Data Management
Researching large-scale data interoperability for the earth and life sciences.
Our research addresses the broad areas of improving discovery, access, interoperability and reusability of large-scale data and metadata pertaining to natural sciences. This includes many topics, with emphasis on data and metadata modeling and standards development; data transformation, distribution, persistence, and change detection; standards for globally unique identifiers; machine learning applications for content aggregation and vocabulary mapping; and high-volume indexing supporting discovery and visualization.