Characterization, description, and considerations for the use of funding acknowledgement data in Web of Science

TL;DR

This paper analyzes the characteristics and coverage of funding acknowledgement data in Web of Science, highlighting its limitations and potential for bibliometric research since 2008.

Contribution

It provides a detailed characterization of funding acknowledgement data in Web of Science, revealing coverage patterns and limitations across years, document types, and languages.

Findings

Funding data coverage is very low before 2009.

Coverage is mainly for articles and reviews in SCIE and SSCI.

English-language publications are most reliably covered.

Abstract

Funding acknowledgements found in scientific publications have been used to study the impact of funding on research since the 1970s. However, no broad scale indexation of that paratextual element was done until 2008, when Thomson Reuters Web of Science started to add funding acknowledgement information to its bibliographic records. As this new information provides a new dimension to bibliometric data that can be systematically exploited, it is important to understand the characteristics of these data and the underlying implications for their use. This paper analyses the presence and distribution of funding acknowledgement data covered in Web of Science. Our results show that prior to 2009 funding acknowledgements coverage is extremely low and therefore not reliable. Since 2008, funding information has been collected mainly for publications indexed in the Science Citation Index Expanded (SCIE); more recently (2015), inclusion of funding texts for publications indexed in the Social Science Citation Index (SSCI) has been implemented. Arts & Humanities Citation Index (AHCI) content is not indexed for funding acknowledgement data. Moreover, English-language publications are the most reliably covered. Finally, not all types of documents are equally covered for funding information indexation and only articles and reviews show consistent coverage. The characterization of the funding acknowledgement information collected by Thomson Reuters can therefore help understand the possibilities offered by the data but also their limitations.