THE ROLE OF INTERNATIONAL SCIENTIFIC COLLABORATION ON DATASETS AND CITATION IMPACT: A SCIENTOMETRIC ANALYSIS OF NATURE SCIENTIFIC DATA (2014-2024)

Abstract

Scientific datasets are foundational to building scientific knowledge. In this study, we investigated how dataset origin and current author affiliation location affect a publication's citations, an indicator of success and impact. We examined the effect of local author involvement and Global North-South collaboration on publication citation outcomes. We analyzed 1,440 datasets from Nature Scientific Data (2014"“2024) across seventeen fields. On average, 40% of authors had an affiliation matching the abstract's referenced location, marking them as local authors. A general linear regression analysis showed the local author proportion had no significant impact on citation counts. Using World Bank income classifications to distinguish Global North and Global South countries, further analysis revealed disparities in authorship patterns. Specifically, when the team was from the Global North 90% of citations were from datasets also published in Global North. When the team was from the Global South, 65% of citations were from datasets with data from both the Global North and South. These findings highlight a citational advantage for Global North datasets and authors and highlight the greater recognition Global South authors receive when collaborating across regions. Local author involvement alone does not impact the citation count, raising questions about equity in data publication and recognition.