NSF’s New Data Management System for Arctic Research Programs
Building on the Cooperative Arctic Data and Information Service (CADIS; http://www.aoncadis.org/), the NSF- funded Advanced CADIS (ACADIS) system is being developed to address the growing and increasingly diverse data management needs of the NSF arctic research community. In July 2011, NSF awarded a four-year continuing grant to the team of ACADIS investigators from the National Snow and Ice Data Center (NSIDC), the University Corporation for Atmospheric Research (UCAR), and the National Center for Atmospheric Research (NCAR). The new ACADIS system will foster scientific synthesis and discovery by providing a service that makes data available to NSF investigators for access and analysis across multiple disciplines. ACADIS will also provide the community with data archival services to preserve data into the future, and value-added products to make the data more useful to more people.
Current Data Advisory Committee Members
Andrew Slater, NSIDC, land surface processes
Dave Bailey, NCAR, global climate modeling
Larry Hamilton, representing SEARCH and the social sciences
Mary-Louise Timmermans, Yale University, deep-water oceanography
Craig Tweedie, University of Texas at El Paso, terrestrial ecology
Carin Ashjian, Woods Hole Oceanographic Institution, ocean ecology
The ACADIS system expands on the capabilities of the CADIS system, which was designed to serve the specific needs of the Arctic Observing Network (AON). ACADIS is being developed to handle the much larger number and wider range of datasets generated by all NSF-funded arctic investigations. Continual upgrades to the user interface will assist users in authoring metadata, and uploading and accessing datasets. The system will also allow for sharing metadata to improve transparency and interoperability between ACADIS and other data systems.
To meet the community's need for greater integration of research data with other data, ACADIS will provide improved visualization capabilities. These services will allow investigators' datasets to be organized in conjunction with other related datasets on the same display—for example, combining point measurements of sea ice conditions from buoys with gridded fields from remote sensing imagery.
Another goal of the ACADIS team is to improve the usability and interdisciplinary reuse of the data. One facet of this involves developing integrated datasets that can serve a wide range of investigators. Another issue is ensuring that key functions of a project's website remain available after project funding ends. Datasets that are assigned a high level of service will receive extended metadata and documentation to make the data more useable for a broader community. Not all datasets will receive the same level of service; criteria for determining the level of service will be developed with input from principal investigators (PIs), the ACADIS advisory committee, and NSF management.
The ACADIS PI team, led by Mark Serreze of NSIDC and Jim Moore of NCAR, has identified ongoing activities and milestones for each quarter of the project's first year, which address project planning and oversight, data acquisition and ingest, data access, and data preservation. New staff, including two data curators, have been hired, and the core of an advisory committee is in place (see sidebar box). The advisory committee had its first conference call on 21 October. The ACADIS team has also developed a data management plan template and posted it on the CADIS website. It includes accompanying guidelines for investigators seeking NSF funding under the new requirement that all proposals include a viable management plan for data collected or generated by the proposed project. The ACADIS team will work with investigators to fully develop their data management plans; offer continued support for data providers and users; and communicate the standards for observations, data formats, and metadata vocabularies.
The ACADIS PIs will rely on an advisory committee and NSF management to help set priorities and support functions. The PIs communicate these priorities and functions to the data curators and project specialists across the NISDC/UCAR/NCAR team.
An interview with ACADIS PIs Mark Serreze and Jim Moore is included in this issue of Witness. See: Interview.
For further information about ACADIS, please go to: http://www.aoncadis.org or contact Mark Serreze (serreze [at] nsidc.org), or Jim Moore (jmoore [at] ucar.edu).