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  • × author_ss:"Lang, F."
  1. Lang, F.: Schlagwortgebung und Klassifizierung (1962) 0.00 
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  2. Lang, F.: Klassifikation : T.1-2. (1979-80) 0.00 
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  3. Lang, F.: Eugen Wüster 1898-1977 (1998) 0.00 
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  4. Lang, F.: Eugen Wüster 1898-1977 : Ein österreichischer Pionier der Terminologie und Dokumentation (1998) 0.00 
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  5. Grassano, N.; Rotolo, D.; Hutton, J.; Lang, F.; Hopkins, M.M.: Funding data from publication acknowledgments : coverage, uses, and limitations (2017) 0.00 
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    Abstract
    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 data set 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 (around 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%): That is, few cases of publications with no acknowledgment 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 around 75% and 32% of the cases, respectively. Reference data on the UK cancer research funding system are used as a case study to demonstrate the utility of funding data for strategic intelligence applications (e.g., mapping of funding landscape and co-funding activity, comparison of funders' research portfolios).
    Type
    a

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