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Mining the grant-makers

This paper outlines how the NCVO aims to use data from grant-making bodies to identify below the radar organisations

Nesta Working Paper 15/06
Issued: May 2015
JEL Classification: L31  
Keywords: Voluntary organisations, below the radar, open data.


Below the radar organisations are small, unregistered, but form a vital part of communities across the country.

The nature of below the radar organisations means they are difficult to quantify and measure, and so the assessment of them in NCVO's Civil Society Almanac series has always been a partial one. Our approach, outlined in the paper, aims to use data from grant-making bodies (both statutory and private) to identify below the radar organisations.

By matching data about who these grant-making organisations fund with data on registered organisations, we hope to identify the remainder as below the radar. This approach, we believe, will enable us to pick up organisations outside the sphere of known, registered organisations.

However, the method will pick up particular types of organisations - those that have an interest or an ability to seek out grant funding. In this sense, this method can be seen as a way of lowering the radar, rather than bypassing it entirely.

The approach had some success in identifying below the radar organisations, allowing some of their characteristics to be explored. Some possibilities for future research and recommendations for improving the source open data are also included.


David Kane, NCVO

The Nesta Working Paper Series is intended to make available early results of research undertaken or supported by Nesta and its partners in order to elicit comments and suggestions for revisions and to encourage discussion and further debate prior to publication (ISSN 2050-9820). The views expressed in this working paper are those of the author(s) and do not necessarily represent those of Nesta.


Peter Baeck

Peter Baeck

Peter Baeck

Director of the Centre for Collective Intelligence Design

Peter leads work that explores how combining human and machine intelligence can develop innovative solutions to social challenges.

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