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A "data sharing trust" model for rapid, collaborative science.

Vincent Chan1, Pier Federico Gherardini2, Matthew F Krummel3

  • 1Department of Microbiology and Immunology, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143-0511, USA; Department of Pathology, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143-0511, USA; ImmunoX Initiative, Department of Microbiology and Immunology, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143-0511, USA.

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Summary
This summary is machine-generated.

Complex datasets offer new discoveries. We introduce a "data sharing trust" to improve data sharing and management, maximizing the value of large datasets for future research.

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Area of Science:

  • Data Science
  • Information Management
  • Scientific Discovery

Background:

  • Large datasets hold potential for novel insights beyond their original research scope.
  • Effective data sharing and management are essential for unlocking this potential.
  • Implementing robust data sharing practices is challenging, especially pre-publication.

Purpose of the Study:

  • To introduce a novel framework, the "data sharing trust," designed to enhance the utility of complex datasets.
  • To address the challenges associated with effective and rapid data sharing and management.
  • To maximize the value derived from large-scale scientific data.

Main Methods:

  • Conceptual framework development for a data sharing trust.
  • Analysis of existing barriers to data sharing and management.
  • Proposal of strategies for trust implementation in scientific research.

Main Results:

  • The "data sharing trust" concept provides a structured approach to data management.
  • This framework facilitates proactive data sharing, moving beyond traditional post-publication access.
  • It aims to increase the accessibility and reusability of complex datasets.

Conclusions:

  • Data sharing trusts are a viable mechanism for enhancing the value of large datasets.
  • Implementing such trusts can accelerate scientific discovery by improving data accessibility.
  • This approach is crucial for realizing the full potential of complex data in research.