Automatic transformations between geoscience standards using XML

As models and analysis tools for geoscience applications become increasingly complex, they allow researchers to manipulate larger, richer, and more finely-grained datasets, often gathered from diverse heterogeneous sources. These complex models and analysis tools provide scientists with opportunities to investigate phenomena in much greater depth, but this additional power is not without cost. Often this cost is expressed in the time required on the part of the researcher to identify, gather, and transform the data necessary to satisfy the demands of their data-intensive computational tools. In addition, it can be difficult to extract all of the meaningful contents of the datasets when metadata is missing, nonstandardized, or in a format unfamiliar to or incompatible with the user application or analysis tool. The evolution of XML standards has simplified this problem by providing domain-specific methodologies for creating self-describing datasets. The evolution of XML standards has also presented the challenge of choosing the best standard for each scientific domain and associated community of interest (COI); however, the process of selecting or creating a domain-specific XML data format standard can be extremely contentious. In addition, many researchers require information compilation from diverse datasets that are stored using differing standards. This research effort presents a mechanism for automating transformations between scientific standards using XML with a focus on the application of the technology to the diverse geoscience XML standards while maintaining the integrity associated with the datasets. This technological capability minimizes the impact of committing to a particular XML standard by providing the flexibility to transform data between standards either to update or change the standard, to bring datasets into conformance for a particular application or data portal, or to transform data to increase its usability for new COIs while maintaining data integrity. ility for new COIs while maintaining data security standards.