Data Management

Data Management is central to virtually all aspects of Environmental System Science and the ModEx cycle. Specifically it must provide tools and workflows that support the archival of rapidly growing diverse data streams from the field, informing model representations with archived data, as well as workflows for model data integration and analysis. ESS-DIVE envisions becoming the repository of choice for archiving data generated by ESS projects, enabling the use of data in support of the DOE’s Data-Model Integration Grand Challenge and Virtual Laboratory vision (U.S. DOE 2018, U.S. DOE 2015) and ultimately knowledge generation. However, assessing the data management needs and priorities of the community is challenging, yet it must drive priorities in ESS-DIVE development. The objective of the Data Management (DM) working group is to work with the ESS Community to ensure their short and long-term needs are met by ESS-DIVE in conjunction with other archival and distribution services, such as ESGF. Thus the DM working group will explore

  • Data Preservation, Sharing, and Publication
  • Common Data and Metadata Standards
  • Data Citation and Attribution
  • Data Federation across different data catalogs
  • Data Synthesis across ESS and other relevant Datasets
  • Development of common Tools for data usage
  • QA/QC, processing, analysis, mining and visualization data to prepare them for use in new research projects.

Data Management Leads

Danielle Christianson Danielle Christianson
Lawrence Berkeley Laboratory
Terri Velliquette Terri Velliquette
Oak Ridge National Laboratory

Want to contribute? Ask the leads to join the Google Group: