ArticleScientific data2026
Construction of a Theoretical Framework for Scientific Data Governance.
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.
What it found
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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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The advancement of data-intensive sciences and artificial intelligence-driven sciences has introduced governance challenges for multi-source heterogeneous scientific data across diverse scenarios. Given the intricate entanglement of stakeholders, processes, and content in scientific data governance, this study intends to propose a theoretical framework to elucidate its complex dynamics and inform governance practices. The theoretical framework for scientific data governance consists of three core dimensions: data stakeholders, data lifecycle, and data governance elements. Non-systematic literature review was employed to identify the classification of data stakeholders and data lifecycle, and bibliometric analysis was used to extract the elements of scientific data governance. Meanwhile, based on the elements of data governance, five governance systems have been summarized, including organizational operation system, technical support system, risk prevention and control system, value realization system, and regulatory system.
Identifiers
What Socratic 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 Socratic graph.