Evaluating discrepancies in funding metadata across bibliographic and administrative databases: the case of South Korea’s public research funding
Year: 2026
Type: preprint
Abstract: Funding metadata underpins the identification of the relationship between research funding and outputs, yet its coverage and accuracy vary across databases. I examine discrepancies in funding metadata for South Korean government-funded research by comparing records from South Korea’s National Science & Technology Information Service (NTIS) with Web of Science and OpenAlex. Linking NTIS-reported publications across these three sources reveals substantial divergence: few project identifiers and publication-project pairs were captured across all three databases. These discrepancies stem from multiple compounding factors, including incomplete database indexing, optional or inconsistent funder acknowledgement policies, and variations in how project identifiers are described and extracted. Accounting for identifier variations and multi-phase project structures recovers additional matches but does not substantially close the overall gap. A logistic regression model further demonstrates that whether funding sources are acknowledged is linked to structural factors, such as stakeholder complexity regarding the co-authors and institutions involved in a publication. This indicates that acknowledgement omissions are driven not merely by technical limitations in metadata collection, but also by institutional constraints surrounding research funding. Furthermore, acknowledgement lag patterns, where the time gap between project execution and publication active years is virtually zero, point to systemic weaknesses in administrative reporting workflows. The paper concludes by recommending policy actions for funding agencies to ensure the interoperability and reliability of NTIS records. These findings underscore the need to evaluate funding metadata discrepancies not merely as a technical indexing challenge, but as an issue deeply embedded within the institutional structures of research systems.
Author: Soohong Eum
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7213862631