NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
GES DISC Datalist Improves Earth Science Data DiscoverabilityAt American Geophysical Union(AGU) 2016 Fall Meeting, Goddard Earth Sciences Data Information Services Center (GES DISC) unveiled a novel way to access data: Datalist. Currently, datalist is a collection of predefined data variables from one or more archived datasets, curated by our subject matter expert (SME). Our science support team has curated a predefined Hurricane Datalist and received very positive feedback from the user community. Datalist uses the same architecture our new website uses and have the same look and feel as other datasets on our web site. and also provides a one-stop shopping for data, metadata, citation, documentation, visualization and other available services. Since the last AGU Meeting, we have further developed a few new datalists corresponding to the Big Earth Data Initiative (BEDI) Societal Benefit Areas and A-Train data. We now have four datalists: Hurricane, Wind Energy, Greenhouse Gas and A-Train. We have also started working with our User Working Group members to create their favorite datalists and working with other DAAC to explore the possibility to include their products in our datalists that may also lead to a future of potential federated (cross-DAAC) datalists. Since our datalist prototype effort was a success, we are planning to make datalist operational. It's extremely important to have a common metadata model to support datalist, this will also be the foundation of federated datalist. We mapped our datalist metadata model to the unpublished UMM(Universal Metadata Model)-Var (Variable) (June version) and found that the UMM-var together with UMM-C (Collection) and possible UMM-S (Service) will meet our basic requirements. For example: Dataset shortname, and version are already specified in UMM-C, variable name, long name, units, dimensions are all specified in UMM-Var. UMM-Var also facilitates Science Keywords to allow tagging at variable level and Characteristics for optional variable characteristics. Measurements is useful for grouping of the variables and Set is promising to define datalist. And finally, the UMM-Service model to specify the available services for the variable will be very beneficial. In summary, UMM-Var, UMM-C and UMM-S are the basis of federated datalist and the development and deployment of datalist will contribute to the evolution of the UMM.
Document ID
20170012177
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Li, A.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Teng, W.
(Adnet Systems, Inc. Greenbelt, MD, United States)
Hegde, M.
(Adnet Systems, Inc. Greenbelt, MD, United States)
Petrenko, M.
(Adnet Systems, Inc. Greenbelt, MD, United States)
Shen, S.
(George Mason Univ. Greenbelt, MD, United States)
Shie, C.
(Maryland Univ. Baltimore County Baltimore, MD, United States)
Liu, Z.
(George Mason Univ. Greenbelt, MD, United States)
Hearty, T.
(SGT, Inc. Greenbelt, MD, United States)
Bryant, K.
(Adnet Systems, Inc. Greenbelt, MD, United States)
Vollmer, B.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Meyer, D.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
December 15, 2017
Publication Date
December 11, 2017
Subject Category
Computer Programming And Software
Earth Resources And Remote Sensing
Report/Patent Number
IN21B-0039
GSFC-E-DAA-TN50523
Meeting Information
Meeting: AGU Fall Meeting
Location: New Orleans, LA
Country: United States
Start Date: December 11, 2017
End Date: December 15, 2017
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: 80GSFC17C0003
CONTRACT_GRANT: NNX15AK27A
CONTRACT_GRANT: NNX15AT34A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
datalist
discoverabilit
earth science
No Preview Available