stage of the grant making process.
Explore our grant making cycle map
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JoinMethods and case studies
Visit our methods and case studies page for a full list of data-driven methods and case studies included on the platform.
Learn moreExplore the data innovation primers
Learn more about how specific data-driven methods and applications could be used in the grant making cycle by reading our data innovation primers. These primers aim to provide the top-level information needed to decide whether a method is right for your work.
These data innovation primers are an ongoing effort. Click here to share feedback on these primers or provide suggestions for methods you would like to learn more about.
Open Grantmaking Innovations
This series of resources describes how more open and effective grantmaking innovations can improve the legitimacy and effectiveness of grant-based public investments.
Living Evidence and Visualization
Living Evidence is the process of gathering and combining large quantities of evidence (i.e. research studies or data) related to a topic of interest into a consolidated format using computational tools and regularly generating updated summaries as new evidence emerges...
Digital Ethnography
Digital Ethnography is the process of using digital technologies to learn about the shared ambitions, behavior, culture, and experiences of communities across different issues...
Futures Studies
Futures Studies is the process of examining how systems could evolve over time in order to anticipate and prepare for multiple future outcomes...
Participatory Sourcing of Questions
Participatory Sourcing of Questions (PSQ) is a method to scope, formulate, and prioritize data-actionable research questions with key stakeholders...
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Share your ideas of methods, applications, and case studies to be featured on the platform. We also welcome ideas for learning events and feedback on the existing methods or the platform as a whole.
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