DATA CONSERVANCY: DIGITAL CURATION OF THE MAGMATIC SYSTEM OF MCMURDO DRY VALLEYS, ANTARCTICA

The Data Conservancy (DC) is an NSF-funded effort to build, implement, and sustain a comprehensive digital research archive with the goal of supporting new forms of inquiry and learning via a virtual research structure. Led by PI Sayeed Choudhury, DC is working with 5 research groups at JHU to comprehensively digitally curate specific areas of their long-term and ongoing research efforts. One of the research topics involves the comprehensive magmatic system displayed in the Ferrar Dolerites of the McMurdo Dry Valleys, Antarctica, where BDM has worked since 1992. The Ferrar Dolerites are one of the most complete and best exposed examples of an integrated magmatic system known and exhibit almost unlimited potential as a natural laboratory for understanding magmatic processes. This makes all aspects of the Dry Valleys data a prime candidate for full digital preservation, which is a challenging task. This first year’s work on the Dry Valleys data has been devoted to determining user requirements, starting the process of converting "analog" data into digital form, and readying data files and metadata for loading into the Data Conservancy System (DCS) software prototype. To date we have prepared four field seasons of field photos, images for over 800 rock samples, and over 300 geochemical analyses for loading into the DCS software prototype. Metadata have been prepared by importing them into a relational database system. Once imported and normalized, the metadata can be edited, queried, formatted, and output in the required form for loading into the DCS system. As we continue digitizing and preparing data for the DCS, our focus will turn increasingly to expanding and refining the Dry Valleys metadata. A key objective is to preserve relationships between the disparate types of data during the process of a comprehensive data/subject integration. Rich metadata are needed to allow users of the Dry Valleys to discover, explore, and retrieve sets of data that are scientifically meaningful and that also realistically represent the actual field context of the observations and samples. Adherence to existing metadata standards is important in facilitating interoperability with existing archives such as the Glacier Photo Collection at the National Snow and Ice Data Center.