ArticleFrontiers in research metrics and analytics2026
Does interdisciplinary breadth shape research data sharing and citation impact? Evidence from six research fields.
Article in Frontiers in research metrics and analytics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Research data sharing has become an important component of open science, yet sharing benefits vary across research contexts. Existing studies have examined factors influencing data sharing and the citation advantage associated with open data, but less is known about how interdisciplinary breadth relates to observable sharing practices and whether the citation advantage of sharing differs across disciplines. This study investigates the relationships among interdisciplinary breadth, observable sharing practices, and citation impact. Methods: The study uses 566,188 journal articles indexed in OpenAlex from 2020 to 2025. Interdisciplinary breadth was operationalized as the number of Level-0 disciplinary concepts associated with each article. Observable sharing practices were identified through repository links, supplementary-material links, and textual sharing statements. Regression models were applied to examine associations among interdisciplinary breadth, data sharing, and citation impact across six research fields, and BERTopic-based topic modeling was also applied in history and digital humanities to explore topic-level variations. Results: The results show that interdisciplinary breadth had a predominantly negative but non-linear association with observable sharing, with sharing probability generally declining as breadth increased, although the decline weakened at higher levels. Articles with observable sharing signals were associated with higher citation counts overall, but the magnitude of this association varied substantially across fields. History exhibited the largest positive citation advantage, whereas digital humanities showed a negative but statistically uncertain association. Topic-level analysis further revealed that observable sharing was concentrated in specific research topics with distinct methodological and infrastructural characteristics. Discussion: These findings highlight that openness practices and their scholarly returns are influenced by disciplinary contexts. Understanding research data sharing therefore requires consideration of both researchers' willingness to share and the infrastructures and evaluation systems embedded in different research disciplines.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.