Hi Jukka, UIMA has specifically been designed to support analysis of arbitrary data types. In addition to a flexible type system for creating an appropriate analysis "language" for analytics to communicate with each other, UIMA has other features that should be applicable to your domain. In particular, support for analyzing large artifacts, including access to remote data and re-segmentation of artifact(s) into new artifacts that can be passed along to specified analytics,
Other advantages of using UIMA would be to reuse existing UIMA components for analyzing free text associated with an EEG image, and for components that make it easy to create search indexes to find content matches based on the analysis. The best place to start is to develop a vision for the overall application you would like to have. For a new analysis domain such as this, there are not many type system definitions available to reuse, but designing the data model is generally the first detailed UIMA design step, even before deciding the modularity of analytics. Eddie Epstein
