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Sökning: WFRF:(Dean Julie) > (2020)

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1.
  • Alexander, Steven M., et al. (författare)
  • Qualitative data sharing and synthesis for sustainability science
  • 2020
  • Ingår i: Nature Sustainability. - : Springer Science and Business Media LLC. - 2398-9629. ; 3:2, s. 81-88
  • Tidskriftsartikel (refereegranskat)abstract
    • Opportunities, challenges and recommended targeted actions to accelerate qualitative data sharing to address complex socio-environmental problems Socio-environmental synthesis as a research approach contributes to broader sustainability policy and practice by reusing data from disparate disciplines in innovative ways. Synthesizing diverse data sources and types of evidence can help to better conceptualize, investigate and address increasingly complex socio-environmental problems. However, sharing qualitative data for re-use remains uncommon when compared to sharing quantitative data. We argue that qualitative data present untapped opportunities for sustainability science, and discuss practical pathways to facilitate and realize the benefits from sharing and reusing qualitative data. However, these opportunities and benefits are also hindered by practical, ethical and epistemological challenges. To address these challenges and accelerate qualitative data sharing, we outline enabling conditions and suggest actions for researchers, institutions, funders, data repository managers and publishers.
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2.
  • Knudsen, Gitte M, et al. (författare)
  • Guidelines for the content and format of PET brain data in publications and archives : A consensus paper
  • 2020
  • Ingår i: Journal of Cerebral Blood Flow and Metabolism. - : SAGE Publications. - 0271-678X .- 1559-7016. ; 40:8, s. 1576-1585
  • Tidskriftsartikel (refereegranskat)abstract
    • It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.
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