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Handling Open Data and the Data Explosion
There is a data explosion in genomics research and the elephant in the room is that it is very difficult to organize and make sense of any of it, let alone all of it. Labs are generating more of it, and more of it, through funding mandates, are becoming publicly available.
We have previously discussed the problems in organizing and making sense of the data being generated within your own organization “Data Management: it starts at the bench” (Nature Immunology, Dec 2009, Chaussabel et al). Now, we want to talk about how to combine your experimental data along with publicly available data to advance discovery.
Our case study is an international multi center study into infectious disease where we have clinical and experimental data being captured in Macedonia, Mexico, Spain, Thailand, and the United Stated. We combine data from all of these sites along with publicly available data to help answer questions on this study and in our ongoing research in personalized medicine.
We will discuss the techniques and the systems that we have built, using open source systems, to enable you to implement similar solutions in your own organizations.
Charlie Quinn has over 20 years of systems development experience and has recently joined the Benaroya Research Institute in Seattle, WA as the Director of Data Management and Data Integration. Prior to joining Benaroya he worked on various projects usually involving systems and data integration, data mining, and graphic visualization in Canada, the US, and parts of Asia.
More recently, he has worked with the Baylor Institute for Immunology Research in Dallas, Texas developing new techniques for data reduction, data mining, distributed collaboration, data management and data integration.
When not working he seems to run a lot of marathons, the occasional triathlon, and spends a fair bit of time outside exploring the pacific northwest.