Funding acknowledgments in the Web of Science: completeness and accuracy of collected data

被引:0
|
作者
Belén Álvarez-Bornstein
Fernanda Morillo
María Bordons
机构
[1] Spanish National Research Council (CSIC),Science, Technology and Society Department, IFS
[2] Complutense University (UCM),Library and Information Science Department, Faculty of Library and Information Sciences
来源
Scientometrics | 2017年 / 112卷
关键词
Funding acknowledgments; Web of Science; Standarization;
D O I
暂无
中图分类号
学科分类号
摘要
The study of acknowledgments as a source of data on research funding is gaining ground in science, as exemplified by the present inclusion of this information in bibliographic databases such as Web of Science (WoS). The objective of this paper is to explore the completeness and accuracy of WoS in extracting and processing funding acknowledgment data. With this purpose, a random sample of articles published in eight thematic areas and selected from the scientific output of Spain in 2014 are analyzed. Funding information that appears in original articles is recorded by WoS in the “funding text” field, but is also extracted to the “funding agency” and “grant number” subfields. In the extraction process, some funding information was lost in 12% of the articles and the distribution of agencies and grant numbers by subfield was not always consistent. In addition, funding support is often incompletely reported by authors: in about half of the articles we studied, the country of origin of the funder or the grant number(s) were not mentioned. We propose and discuss the need to develop more detailed guidelines on how to acknowledge funding. More accurate documentation of funding sources in published articles would benefit researchers, funders and journals, and enhance the reliability and usefulness of studies on funding acknowledgments.
引用
收藏
页码:1793 / 1812
页数:19
相关论文
共 50 条
  • [21] Document type assignment accuracy in the journal citation index data of Web of Science
    Paul Donner
    Scientometrics, 2017, 113 : 219 - 236
  • [22] Accuracy and completeness of mortality data in the Department of Veterans Affairs
    Sohn M.-W.
    Arnold N.
    Maynard C.
    Hynes D.M.
    Population Health Metrics, 4 (1)
  • [23] Improved Accuracy/Completeness of EHR Race/Ethnicity Data
    Weathers, Allison L.
    Garg, Neeta
    Lundgren, Karen B.
    Benish, Sarah M.
    Baca, Christine B.
    Benson, Richard T.
    NEUROLOGY-CLINICAL PRACTICE, 2024, 14 (03)
  • [24] Completeness and Accuracy of Death Registry Data in Golestan, Iran
    Hasanpour-Heidari, Susan
    Jafari-Delouei, Nastaran
    Shokoohifar, Nesa
    Sedaghat, Seyed Mehdi
    Moghaddami, Abbas
    Hosseinpour, Reza
    Poorabbasi, Mohammad
    Gholami, Masoomeh
    Semnani, Shahryar
    Naeimi-Tabiei, Mohammad
    Honarvar, Mohammad Reza
    Fazel, Abdolreza
    Etemadi, Arash
    Bray, Freddie
    Roshandel, Gholamreza
    ARCHIVES OF IRANIAN MEDICINE, 2019, 22 (01) : 1 - 6
  • [25] Data accuracy and completeness: General practitioner versus hospitals
    Bain, M
    Chalmers, J
    Brewster, D
    BRITISH JOURNAL OF GENERAL PRACTICE, 1996, 46 (409): : 495 - 495
  • [26] Evaluation of neonatal mortality data completeness and accuracy in Ghana
    Dadzie, Dora
    Boadu, Richard Okyere
    Engmann, Cyril Mark
    Twum-Danso, Nana Amma Yeboaa
    PLOS ONE, 2021, 16 (03):
  • [27] SQL query to increase data accuracy and completeness in PATSTAT
    Pasimeni, Francesco
    WORLD PATENT INFORMATION, 2019, 57 : 1 - 7
  • [28] Usefulness, completeness, and accuracy of web sites providing information on osteoarthritis in dogs
    Jehn, CT
    Perzak, DE
    Cook, JL
    Johnston, SA
    Todhunter, RJ
    Budsberg, SC
    JOURNAL OF THE AMERICAN VETERINARY MEDICAL ASSOCIATION, 2003, 223 (09) : 1272 - +
  • [29] ANALYSIS OF THE WEB OF SCIENCE FUNDING ACKNOWLEDGEMENT INFORMATION FOR THE DESIGN OF INDICATORS ON 'EXTERNAL FUNDING ATTRACTION'
    Yegros-Yegros, Alfredo
    Costas, Rodrigo
    14TH INTERNATIONAL SOCIETY OF SCIENTOMETRICS AND INFORMETRICS CONFERENCE (ISSI), 2013, : 84 - 95
  • [30] The Role of Data Science in Web Science
    Phethean, Christopher
    Simperl, Elena
    Tiropanis, Thanassis
    Tinati, Ramine
    Hall, Wendy
    IEEE INTELLIGENT SYSTEMS, 2016, 31 (03) : 102 - 107