Data Curation Profiles are designed to capture requirements for specific data generated by a single scientist or scholar as articulated by the scientist him or herself. They are also intended to enable librarians and others to make informed decisions in working with data of this form, from this research area or sub-discipline. Data Curation Profiles employ a standardized set of fields to enable comparison; however, they are designed to be flexible enough for use in any domain or discipline. Context A profile is based on the scientist/scholar's reported needs and preferences for these data. They are derived from several kinds of information, including interview and document data, disciplinary materials, and standards documentation. Sources of Information • An initial interview with the scientist conducted in August, 2010. • A second interview with the scientist conducted in September, 2010. • A worksheet completed by the scientist as a part of the interviews. • A published paper explaining the research and the methodology used to gather, process and analyze the data set in question. Scope Note The scope of individual profiles will vary, based on the author's and participating researcher's background, experiences, and knowledge, as well as the materials available for analysis. Editorial Note Any modifications of this document will be subject to version control, and annotations require a minimum of creator name, data, and identification of related source documents. Author's Note This Astrophysics data curation profile is based on analysis of interviews, a completed worksheet and information gathered from a publication, collected from a researcher working in this research area or sub-discipline. Some subsections of the profile were left blank; this occurs when there was no relevant data in the interview or available documents used to construct this profile.

The Chronopolis Digital Preservation Initiative, one of the Library of Congress’ latest efforts to collect and preserve at-risk digital information, has completed its first year of service as a multi-member partnership to meet the archival needs of a wide range of domains.Chronopolis is a digital preservation data grid framework developed by the San Diego Supercomputer Center (SDSC) at UC San Diego, the UC San Diego Libraries (UCSDL), and their partners at the National Center for Atmospheric Research (NCAR) in Colorado and the University of Maryland's Institute for Advanced Computer Studies (UMIACS).Chronopolis addresses a critical problem by providing a comprehensive model for the cyberinfrastructure of collection management, in which preserved intellectual capital is easily accessible, and research results, education material, and new knowledge can be incorporated smoothly over the long term. Integrating digital library, data grid, and persistent archive technologies, Chronopolis has created trusted environments that span academic institutions and research projects, with the goal of long-term digital preservation.A key goal of the Chronopolis project is to provide cross-domain collection sharing for long-term preservation. Using existing high-speed educational and research networks and mass-scale storage infrastructure investments, the partnership is leveraging the data storage capabilities at SDSC, NCAR, and UMIACS to provide a preservation data grid that emphasizes heterogeneous and highly redundant data storage systems.In this paper we will explore the major themes within Chronopolis, including:a) The philosophy and theory behind a nationally federated data grid for preservation. b) The core tools and technologies used in Chronopolis. c) The metadata schema that is being developed within Chronopolis for all of the data elements. d) Lessons learned from the first year of the project.e) Next steps in digital preservation using Chronopolis: how we plan to strengthen and broaden our network with enhanced services and new customers.

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The NSF-DIGARCH is building digital preservation lifecycle management infrastructure for the preservation of large-scale multimedia collections.The infrastructure consists of interfaces to TV production lifecycle systems, metadata definition and capture systems, and a persistent archive workflow which preserves the material in a SRB data grid. Kepler is used to build the workflow.