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The good news is that it is now possible to create large databases of information about images and data standards do exist. The bad news is that each of these databases is protected by proprietary formats that do not communicate with one another and standards do not yet exist for all image types. Researchers from each of the disciplines under an umbrella term called imaging refer to the images in a unique way, using different vocabulary. Wouldn't it be nice if a scientist could simply ask questions without regard to disciplinary boundaries and harness all of the available data about a tissue, cells, genes, proteins, and other parts of the body to prove or disprove a hypothesis?

The promise of Big Data. The promise of integrating them awaits technical solutions, such as that represented by the large but mutually-exclusive imaging data sets in each discipline, is that mashups can be made that integrate two or more data sets in a single graphical interface. Such mashups await technical solutions in the areas of data standard development and implementation, software development, and innovative applications of the resulting integration. A significant start to all of these technical solutions comprise the National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) and its sub-projects.

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