Data Workshops are held on a periodic basis and cover a variety of topics from data access to metadata standards to data models for scientific datasets. See the Calendar of Events for the next scheduled data workshop.
Data Workshops are held on a periodic basis and cover a variety of topics from data access to metadata standards to data models for scientific datasets. See the Calendar of Events for the next scheduled data workshop.
NSF EarthCube WorkshopDecember 17-18 2012
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Latin American Data WorkshopAugust 21, 2008 - August 23, 2008
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Using Data in the Classroom Workshop 2008April 30, 2008 - May 3, 2008
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Community Standards for Unstructured Grids WorkshopOctober 15, 2006 - October 17, 2006
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Marine Metadata Initiative Workshop: Advancing Domain VocabulariesAugust 9, 2005 - August 11, 2005
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DLESE Data Services WorkshopApril 18, 2005 - April 20, 2005
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Special LDM Training SessionFebruary 3, 2005 - February 4, 2005
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LEAD Kickoff MeetingSeptember 29, 2003 - September 30, 2003
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OPeNDAP/NVODS/DODS Technical Working ConferenceMarch 19, 2003 - March 21, 2003
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Questions or comments about the data workshops can be sent to: support@unidata.ucar.edu
Unidate hosted this NSF workshop with the goal of helping shape the development of EarthCube and
help in building an infrastructure that makes it easy to
integrate and use data from disparate sources, allowing
investigators to perceive linkages that today are obscured
by incompatible formats or simple lack of knowledge that the
data they need for their investigations indeed exist. The
overarching goal was to work toward a scientific ecosystem in
which "data friction" is reduced, and data transparency and
ease-of-use are significantly increased.
Unidata, in conjunction with the Universidade de Sao Paulo's Instituto de Astronomia, Geofisica e Ciencias Atmosfericas (IAG) hosted a 
This 
NOAA and the Unidata Program sponsored a workshop to develop 
The 
Sponsored by DLESE Data Services, this 
The purpose of this meeting was to address the fundamental IT research challenges needed to create an integrated, scalable framework for the Linked Environments for Atmospheric Discovery (LEAD) project. The goal of LEAD is to create an integrated and scalable framework for identifying, accessing, preparing, assimilating, predicting, managing, analyzing, mining, and visualizing a broad array of meteorological data and model output, independent of format and physical location.