XDTM: XML Data Type and Mapping for Specifying Datasets

Abstract. We are concerned with the following problem: How do we allow a community of users to access and process diverse data stored in many different formats? Standard data formats and data access APIs can help but are not general solutions because of their assumption of homogeneity. We propose a new approach based on a separation of concerns between logical and physical structure. We use XML Schema as a type system for expressing the logical structure of datasets and define a separate notion of a mapping that combines declarative and procedural elements to describe physical representations. For example, a collection of environmental data might be mapped variously to a set of files, a relational database, or a spreadsheet but can look the same in all three cases to a user or program that accesses the data via its logical structure. This separation of concerns allows us to specify workflows that operate over complex datasets with, for example, selector constructs being used to select and initiate computations on sets of dataset elements—regardless of whether the sets in question are files in a directory, tables in a database, or columns in a spreadsheet. We present the XDTM design and also the results of application experiments with an XDTM prototype.