This article contributes to the development of methods for analysing research funding systems by exploring the robustness and comparability of emerging approaches to generate funding landscapes useful for policy making. We use a novel dataset of manually extracted and coded data on the funding acknowledgements of 7,510 publications representing UK cancer research in the year 2011 and compare these ‘reference data’ with funding data provided by Web of Science (WoS) and MEDLINE/PubMed. Findings show high recall (about 93%) of WoS funding data. By contrast, MEDLINE/PubMed data retrieved less than half of the UK cancer publications acknowledging at least one funder. Conversely, both databases have high precision (+90%): i.e. few cases of publications with no acknowledgement to funders are identified as having funding data. Nonetheless, funders acknowledged in UK cancer publications were not correctly listed by MEDLINE/PubMed and WoS in about 75% and 32% of the cases, respectively. ‘Reference data’ on the UK cancer research funding system are then used as a case-study to demonstrate the utility of funding data for strategic intelligence applications (e.g. mapping of funding landscape, comparison of funders’ research portfolios).
FULL-TEXT at http://arxiv.org/pdf/1604.04896.pdf
Author(s): Nicola Grassano, Daniele Rotolo, Joshua Hutton, Frederique Lang, and Michael M. Hopkins
Organization(s): Science Policy Research Unit (SPRU), University of Sussex
Source: Journal of the Association for Information Science and Technology
Year: 2016