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5 Closing Remarks and General Discussion
Pages 51-58

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From page 51...
... • What concrete steps should be pursued next to advance discussions and actions for relevant research, operations, and policies? The workshop activities then concluded with Poste moderating a discussion among Scott Dowell, the deputy director for surveillance and epidemiology at the Bill & Melinda Gates Foundation; Jennifer Gardy, an assistant professor in the School of Population and Public Health at the University of British C ­ olumbia; Kent Kester, the vice president and head of translational science and biomarkers at Sanofi Pasteur; Lonnie King, a professor and dean emeritus of the C ­ ollege of Veterinary Medicine at The Ohio State University; Martin Sepúlveda, a recently retired senior physician at IBM's Watson Research Laboratory; Jay 51
From page 52...
... In the end, he said, the ultimate value of big data will come down to its utility for the public health practitioner and policy maker. Learning from Others Learning lessons from other fields, particularly with regard to integrating big datasets as opposed to merely aggregating them, will be critical to quickly and effectively addressing the challenges posed by Poste, a message reiterated by several workshop participants when each was given the opportunity to recount the key messages of the small group discussions that started the second day of the workshop.
From page 53...
... Compiling comprehensive genetic signature databanks for infectious diseases, he said, will lead to the development of distributed, rapid, and automated point-of-need diagnostic tests, which in turn will enable a real-time situational awareness of emerging threats and lead to faster mobilization of responses to those threats. The data for these signature databanks will come from comprehensive front-line sampling of sentinel species informed by geo-demographic and geographical ­nformation i system applications.
From page 54...
... In addition, too many biomedical datasets are problematic because of "sloppy science" that produces irreproducible data, the use of underpowered statistics that over-fit large feature sets to small sample sizes, silos and data tombs, a reluctance to share data, the limited use of common ontologies, inconsistent and incompatible data formats, and episodic snapshots of dynamic systems. Sharing Data Siegel, Gardy, and Kester all stressed the need for researchers to stop hording their data.
From page 55...
... It will change the cultural process of knowledge acquisition by fostering the devel­ opment of large-scale collaboration networks, consortia, and open systems to augment individual investigator-driven research as well as the analysis and application of knowledge to produce real-time intelligence, deeper insights, and better decision making. Big data, he predicted, will also change education, training, ­ health care delivery, public policy formation, and the critical competencies and infrastructure required for institutional relevance and competitiveness.
From page 56...
... In his opinion, he added, public health will benefit from the new partners that big data will bring to the field, and he encouraged public health organizations to reach out to disciplines such as retailing and marketing, which he said have the most experience with data analytics and novel insights into using big data. As a final thought, he said that these are disruptive times in public health as a result of the emergence of new infectious diseases and such times demand innovation.
From page 57...
... CLOSING REMARKS AND GENERAL DISCUSSION 57 forward, part of the forum's task will be to think about where we can delve into some of these use cases and explore where exactly benefit can be had, what is the most effective path toward those concrete, real-world benefits, and what the pitfalls are, and where we can be led astray by big data."


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