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Other literature type . 2025
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Conference object . 2025
License: CC BY
Data sources: Datacite
ZENODO
Conference object . 2025
License: CC BY
Data sources: Datacite
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Training Needs for FAIR Pathogen Data: A Global Survey

Authors: van Geest, Geert; Feitzinger, Anna; Thomas-Lopez, Daniel; Gurwitz, Kim T; Palagi, Patricia M.; Neves, Aitana; Williams, Jason;

Training Needs for FAIR Pathogen Data: A Global Survey

Abstract

The Pathogen Data Network (PDN) is a global consortium working to provide infrastructure, tools, training, outreach, and support for FAIR (Findable, Accessible, Interoperable, Reusable) infectious-disease data management. To effectively achieve its goals, PDN aims to understand the needs and experiences of various stakeholders who work with or are impacted by pathogen data. For this purpose, the members of PDN workstream 5 developed and distributed a global stakeholder survey, targeting those whose work or study involve pathogen data relevant to human health, such as researchers, data stewards, bioinformaticians, healthcare professionals, policymakers and educators. One important aim of the survey was to identify the barriers faced when working with pathogen data, covering areas such as data access and sharing, data quality and standardization, technology and resource limitations, legal and ethical policies, and collaboration challenges. The survey also asked participants to prioritize training and professional development topics and indicate preferred training formats. Finally, it asked for input on the most important PDN resources or tools, like the Pathogens Portal, metadata standards and workshops. The survey results have been collected in the first quartile of 2025 and will be used to guide PDN in shaping its training, educational and outreach initiatives and inform the development of its tools and services. In this poster, we will present a summary of the training-related survey responses and our planned interventions. 

Keywords

Pathogen, Training

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green