A Data Model for Distributed Multiresolution Multisource Scientific Data

Modern dataset sizes present major obstacles to understanding and interpreting the significant underlying phenomena represented in the data. There is a critical need to support scientists in the process of interactive exploration of these very large data sets. Using multiple resolutions of the data set (multiresolution), the scientist can identify potentially interesting regions with a coarse overview, followed by narrower views at higher resolutions. Scientific data sets are often multisourcecoming from different sources. Although it may be infeasible to physically combine multiple datasets into a single comprehensive dataset, the scientist would often like to treat them as a single logical entity. This paper describes formal conceptual models of multiresolution and distributed multisource scientific data along with an implementation of our multisource model. Our goal is to allow a scientist to describe a dataset that combines several multisource multiresolution datasets into a single conceptual entity and to provide efficient and transparent access to the data based on functionality defined by the model.