Latest Project to Cure PKD

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This presentation outlines a mechanism for using the power of "Big Data", social networking and technology infrastructure to speed the process of curing a horrible disease.

Health & Medicine Business

PKuReD Prepared 10/01/2008 By Sean Flaherty, Mark Stone & Ken Kahtava For the Polycystic Kidney Disease Foundation

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The Idea If we could harness the breadth and passion of the PKD community, we could assemble an unprecedented database that would add immeasurable value to the research being conducted in the Polycystic Kidney Disease space.

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Abstract: Sharing data is a tenet of science, yet commonplace in only a few subdisciplines. Recognizing that a data sharing culture is unlikely to be achieved without policy guidance, some funders and journals have begun to request and require that investigators share their primary datasets with other researchers. The purpose of this study is to understand the current state of data sharing policies within journals, the features of journals that are associated with the strength of their data sharing policies, and whether the strength of data sharing policies impact the observed prevalence of data sharing. Methods: We investigated these relationships with respect to gene expression microarray data in the journals that most often publish studies about this type of data. We measured data sharing prevalence as the proportion of papers with submission links from NCBI’s Gene Expression Omnibus (GEO) database. We conducted univariate and linear multivariate regressions to understand the relationship between the strength of data sharing policy and journal impact factor, journal subdiscipline, journal publisher (academic societies vs. commercial), and publishing model (open vs. closed access). Results: Of the 70 journal policies, 53 made some mention of sharing publication-related data within their Instruction to Author statements. Of the 40 policies with a data sharing policy applicable to gene expression microarrays, we classified 17 as weak and 23 as strong (strong policies required an accession number from database submission prior to publication). Existence of a data sharing policy was associated with the type of journal publisher: 46% of commercial journals had data sharing policy, compared to 82% of journals published by an academic society. All five of the openaccess journals had a data sharing policy. Policy strength was associated with impact factor: the journals with no data sharing policy, a weak policy, and a strong policy had respective median impact factors of 3.6, 4.9, and 6.2. Policy strength was positively associated with measured data sharing submission into the GEO database: the journals with no data sharing policy, a weak policy, and a strong policy had median data sharing prevalence of 8%, 20%, and 25%, respectively. Conclusion: This review and analysis begins to quantify the relationship between journal policies and data sharing outcomes. We hope it contributes to assessing the incentives and initiatives designed to facilitate widespread, responsible, effective data sharing.

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