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  3. Community Needs For Fair Pathogen Data.
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  3. Community Needs For Fair Pathogen Data.

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Community needs for FAIR pathogen data.

Geert van Geest1, Daniel Thomas-Lopez2, Anna A Feitzinger3

  • 1SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.

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|April 27, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Systemic issues like funding and skilled personnel hinder infectious disease data sharing. Training in bioinformatics and using the Pathogens Portal are key priorities for improving data reuse and interoperability.

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Area of Science:

  • Public Health
  • Infectious Disease Research
  • Data Science

Background:

  • Infectious disease datasets are crucial for public health but face data sharing and integration barriers.
  • Achieving Findable, Accessible, Interoperable, and Reusable (FAIR) data is vital for scientific discovery and pandemic response.
  • The specific needs of the global pathogen data community require systematic characterization.

Purpose of the Study:

  • To identify infrastructural and educational priorities among infectious disease data stakeholders.
  • To guide community-responsive support for data sharing and interoperability initiatives.
  • To address the unmet needs of the global pathogen data community.

Main Methods:

  • A cross-sectional survey was distributed to experts within the Pathogen Data Network (PDN) and open professional channels.
  • 136 responses from researchers, healthcare professionals, bioinformaticians, and educators were analyzed.
  • Descriptive analysis identified prioritized barriers, training needs, and preferred support mechanisms.

    • Main Results:

    • Limited funding (74%), data aggregation challenges (68%), and personnel shortages (52%) were primary structural impediments.
    • Bioinformatics for infectious disease research (68%) and using the Pathogens Portal (51%) were top training priorities.
    • Virtual short courses (68%) and webinars (66%) were preferred training formats.

    Conclusions:

    • Barriers to FAIR pathogen data are predominantly systemic, not just technological.
    • The survey framework and dataset can serve as a reusable template for needs assessment in other regions.
    • Aligning support with identified priorities can enhance data interoperability and reuse in infectious disease research.