IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v68y2017i4p999-1017.html

Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations

Author

Listed:
  • Nicola Grassano
  • Daniele Rotolo
  • Joshua Hutton
  • Frédérique Lang
  • Michael M. Hopkins

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 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 identi ed 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).
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
  • Handle: RePEc:bla:jinfst:v:68:y:2017:i:4:p:999-1017
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/asi.23737
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jinfst:v:68:y:2017:i:4:p:999-1017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.