Evidence map›Paper›PMID 42277083›Full record

ArticleScientific data2026

The Role of Data Papers in Scientific Data Dissemination and Reuse.

Liyue Chen, Zihao Qu, Na Ma, Xiaomin Liu

Abstract read
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liyue ChenNational Science Library, Chinese Academy of Sciences, Beijing, 100190, China.
Zihao QuNational Science Library, Chinese Academy of Sciences, Beijing, 100190, China.
Na MaNational Science Library, Chinese Academy of Sciences, Beijing, 100190, China.
Xiaomin LiuNational Science Library, Chinese Academy of Sciences, Beijing, 100190, China. liuxm@mail.las.ac.cn.

Funding

China Association for Science and Technology Foundation 2023QNRC001
6 · The paper itself

Abstract

Data papers have emerged as a distinctive publication format in the open science era, yet their actual role in fostering scientific data reuse remains uncertain. Drawing on extensive citation-context datasets and large language models, this study investigates the specific contributions and citation purposes of data papers, complemented by a comparative analysis across diverse disciplinary domains. The findings show that while data papers significantly enhance dataset visibility and scholarly recognition, most citations emphasize descriptive or contextual information rather than facilitating direct computational, comparative, or synthetic reuse. Moreover, despite persistent advocacy for a "data-driven" research paradigm, the contribution of data papers to catalyzing novel scientific insights appears to be modest and often indirect. Notable disciplinary differences reveal that data-intensive fields, such as Earth and Life Sciences, embed datasets directly into research workflows, whereas more conceptual domains primarily treat data papers as methodological guides or contextual references. Additionally, publishing attributes-spanning journal practices to national data infrastructures-emerge as critical determinants of reuse patterns, with dissemination effectiveness shaped more by publication management and the thematic priorities of editors than by output volume alone.

Identifiers

PMID42277083
PMCPMC13601586

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.